Monoclonal Antibodies for COVID-19 – An evidence based update

Nicholas McManus — Tue, 18 Jan 2022 16:02:40 +0000

In November of 2020, we discussed the first clinical data for the Monoclonal Antibodies Bamlanivimab and Regenergon (mAb). For a refresher, you can check out the article here. Since that time, researchers have developed several different versions with varying results. There are three mAb products with Emergency Use Authorization (EUA) from the FDA. The National Institutes of Health (NIH) COVID-19 Treatment Guidelines Panel (from here on out, we will just call them “the panel”) recommend the following dosing regimens for non-hospitalized patients with mild to moderate COVID-19 who are at high risk of serious illness.

Bamlanivimab 700 mg plu etesevimab 1,400 mg
Casirivimab 600 mg plus imdevimab 600 mg (a.k.a. Regeneron)
Sotrovimab 500 mg

There have been three pivotal trials that have guided these dosing recommendations. A summary of these three Randomized Controlled Trials driving recommendations can be found in the table below. When looking at this data, you will see different numbers for absolute risk reduction (ARR) versus relative risk reduction (RRR) and warrants a little discussion. If you are not interested, skip to the table (not recommended).

Begin nerdy sidebar...

A relative risk reduction (RRR) tells us how much the mAb treatment decreased the risk of needing hospitalization when the treatment group was compared to the control group (patients who did not receive mAb treatment). While this measurement helps researchers see the benefit of a drug in a trial, patients want to know how much a drug decreases their own risk, and the RRR does not really tell us that.

For example, the RRR for Regeneron was found to be about 71%. That does not mean that you personally have a 71% lower chance of needing to be hospitalized by getting the treatment. It means that when two groups are compared, 71% fewer patients needed hospitalization in the group that got mAb treatment.

Looking closely at the raw data from Regeneron outcomes, there were only five patients in the mAb group vs. 18 patients in the placebo group that even needed to be hospitalized. However, there were about 740 people in each group. So, it is highly probable that you will not need to be hospitalized regardless of getting the treatment (1.5% overall risk of needing to be hospitalized). By dividing five by 18, we can see that ~ 71% fewer people ended up getting admitted if they got Regeneron (that’s our RRR).

When we want to know the individual’s percentage point reduction of overall risk, we need to calculate the absolute risk reduction (ARR). For mAb studies so far, the ARR is the percentage point decrease in risk of hospitalization to the patient if they get the treatment. The ARR considers the entire population at risk of an outcome (i.e., hospitalization). To keep it simple, up to this point, mAb treatment has decreased the absolute risk that high-risk patients will need to be hospitalized by about 3-6%.

While this may sound like a super small number, it really is not. The ARR is almost always low as the risk of a bad outcome is typically low when everyone is taken into account. For comparison, the ARR of Aspirin in decreasing the risk of death after a stroke is 1.3%, and it is considered standard of care by the American Stroke Association. As another example, the RECOVERY trial found corticosteroids to have an ARR of 3% at preventing death from COVID-19. Similarly, a Cochrane review found Tocilizumab to have an ARR of 3% at reducing mortality.

The ARR is also helpful to clinicians, as we can use it to calculate the Number Needed to Treat (NNT). That is the number of patients we will need to treat to prevent ONE bad outcome. In the case of mAb therapy, the outcome measured has been hospitalizations or all-cause mortality.

The NNT is an easy calculation that can really step up your study appraisal game. All you need to know is the ARR. Not all studies will give you the ARR. You can use this online calculator to calculate it yourself if you really want to nerd out.

NNT = 1/ARR

For reference, here are some NNT data for common drug interventions:

Aspirin given immediately for heart attack (STEMI) = 1 in 42 to prevent death
Aspirin after acute stroke = 1 in 79 to prevent death or dependence
Aspirin after acute stroke = 1 in 140 to prevent recurrent stroke
Blood Pressure Medication = 1 in 67 to prevent stroke
Anticoagulation for atrial fibrillation = 1 in 60 to prevent stroke
Steroids for croup = 1 in 11 to avoid repeat visit
Steroids for COPD = 1 in 11 to prevent death

End nerdy sidebar...

Here is a table summarizing the three major RCT’s that drove “the panels” recommendations for mAb therapy.

Sources: Dougan, et al.; Weinreich, et al.; Gupta, et al.

Some things to consider when looking at the data in the table above. The phase 3 Blaze-1 trial (Bamlanivimab plus Etesevimab stopped enrolling patients into the placebo arm after an independent review of the preliminary data. This certainly adds bias to the predetermined outcome data. Further, in the grand scheme of randomized controlled trials, these are relatively small in size. All were underpowered to determine any benefit at decreasing mortality.

I am only discussing the details of these 3 studies, as they include the best data. However, there have been a total of six RCTs looking at outcome data for mAb therapy in non-hospitalized patients with COVID-19. A recent Cochrane review of all of these studies concluded that the certainty of evidence in favor of mAb therapy is low and the evidence is insufficient to draw hard conclusions. There are currently 36 ongoing studies for mAb in this patient group and may provide stronger evidence.

One major factor to highlight is that the dominant strains during the study period for all of the RCTs were pre-delta. Delta wasn’t even first identified in the US until March of 2021 and didn’t become the dominant variant until May of 2021.

Last month, the Mayo Clinic published a study examining the rate of developing a severe infection from the delta variant after monoclonal antibody infusion with Bamlanivimab plus Etesevimab or Casirivimab plus Imdevimab compared to the pre-delta era. Essentially, 3% of people who received mAb treatment pre-delta ended up hospitalized vs. 4.9% of patients who received mAb with Delta with an adjusted odds ratio of 2.04). I only say this as there is a high probability that if the original studies were re-done in the Delta era, the risk of hospitalization would likely be higher. The number needed to treat to prevent one hospitalization would likely be much higher, potentially by a factor of 2.

The lack of data on clinical outcomes with Delta is only one piece of the problem. Newer studies show that variants of concern, particularly the Omicron variant, may not be affected by some current mAb treatments.

In Vitro (not on humans) studies assessing viral susceptibility to these meds suggest that Sotrovimab is likely the only monoclonal Antibody that may still have activity against Omicron. However, to what degree is yet to be fully determined.

To do these in vitro studies, researchers literally take the drug and mix it with different concentrations of either live SARS-CoV-2 or an artificial version of the virus (called a pseudovirus). They then determine what concentration of the virus is needed to decrease viral replication by half. Regeneron and Bam-Etes couldn’t reach this threshold with the Omicron variant, even at super-high concentrations.

Sotrovimab was the only mAB that is currently available that was able to neutralize the virus. Still, it took THREE TIMES the concentration of the drug to neutralize Omicron than it took to neutralize all other variants.

Source figure: Touret et al.

The CDC has a nice summary table outlining which mAb therapies are likely to maintain neutralizing against the different variants.

There isn’t any real-world outcome data on Sotrovimab with Delta or Omicron. Still, the true absolute risk reduction for hospitalization will likely be less than what was seen in the original studies. It certainly still seems plausible that Sotrovimab is better than nothing, but it certainly is not a silver bullet. The cost of these therapies isn’t cheap either. Thee therapies each cost around $2,100 per dose. Currently, patients do not pay this cost directly. The available doses were purchased by the U.S. government and distributed to the states based on need.

As Omicron now makes up over 95% of all new COVID-19 cases in the United States, with daily positive cases the highest of the entire pandemic, hospitals are in short supply of Sotrovimab. Due to this limited supply, many patients who are candidates for mAb therapy cannot get it as supply is shunted to only those at the highest risk.

So, who is at the highest risk?

While some retrospective studies have shown a possible mortality benefit of mAb, these studies were done in the pre-delta era. Similar studies have produced mixed results (Cooper et al.; Ganesh et al.; Pannier et al.). Keep in mind, a definite mortality benefit was not seen in the more extensive randomized controlled trials as well as the Cochrane review.

The RECOVERY Trial (a large ongoing RCT that has driven most of “the panels” recommendations) found that Regeneron did not decrease mortality when all patients were included for analysis.

However, they also found that nearly one-third of all patients who were hospitalized with COVID-19 did not have measurable antibodies at the time of admission. Meaning, the immune system of 1/3rd of patients did not yet produce antibodies by the time they got sick enough to need admission to the hospital (we call this seroconversion). Those who were seronegative (no antibodies present in their blood) were TWO TIMES more likely to die than those who were seropositive (had antibodies in their blood) and also had a significantly higher viral load.

In patients who were seronegative on admission, getting Regeneron at admission decreased the duration of hospitalization by 4 days and reduced the relative risk (RRR) of death by ~18%. Based on the raw data, I am calculating an absolute risk reduction (ARR) of about 5% with a number needed to treat (NNT) of about 20. There was no mortality benefit seen to patients who were seropositive at the time of mAb treatment.

Again, the collection of this data ended in May of 2021, just as Delta was entering the scene. So, we can’t really generalize the data to Delta and Omicron. Still, I would be interested in seeing more studies specifically targeting patients presenting to the hospital and/or being admitted to the hospital and are seronegative as a target for possible mAb therapy, particularly in the setting of limited supply.

Other options on the horizon...

The FDA has recently issued EUA’s that allow two oral antiviral agents to be used in non-hospitalized patients with mild to moderate COVID-19 and at high risk of disease progression. These include ritonavir-boosted Nirmatrelvir (Paxlovid) and Molnupiravir.

Considering the high prevalence of the Omicron variant as well as supply and demand issues, on December 30th, “the panel” updated their recommended outpatient treatment options for COVID-19 (in order of preference):

Paxlovid (nirmatrelvir 300 mg plus ritonavir 100 mg) orally twice daily for 5 days
Sotrovimab 500 mg administered as a single intravenous (IV) infusion
Remdesivir 200 mg IV on Day 1 followed by remdesivir 100 mg IV on Days 2 and 3
Molnupiravir 800 mg orally twice daily for 5 days

Obviously, supply will be an issue for a while. The U.S. government began shipping 65,000 courses of Paxlovid in late December, with a goal of 20 million treatment courses to be delivered by the end of 2022. Discussion of these oral antiviral agents warrants a separate discussion. So, stay tuned…

COVID-19 Vaccines in Pregnancy

Nicholas McManus — Thu, 06 Jan 2022 06:34:07 +0000

Lately, I have been asked numerous times for my opinion on COVID-19 vaccines for pregnant women. While I try not to give my opinion, I base recommendations on currently available evidence. I recommend anyone pregnant or looking to become pregnant discuss the vaccine with their obstetrician. But it is essential to come to the discussion with some background knowledge. So, let’s talk about it…

The Centers for Disease Control and Prevention (CDC), the Society for Maternal-Fetal Medicine (SMFM), and the American College of Obstetricians and Gynecology (ACOG) all have published position statements recommending COVID-19 vaccinations for pregnant women. Unfortunately, despite these recommendations, less than 40% of pregnant women in the United States have been vaccinated against COVID-19, with only 19% of women getting vaccinated while pregnant (CDC, 2021).

So, what safety data do we have?

As of December 2021, over 177,000 vaccinated pregnant women have enrolled in the CDC’s V-safe post-vaccination health checker. V-safe is very different than the Vaccine Adverse Event Reporting System (VAERS). In VAERS, anybody can post what they think is an adverse event to a vaccine. In a previous post, we discussed why this data is notoriously inaccurate and should NOT be used as a sole indicator of vaccine adverse events due to many confounders.

V-safe is a smartphone-based tool that uses text messaging and web surveys to give personalized health check-ins after receiving a COVID-19 vaccine. Through v-safe, you can quickly tell CDC if you have any side effects after getting a COVID-19 vaccine. Suppose you enroll in V-safe and report that you were pregnant at the time of vaccination or after vaccination. In that case, the CDC COVID-19 pregnancy registry staff will contact you several times throughout your pregnancy for health check-ins.

No unexpected pregnancy or fetal problems have been identified from the over 177,000 vaccinated pregnant women registered with V-safe. Specifically, there have been no reports of any increased risk of pregnancy loss, growth problems, or congenital disabilities. Don’t take this as a statement that bad things can’t happen. They do, just not at a rate higher than expected compared to unvaccinated pregnant women. These findings align with what has been seen in several earlier studies on COVID-19 vaccine safety in pregnancy (Shimabukuro, 2021; Kharbanda, 2021).

The most recent study assessing the risks of the vaccine in pregnancy was just published by the CDC yesterday (Lipkind, 2022). They looked at over 46,000 pregnant women and included those who received the initial vaccine series and those who received boosters compared to those who did not receive the vaccine. Overall, 6.6 percent of babies were born prematurely, before 37 weeks of pregnancy, and 8.2 percent were born small for their gestational age, weighing less than 5 pounds and 8 ounces. These numbers were essentially the same compared to pregnant women who did not receive the vaccine.

What data is missing?

The first trimester is when fetal organ development occurs and is often the most at-risk time for the development of congenital disabilities. The most significant limitation in the Lipkind study is that only 1.7% of all vaccinations happened during the first trimester. So, this report really can’t conclude the risk to vaccinated women in the first trimester.

However, we have data suggesting this is unlikely to be an issue. When a new drug or vaccine is being developed, researchers must complete Developmental and Reproductive Toxicity studies (also known as DART studies). DART studies assess effects on male and female fertility, developmental toxicity, and pre/postnatal development.

DART studies have been done for both mRNA vaccines before they were approved. According to the report presented to the European Medicines Agency, animal studies using the Pfizer/BioNTech COVID-19 vaccine do not indicate direct or indirect harmful effects concerning pregnancy, embryo/fetal development, parturition, or postnatal development (EMA).

A DART study of Moderna’s vaccine was done in rats and was reviewed by the FDA. This study concluded that the Moderna vaccine given before mating and during gestation periods did not affect female reproduction, fetal/embryonal development, or postnatal developmental (FDA).

In a DART study of the J&J/Janssen COVID-19 vaccine, female rabbits were administered the vaccine seven days before mating and repeated early in gestation and again late in pregnancy. Furthermore, no vaccine-related adverse effects on female fertility, embryo-fetal, or postnatal development were observed up to postnatal day 28 (FDA 2021).

What is the risks versus the benefits?

It is essential to understand that the overall risk of poor outcomes from COVID-19 in women of childbearing age is still low, but pregnancy significantly increases this risk. As of January 2nd, 2022, there have been 155,587 cases of COVID-19 in pregnant women reported to the CDC (CDC, 2022). Of these cases, the overall risk of hospitalization for COVID-19 was 16.8%, with an overall risk of death at 0.16%. The highest risk was seen in the 25 to 29-year-old age group. When comparing this risk to non-pregnant women, the rate of hospitalization for COVID-19 is over 3 X more likely in pregnant women (Zerbo, 2021).

The risk of adverse effects is higher for every possible outcome from pregnant women who get COVID-19 than in pregnancies with no COVID-19. The July CDC report has a lovely table that breaks it down (see Table 2 in the report). They looked at about 500 thousand deliveries (6,650 of which had COVID-19). 97% of pregnant people hospitalized, either for illness or labor and delivery, with confirmed SARS-CoV-2 infection were unvaccinated. Further, this study shows that pregnant women with COVID-19 have a 2.7 X increased risk of clotting issues, a 35 X increased risk of acute respiratory distress syndrome, a 3.5 X increased risk of renal failure, a 2.2 X increased risk of adverse cardiac event, a 1.2 X increased risk of preterm labor, and a 1.2 X increased risk of stillbirth. In this study, 0.7% of pregnant women hospitalized with COVID-19 died. In contrast, none of the non-pregnant women hospitalized with COVID-19 died, suggesting a 17 X increased risk of death in COVID-19 if you are pregnant. (Ko, 2021).

In studies comparing the risk of hospitalized COVID-19 in women who are pregnant vs. not pregnant, women who are pregnant are 3 X more likely to need ICU care, 2-3 X more likely to require intubation (Panagiotakopoulos, 2020; Zambrano, 2020; Delahoy, 2020)

1.2 X increased risk of preterm labor and stillbirth

3 X increased risk of ICU admission

2-3 X increased risk of needing intubation

17 X increased risk of death

But what about blood clots?

With the Johnson & Johnson vaccine, the CDC reported cases of thrombosis with thrombocytopenia syndrome (TTS) at a rate of about seven cases per 1 million vaccinated women between 18 and 49 years old (0.0007% rate). Of note, the background rate of TTS before COVID-19 even existed was 2-5 cases per million (0.0005% rate). Again, TTS is much more likely to occur with COVID-19 infection at a rate of 39 cases per million (Furie, 2021). It is essential to understand that the excess rate of TTS has ONLY been observed in the Johnson & Johnson vaccine in the U.S. and not with either mRNA vaccine.

Venous thromboembolism (vein blood clots) occurs in women who have not received any COVID-19 vaccine at a rate of 5 cases per 10,000 women. This risk increases to 10 cases per 10,000 women who use estrogen-containing oral birth control. The risk further increases to 8-20 cases per 10,000 women who become pregnant. Again, this is nowhere near the chance of blood clots from COVID-19 infection at a rate of 30 cases per 10,000 pregnant women. Studies assessing the rate of developing any blood clots from either mRNA vaccine have not shown an increased rate of blood clots beyond the expected background rate for women of childbearing age (5 cases per 10,000).

A summary table of the chance of developing blood clots specific to women of childbearing age is outlined below.

¹Todd, et al., 2021; ² Laporte, et al., 2021; ³ Simpson, et al., 2001; ⁴ Haemost, et al., 2008; ⁵ Heit, et al., 2005; ⁶Ko, et al., 2021

Can't the vaccine make me infertile?

There has been a misguided rumor that the COVID-19 vaccine can lead to fertility issues. This misconception arose when a false report surfaced on social media saying that the spike protein on this coronavirus was the same as another spike protein called syncytin-1, which is involved in the growth and attachment of the placenta during pregnancy. The false report said that getting the COVID-19 vaccine would cause a woman’s body to fight this different spike protein and affect her fertility. The two spike proteins are entirely different, and getting the COVID-19 vaccine has not been shown to affect fertility. This was shown in the various DART studies we already discussed. Another study from September of 2021 showed no decrease in success of in vitro fertilization in women who had a COVID-19 vaccine or from SARS-CoV-2 infection (Morris, 2021). During the Pfizer vaccine tests, 23 women volunteers involved in the study became pregnant. Only one person in the trial suffered a pregnancy loss. This person received the placebo and not the actual vaccine.

Something else to consider...

While the purpose of this article is to focus on COVID-19 vaccination data in pregnancy, some generalizable data can help us. Many anecdotal reports of people claiming they see higher rates of strokes and heart disease from the COVID-19 vaccines. This just isn’t supported by the current data. An August 2021 study of 30 MILLION people in Europe showed a slight but statistically insignificant increase in thrombotic events, but nowhere near the rate seen to consider the vaccine a cause of these events and nowhere near the rates seen when someone gets hospitalized for COVID-19 (Hippisley-Cox, 2021). The infographic from this report summarizes the study data nicely.

But I can still get COVID-19 even if I had the vaccine. So what's the point?

It is important to consider the protection offered by the vaccine. An ongoing analysis of outcomes in patients with COVID-19 based on vaccination status is being conducted by the Kings County public health department. Over the last 30 days, their data shows that patients who are not fully vaccinated are 6 X more likely to develop a symptomatic infection, 33 X more likely to be hospitalized, and 45 X more likely to die of COVID-19 related illness.

In conclusion, the evidence regarding vaccine safety in pregnancy favors getting vaccinated to decrease the risk of adverse outcomes. While no intervention is without risk, the risk of not doing anything appears less favorable. People considering vaccination should always discuss this with their doctor as personal aspects of health may play a factor in a risk-benefit discussion.

COVID-19 Boosters….are they necessary?

Nicholas McManus — Fri, 08 Oct 2021 00:45:06 +0000

In mid-August, the Food and Drug Administration amended the emergency use authorizations for Pfizer and Moderna to allow a third dose of their COVID-19 vaccines for certain immunocompromised people

The CDC now recommends a booster for those who received the Pfizer vaccine > 6 months ago and meet the following criteria:

- 65 years and older
- Age 18+ who live in long-term care settings
- Age 18+ who have underlying medical conditions
- Age 18+ who work in high-risk settings
- Age 18+ who live in high-risk setting

Note: Regardless of booster status, the CDC still considers any individual “fully vaccinated” after 2 weeks of completing the primary 2 doses.

At the time of this recommendation, there have been over 42 million cases of documented COVID-19 infections resulting in 700,000 deaths in just the United States. Roughly 55% of the population has received either 2 doses of either mRNA vaccine or the single dose J&J vaccine.

So, what’s the deal? Does this mean the vaccines aren’t working?

Israeli data through July of 2021 raised some serious efficacy concerns for those who received the Pfizer vaccine > 6 months ago. Remember, the initial goal of vaccine effectiveness was 50%. While that may seem like a low bar, this would still be more effective than the flu shot.

This bar chart summarizes the frequently referenced Israel data published in July. Essentially, the two columns on the right show that two doses of the Pfizer vaccine offered substantial protection against hospitalization and severe infection regardless of when people were vaccinated. The light blue bar is those that were vaccinated back in January. While severe illness and hospitalization prevention was still high at six months, the protection against developing symptomatic infection was only 16% when the Delta variant took over as the predominant variant.

Since the Israel data came out in late July, the US has done a few studies. The Mayo Clinic published the following effectiveness rates. At first glance of this data, you see that in July, the effectiveness of the Pfizer vaccine decreased to 42% against developing mild symptoms and 75% against hospitalization. While this makes it look like the vaccine may not be effective against Delta. However, they did not correct for the timing of vaccine administration.

A Pfizer-funded study published October 4th, including over 4 million people vaccinated in the US, suggests the decrease in effectiveness likely has more to do with time since vaccination and less to do with the specific variant. This decline was also seen with other variants. Another important takehome from this study is that regardless of the decrease in effectiveness against symptomatic infection, there remains high protection against hospitalization in vaccinated individuals.

This data is summarized in the graph showing effectiveness against infection (top chart) vs. effectiveness against hospitalization (bottom graph). This research indicates that vaccine efficacy began to decline at a constant rate prior to Delta variant emergence in the US, while protection against hospitalization was maintained.

Source: Tartof, et al.

This trend in a decrease in vaccine efficacy against infection with sustained protection against hospitalization and death has been reproduced several times over. The September briefing from the CDC offers an excellent visual summary of these earlier studies.

Source: CDC

With over 182 million people fully vaccinated in the US, hospitalization rates are 10-22 TIMES higher in those who are unvaccinated ass compared to vaccinated adults.

Source: CDC

So, does the booster offer increased protection?

Israel authorized a 3rd dose of the Pfizer vaccine on July 12 for immunocompromised adults and on July 30 for all adults > 60 years. This was expanded to include all people > 12 years old by the end of August. The caveat is that people had to be at least five months past their 2nd dose to qualify for a booster.

Both studies were rather large, extracting data from the Israeli Ministry of Health database. Both compared people who received a booster dose to those who completed the 2-dose Pfizer series at least five months prior. Unvaccinated patients were not assessed in these studies.

Results of these studies showed that vaccine effectiveness against delta after a booster dose returned to effectiveness levels seen following the 2nd vaccine dose against alpha.

If VE after waning is 50% for INFECTION and increases 10-fold it becomes 95%

If VE after waning is 80% for SEVERE and increases 10-fold it becomes > 97%

A summary of outcomes is listed in the table below.

From this data, it is reasonably apparent that a booster offers increased odds of protection compared to those who have not received a booster. However, both studies are limited in the short follow-up periods, with a maximum of 21 days for documented infection and 16 days for severe disease. It is also important to note that the Patalon et al. study is pre-print and not yet peer-reviewed.

A report from the Israeli Ministry of Health offers a closer look into these benefits. The reproduction number (R0) right before the decision to provide boosters was relatively high, at 1.33, doubling every ten days. Remember from previous posts; if the R0 is > 1, the disease will continue to spread through a community. Our goal is to drive this number below 1.

Source: FDA

Following the booster initiative, this was effectively achieved.

Source: FDA

In a projection model from the Israeli Ministry of Health, delay of just 2 weeks in initiating their booster vaccination program could have led to significant increases in hospitalization and easily exceeded the national capacity.

Keep in mind that vaccines mean more than just personal protection when it comes to public health. It should be obvious to understand that if fewer people get sick, the transmission will also decrease. Data published this week shows that individuals who receive two COVID-19 vaccine doses and later contract the Delta variant are less likely to infect their close contacts than are unvaccinated people. However, this benefit was only seen within the first three months following vaccination.

According to the CDC, the number needed to vaccinate to prevent one hospitalization over six months is summarized below. It is essential to consider that this data is just for the rate of hospitalizations from a booster dose. As discussed in prior posts, disease not requiring hospitalization can still carry significant morbidity, with up to 50% of mild cases having long-hauler symptoms.

Source: CDC Number needed to vaccinate with booster dose to prevent one hospitalization over 6 months.

The largest benefit from booster vaccination is individuals > 65 years of age. The benefit to other ages is incrementally smaller, given higher vaccine efficacy maintained from the primary series at this time. This will likely change as we know vaccine efficacy decreases over time, regardless of age.

Source: CDC: Vaccine effectiveness against symptomatic infection, by age and time since vaccination.

So, are the boosters safe?

The short answer is, they appear to be just as safe as the first two doses. Before the Israeli Ministry of Health briefing on September 17th, 2.8 million booster doses had been given. While under-reporting is expected, ALL hospitalized and deceased patients were independently investigated.

From these 2.8 million doses, we have the following data:

There were 1,328 reports of non-serious adverse events that were like those seen in from the first 2 doses.

Source: FDA

There were 19 serious events reported

Source: FDA

Overall, the immediate safety events from the booster vaccine appear like those seen from the first and second doses. This data is just for the Pfizer vaccine. While rare clotting disorders have been described with the AstraZeneca and Johnson & Johnson vaccines, these have not been associated with the mRNA vaccines. There has been an association with a small increased risk of Myocarditis from the Pfizer vaccine, almost all events occurring in young males. The following infographic was put out by the CDC to address this concern.

Bottom Line:

- 3-fold reduction in symptomatic infection
- 5-fold reduction in severe illness
- Post-booster efficacy against delta is similar to pre-waning efficacy against alpha
- Adverse events appear similar to those seen in the first and second dose

Should those who have had COVID-19 get a booster?

Let’s summarize what we know about prior infection and the vaccines….

In a peer-reviewed study published in June, researchers showed that the antibodies from the vaccine more targeted to the receptor-binding domain of the SARS-CoV-2 spike protein than antibodies elicited by natural infection and had greater binding breadth. This suggests that vaccine-induced immunity was more equipped to handle mutations in this region than those from natural disease.

In another peer-reviewed study from June published in Nature, researchers showed that the Pfizer vaccine produced more neutralizing antibodies than unvaccinated individuals who recovered from COVID-19 but did not require hospitalization.

One month later, a pre-print study of patients who recovered from severe SARS-CoV-2 infection, showed infection produces B-cell responses that continue to evolve for at least one year. During that time, memory B-cells express increasingly broad and potent antibodies that were resistant to mutations found in the current variants of concern. When compared to SARS-CoV-2 naïve patients vaccinated with either mRNA vaccine, natural infection produced antibodies with greater potency and breadth when compared to antibodies obtained from vaccination alone, suggesting those vaccinated following illness will have heightened immune protection.

A study from the Cleveland Clinic tracked cases in healthcare workers who were either vaccinated or previously had COVID-19. They found that the rate of reinfection is essentially the same between the two groups. Another study out of Qatar similarly found that the chance of reinfection is low among those who previously had COVID-19 and those who were vaccinated.

It is important to note that these studies took place before the Delta variant showed up in the United States. Newer data shows antibody response from natural infection is likely similarly suppressed as is seen with the vaccines.

In a peer-reviewed publication from June, research showed that antibody levels obtained after a mild natural infection were similar to getting a single dose of either mRNA vaccine. This suggests that a natural infection essentially serves as the “first dose” of a two-dose vaccine.

Another study in JAMA showed that, compared with unvaccinated participants, those who had received at least ONE dose had higher antibodies and a nearly 50-fold increase in neutralizing activity.

Conslusion

We all knew boosters would eventually be recommended. However, we need to stop considering booster recommendations as a sign of vaccine failure. It certainly is not. The immune system is quite complex. Antibody levels and the humoral immune response are only one part of the equation. Cell-mediated immunity likely plays a significant role, as is made apparent by the sustained benefit of the vaccine at preventing hospitalization and death well past six months. It is quite possible that a booster could provide a more extended and more sustained humoral response, as is seen with other vaccines. The verdict is still out on that, of course.

The booster offers further benefits to public health initiatives. Boosters seemingly decrease transmission as they restore protection to the delta variant close to those seen when the alpha variant was prevalent and have reduced the R0 below 1 in Israel following the initiation of their booster campaign.

Not receiving the booster does not that you are not “fully vaccinated” by the current CDC definition. If you are interested in enhanced personal protection (11-fold increase in efficacy against symptoms) and contribution to the public health campaign, the booster is likely right for you. The safety profile appears no different than that seen in the primary series.

COVID-19 Vaccines – An Evidence Based Update

Nicholas McManus — Thu, 19 Aug 2021 22:51:43 +0000

SARS-CoV-2 is a positive-sense single-stranded RNA virus. Being a single-stranded RNA virus, it is unstable and vulnerable to frequent mutations. There have been over 1.8 MILLION SARS-CoV-2 mutated strains identified and entered into the GISAID database. Fortunately, not every mutation causes a significant enough change for us to lose sleep over. However, several variants of concern (VOC’s) have been identified, and more will inevitably be identified that deserve discussion to understand their interplay with current vaccines available.

But first, let’s pretend we are all budding virologists and set the stage by looking at the SARS-CoV-2 viral genome. The following graphic is a basic representation of the viral structure with the RNA sequence hidden inside that encodes at least 29 proteins.

SARS-CoV-2 structural proteins (SP) are encoded by 4 genes including the E (envelop), M (membrane), S (spike) and N (nucleocapsid) genes. The remainder non-structural proteins (NSP) are mostly enzymes or functional proteins that play a role in viral replication and induce a person’s responses to infection.

The mRNA vaccines contain synthetic mRNA, which serves as a blueprint that codes for just ONE of these proteins, the spike protein (the red box part of the genome in the diagram above). The mRNA itself is quite fragile and the body rapidly breaks down this synthetic mRNA and it is eliminated from the body within a few days. It does NOT enter the nucleus of the cell, it does NOT alter your DNA and does NOT multiply in your body forever, despite false claims that this can happen. In fact, the spike protein is only kept around for about 2-3 weeks to train the immune system. After this, it too is degraded and excreted.

T-cells and B-cells work together during a viral infection (and following vaccination) to induce both a cell-mediated and antibody-mediated immunity, respectively. In cell-mediated immunity, T-cells kill the virus-infected cells. In antibody-mediated immunity, antibodies neutralize the virus itself. The mRNA vaccines mimic a natural infection on a significantly blunted scale. This is with the intention that if your body meets the real virus in the future, it is ready and armed to fight the invader and (hopefully) prevent symptomatic or severe infection. If the vaccine is effective enough, this could potentially even suppress the viral replication enough to decrease the risk of transmitting the virus to another person. As this whole process is short-lived (< 3 weeks), the likelihood of delayed adverse effects (months or years) from this vaccine technology is highly improbable. Especially when compared to natural infection, which does this same process with 28 ADDITIONAL proteins.

I was told the PCR test is counting the flu as COVID-19?

On July 21st, the CDC announced that it will be retiring it’s 2019-nCoV PCR panel. Somehow people interpreted this to mean there was an issue with the accuracy of the test. It is not being retired because it can’t tell the difference between influenza and SARS-CoV-2. That is false. It is being retired because there are more efficient tests now. We used to have to obtain multiple different swabs to test for different infections (i.e., one for influenza, one for SARS-CoV-2 and one for RSV). The new swab will be able to check for all of these with one swab. That’s only one swab that needs to be shoved into the nose of a patient instead of three. Plus, there are over 250 different PCR tests currently approved for emergency use to detect COVID-19.

How do we know these tests don’t accidentally measure the flu as COVID-19?

Because the test was developed to look for the presence of a nucleic acid found only in the covid virus. It has been studied before it was ever approved to make sure it didn’t react with other viruses.

So, what’s the deal with these variants?

Viruses mutate, as should be very apparent to everyone at this point. However, not all mutations have significant consequences while others do. A common point of misinformation currently circulating is that viruses can only mutate to become less lethal. This is not accurate. While it certainly would be in the best interest of a virus for it to be less lethal and more transmissible, it is not always possible to be both.

Viruses are constantly changing in multiple ways. Antigenic drift occurs when the genes of a virus go through a series of small changes until the host organism’s immune system no longer recognize the virus. This is often caused by point mutations in a gene and can result in epidemics (large infections in a single community). More dramatically, antigenic shift occurs when the virus undergoes a more abrupt change so drastic that a large portion of the population does not have adequate immunity.

This has been the cause of four major influenza pandemics since the 19^th century. The Ebola outbreak in 2016 is another example of evolutionary changes that resulted in a more transmissible and more lethal illness. Other examples include Zika virus and Hepatitis B to name a few. Not to mention that it has already been documented in several SARS-CoV-2 variants (Peer reviewed sources here, and here, and here, and here, and here.)

Plus, you can’t overlook the fact that even if the virus is less lethal, it can certainly still cause an excess of death when the healthcare system is over-run with everyone getting ill at one time. This has been demonstrated repeatedly through this pandemic on a global scale and likely a major factor in the wide range of case fatality rates between regions over time.

LOWER mortality does not always mean LESS mortality...

For example, let’s say we have two viral strains. One is 50% more lethal but less transmissible. The other is less lethal but 50% more transmissible. Initially, the more lethal strain will cause more deaths. However, over time, the more transmissible strain will cause an exponential growth in the number of infections, ultimately causing significantly more death. While it certainly is possible that the SARS-CoV-2 virus will eventually mutate into less lethal strains over time, it does not negate the fact that there is still a significant amount of chronic illness and mortality associated with the current strains circulating at this time.

Variants of Concern (VOC)

VOC’s are variants that demonstrate one or more of the following:

1. 1. Increase in transmissibility
  2. Increase in virulence of change in clinical disease presentation
  3. Decrease in effectiveness of public health and social measures or available diagnostics, vaccines, therapeutics

There are currently four VOC’s being tracked by the WHO, although multiple others are expected to arise over time as data evolves. Here is a collection of data obtained and reviewed from the CDC, the ECDC and the WHO on VOC’s.

Alpha Variant

United Kingdom, September 2020

Key Spike Protein Mutations: N501Y, A570D, D614G, P681

50% increased transmission than earlier strains (R₀ 4-5)
Potential increased severity based on hospitalizations and case fatality rates
Monoclonal antibody treatments still effective (BAM fact sheet, Regen-CoV fact sheet)
Vaccines very effective against symptomatic infection, hospitalization, death, and possibly transmission
7 x more likely to require hospitalization
2.3 x more likely to require admission to the Intensive Care unit

Beta Variant

South Africa, May 2020

Key Spike Protein Mutations: K417N, E484K, N501Y, D614G

50% more transmissible than the original strain (R₀ of 4-5)
Monoclonal antibodies Bamlanivimab and Etesevimab are not effective
Monoclonal antibody Regeneron is sill effective
9.4 x more resistent to antibodies to prior infection
10.3 to 12.4 x more resistant to vaccination (Wang et al., Wu et al., Madhi et al. Cele et al.)
Possibly more severe infection (Pearson, et al., Funk, et al.)
6 x more likely to require hospitalization
3 x more likely to require admission to the Intensive Care Unit
1 x more likely to result in death

Gamma Variant

Japan/Brazil, November 2020

Key Spike Protein Mutations: K417N/T, E484K, N501Y, D614G

2.4-fold more transmissible
Previous infection provides only 54-79% protection against reinfection
Significantly reduced susceptibility to the monoclonal antibodies Bamlanivimab and Etesevimab
Monoclonal antibody Regeneron (Regen-CoV) still appears to be efficacious
3.4 x more resistant to antibodies from prior infection
3.8-4.8 x more resistant to vaccination
6 x more likely to require hospitalization
2 x more likely to require admission to the Intensive Care Unit
60% less likely to result in death

Delta Variant

India, October 2020

Key Spike Protein Mutations: L452R, T478K, D614G, P681R

Currently the cause of 98% of all cases in the United States
64% more transmissible than alpha variant
200% more transmissible as the original Wuhan strain (R₀ 5-8)
Potential reduction in neutralization by some monoclonal monoclonal antibody treatments
9 x more resistant to antibodies from prior infection and vaccination
86% increased risk of hospitalization if unvaccinated
62% less likely to require hospitalization if vaccinated in Scotland
Fully vaccinated people with breakthrough infections from this variant appear to be infectious for a shorter period to time
Produces 1,000 X more viral particles than other variants
Remain infectious longer (18 days vs 13 days)
P681R mutation. The mutation lies at the junction between two subunits of SARS-CoV-2’s spike protein, at a site that allows the human cellular enzyme furin to cleave the spike into two parts. This cleavage, some experiments suggest, primes spike proteins in a way that allows them to fuse more readily with a host cell’s membrane, according to a detailed description in Nature.

Lambda Variant

Peru, December 2020

Key Spike Protein Mutations: L452Q, F490S, D614G

Not currently a VOC, but likely will be in the future
Highly infectious and T76I and L452Q are responsible for this property
RSYLTPGD246-253N, L452Q and F490S confer resistance to antiviral immunity
mRNA vaccines still highly effective
3.05 x reduction in neutralization of Lambda variant from inactivated virus vaccine CoronaVac
Regen-CoV monoclonal Ab still effective

So, does the Delta variant cause more lethal disease?

The answer is a bit complicated. We know that the delta virus produces a much higher amount of virus (viral load) in patients than was seen with earlier strains of the SARS-CoV-2 virus. We are talking 1,000x more virus being present when infection occurs. As we know from several studies, the more virus that is present, the more severe the infection tends to be. This is the whole premise behind treatments with monoclonal antibodies like Bamlanivimab and Regen-CoV, which work by decreasing viral load.

One Canadian study suggested the Delta variant is associated with a 120% increased risk of hospitalization, 287% increased risk of ICU admission, and 137% increased risk of death compared to the original Wuhan strain.

Scottish researchers published a paper in the Lancet in June showing a 2-fold increase in the rate of hospitalization in patients infected with the Delta variant, suggesting it causes more severe infection. Further, based on data from December 2020 through March 2021 looking at the Alpha, Beta, and Gamma variants, we know that all of these variants were also associated with an increased rate of severe disease, hospitalization, and ICU admission. Still, fortunately, this was not associated with an overall increase in the rate of death.

Bottom Line: The verdict is still out regarding whether the Delta variant is more lethal. But there is more to the story…

The Delta variant is significantly more contagious...

We know that the Delta variant is significantly more contagious than other strains. It has a current estimated reproductive number (R0) of 5-8. Meaning each person infected will infect another 5-8 people, on average.

However, despite a significant increase in cases, we aren’t really seeing a corresponding increase in death like we did with other community outbreaks over the last year and a half. So, what gives?

Is this the effect of the vaccine, or is Delta less deadly?

This decrease in death only appears to hold true in areas where vaccination is over 50%. Ukraine is one of the least vaccinated countries, with only 6% of their population fully vaccinated. Deaths in Ukraine from the current outbreak follow a trajectory that more closely mirrors what we have seen before vaccines were available.

Source: Reuters

Hopefully, the overall trend seen in highly vaccinated continues, and the mortality of this virus stays low. That would be the ideal situation, and it is certainly possible. Based on data from the U.K., the Delta variant currently has a low case fatality rate of just 0.2% for the general population. This is likely because a large portion of the people most at risk of dying from COVID-19 has been vaccinated in the United Kingdom. Most Delta variant hospitalizations occur in those under the age of 50 and in those who are unvaccinated. So, we cannot simply use the data we have today and compare it to early 2020, when we knew significantly less about this virus today, to determine if it is more lethal in comparison. Regardless of severity, this is not the only marker for public health concerns.

The Delta variant causes similar amount of virus in vaccinated and unvaccinated...

In a pre-print study of 218 patients with Delta variant infections, those vaccinated had viral loads that were essentially the same as those who were unvaccinated. This contradicts data from breakthrough cases seen in earlier variants suggesting the vaccine may no longer protect against transmission. While this is a huge bummer, there is some positive data from this study.

We already know that a high viral load is associated with more severe illness. In this study, despite equal viral loads at the time of diagnosis, those who were vaccinated had a significantly more rapid decrease in the amount of virus they produces as well as much less severe illness (see table).

Similar reports of viral load have been seen in other cluster outbreaks, suggesting it is highly probable that vaccinated patients can spread infection from the Delta variant. This makes herd immunity significantly more challenging to obtain through vaccinations alone. Again, this is a bummer. Although we do have more evidence that vaccines offer significant individual protection and likely lowers your chance of dying if you get infected.

But the news says vaccinated people are testing positive. Does that mean the vaccines aren't working?

Compared to the original virus, all the variants thus far are better at evading the immune system’s antibody response, some better than others. That’s because so-called neutralizing antibodies recognize and bind to the spike proteins on the virus’s surface, preventing the virus from infecting cells. But if the virus mutates its spike protein, then the antibodies may not bind as well, and the virus gains an advantage.

Having a certain portion of vaccinated patients become infected is completely expected. The vaccine isn’t an impenetrable forcefield (it would be a lot cooler if it were). It is a layer of armor to offer protection comparable to wearing a seatbelt while riding in a car. It won’t completely prevent death and debility, but it should still make those situations much less likely if used correctly. The CDC stopped collecting data on all symptomatic breakthrough cases in April (they still collect data on hospitalization and death). Fortunately for us, most states continue to collect this data and can be accessed here and in the picture below.

As you can see, even as the Delta variant makes up most cases in the United States, the vast majority of symptomatic cases are occurring in those who are unvaccinated.

Remember, the initial goal of vaccine effectiveness was only 50%. While that may seem like a low bar, this would still be more effective than the flu shot. When the CDC removed the mask mandate for vaccinated individuals in May of 2021, the dominant circulating variant was Alpha. The breakthrough rate of infection was very low, and those breakthrough cases had very low viral loads, suggesting a low rate of transmission if you were vaccinated.

So, what is the available data from around the world telling us about the vaccines’ effectiveness? Let’s look at the significant studies.

Qatar - July 9th, 2021

Chemaitelly, et al., 2021

Assessed vaccine efficacy for Moderna against Alpha and Beta variants for hospitalization and death
Qatar has a population that comprises mainly working-aged adults
Used a matched test-negative, case-control study design

United Kingdom - June 14th, 2021

Stowe, et al., 2021

This is a pre-print study that has not been peer-reviewed
Estimated vaccine efficacy against symptomatic disease and hospitalization

Scotland - June 14th, 2021

Sheikh, et al., 2021

19,543 confirmed SARS-CoV-2 infections included in analysis between April 1 and June 6, 2021
At the start of the study period, only 7.6% of the population was fully vaccinated
Increased to 39.4% by the end of the study period
Vaccinated patients were 62% less likely to require hospitalization

UK REACT-1 Study - pre-print

Elliott, et al., 2021

989,233 volunteers screening for prevalence of COVID-19 in the UK
Used self-reported vaccination status and patients swabbed themselves at home
527 tested positive (100% of these were the Delta variant)
44% of infections occurred in fully vaccinated individuals
Highest prevalence of infection was among people 12 to 24 years old

Results:

1 in 26 chances of being infected with Delta variant if you were exposed and vaccinated
1 in 13 chances of being infected with Delta variant if you were exposed and unvaccinated

United Kingdom - August 12th, 2021

Bernal, et al., 2021

A total of 19,109 people included in this study
Compared vaccination (Pfizer and AstaZeneca) status in persons with symptomatic Covid-19 with vaccination status in persons who reported symptoms but had a negative test
Then did a secondary analysis for Alpha or Delta variant

Israel - July 23rd, 2021

Recent data from Israel is a bit more concerning about the ability of the current vaccines to prevent symptomatic infections with the Delta variant. Before you panic, let’s look at the actual data in more detail. The purple bar represents all vaccinations to date, and the colored bars represent the month of vaccination. Regardless of when the person was vaccinated, there is a high effectiveness rate against hospitalization and severe COVID-19.

However, the vaccine’s effectiveness against all infections was 39% in this study regardless of when people were vaccinated. More concerning is that those who received their vaccines in January 2021, were only 16% protected against developing an infection. Fortunately, the protection against hospitalization and severe COVID-19 is still very high (82% and 86%, respectively).

Qatar - August 11th, 2021

Tang, et al., 2021

Pre-print study (not yet peer reviewed)
To determine the effectiveness of Pfizer and Moderna against Delta variant from March to July against all infections (symptomatic or asymptomatic)

Why does the Israel data look so different from the United Kingdom?

I don’t think we have a definite answer yet. A few notable differences are important to note:

First, vaccine strategies were not the same: Israel was aggressive with providing as many people a 2-dose regimen and stuck to the 3-week interval between first and second doses. On the other hand, the UK delayed many of their second doses by 12 weeks to offer a larger initial spread across their population. This may have provided the UK a significant advantage. Studies such as this one and this one have shown that increasing the time between dosing intervals offers a more robust immune response.

Secondly, there could be waning immunity: Clinical data shows antibody levels persist for at least 6 months following vaccination and that neutralizing antibody levels are highly predictive protection against symptomatic infection. However, as we just observed, the Pfizer vaccine may lose its effectiveness to protect against symptomatic infection over time. More data needs to emerge to determine if this is the reason for the differences between the UK and Israel vaccine effectiveness.

The more critical take-home message here is that Israel and the UK have > 60% of their populations vaccinated; both had surged in cases with the Delta variant WITHOUT any significant surges in severe cases or death. It is too early to entirely blame waning immunity as the cause of differences in the data between the UK and Israel. However, based on this data, I would not be surprised if we see new recommendations for booster vaccines in the coming days to weeks.

A follow-up study published out of Oxford University on August 12^th showed the effectiveness of the Pfizer vaccine against symptomatic infections begins to drop after 3 months. In light of this data, Israel began administering booster vaccines to those 50 years of age and older. So far a total of 1.1 million booster shots has been administered (roughly 12% of their population). A Maccabi Healthcare Services study then surveyed 150,000 of these patients and compared them to a sample of patients who received their second dose of the vaccine in January and February. They found, that with a booster, the efficacy of the Pfizer vaccine against all infections (not just hospitalizations and death) increased to 86%.

How does this compare to what we are seeing in the United States?

The Mayo Clinic published data of the mRNA vaccines over a 7-month period covering both the time when the Alpha variant was the predominant strain and when the Delta variant became the predominant strain. The three groups analyzed included unvaccinated individuals, those who were fully vaccinated with Moderna, and those who had been fully vaccinated with Pfizer. This was conducted with patients across multiple Mayo Clinic Health System sites in multiple states (Minnesota, Wisconsin, Arizona, Florida, and Iowa). Results of vaccine effectiveness is outlined in the table.

While the data clearly seems to favor Moderna, it should again be stressed that both vaccines retained significant protection against hospitalization during July, at 75-81%, a decline from May of just 12-14 points. Likewise, in the earlier UK analysis Pfizer and AstraZeneca showed continuing efficacy against hospitalization due to the Delta variant, even though you aren’t as protected from developing a symptomatic infection.

A study that was just published on August 18^th from the CDC, looked at the rate of hospitalizations in New York between vaccinated and unvaccinated from May through July as the Delta variant became the dominant strain making up over 98% of infections. As expected, they found the rate of effectiveness of the vaccine declined from 91.7% to 79.8% over the summer months. However, vaccine effectiveness against hospitalization remained stable at 91.9% to 95.3% as hospitalizations in unvaccinated patients continued to increase with the Delta variant.

But, the news is telling me that outbreaks have more vaccinated cases than unvaccinated. Does that mean these large international studies all got it wrong?

On August 6^th, the CDC released a report of an outbreak of COVID-19 cases following multiple large public gatherings in Barnstable County, Massachusetts in July. Headlines of this outbreak peppered media headlines and the country lost their minds…so let’s unpack what really is going on here.

There were 469 cases during events over July 4th that attracted over 60,000 people to the area. The baseline vaccination rate in Massachusetts at the time of this study was 69%. Of the 469 cases, 90% were thought to be the Delta variant based on random genetic testing of 133 samples. While 74% of the positive patients were fully vaccinated, 21% were asymptomatic, 1.2% were hospitalized, and no deaths were reported. Again, viral load was similar in vaccinated and unvaccinated patients.

The biggest shock behind this data is that some are misinterpreting the results as a failure for the vaccine. At first glance, the 74% number was suggested by some to mean you are more likely to get infected if you were vaccinated. In cognitive psychology, judging an outcome without understanding the base rate of vaccinations is known as the base rate fallacy.

For example, did you know that the vast majority of surgical-related deaths involve right-handed surgeons? Is that because right-handed surgeons aren’t as good as left-handed surgeons? No, it’s because 90% of surgeons are right-handed.

For example, if 83% of the population is vaccinated and there is an outbreak with 50% of cases occurring in the vaccinated group and 50% of them occurring in the unvaccinated group. This is what it could look like…

Headlines would read (as they did with Israel), “50% of COVID-19 cases occur in vaccinated). You don’t have to be an epidemiologist to understand that the group on the left looks very different than the group on the right. While each group has the same number of infected individuals, the rate of infection amongst vaccinated individuals is 2%, while the infection rate in unvaccinated individuals is 6.5 times more likely.

How about a real-world example specific to COVID-19. Iceland is currently experiencing a surge in cases, with 67% occurring in vaccinated people. Iceland is a bit easier to use as a reference of understanding as we don’t know the vaccination status of all the visitors to Barnstable County, Massachusetts. So, is Iceland showing the world that vaccines don’t work?

Let's break it down...

There were 2,239 total positive cases in Iceland from July 9th to August 10th. Of these, 1,503 were vaccinated, and 684 were unvaccinated. 86% of the population is fully vaccinated, with a total population of about 357,000 (90% of men and 96% of women have received at least one dose of a vaccine, and children are currently not eligible).

When we correct for the baseline vaccination rate in each group….

We see that the baseline rate of breakthrough cases in vaccinated people is 6 per 1,000, while the infection rate for unvaccinated patients is 18 per 1,000. Therefore, the actual rate of infection is 3x higher than that for vaccinated people. On top of that, Iceland is one of the most vaccinated countries globally, and despite this outbreak, there have been ZERO Covid-related deaths since late May.

My point with this exercise is that headlines do not negate the fundamentals of scientific data. Yes, it concerns that current vaccines do not appear to offer protection against the transmission of the disease. Yes, it worries that newer strains are less effective against the present variants. However, the vaccine continues to provide strong evidence of protection against severe disease. In a July 25th report from the National Center for Immunization and Respiratory Disease, the vaccine offers

1. 1. 3-fold reduction in risk of infection
  2. 8-fold reduction in risk of symptomatic disease
  3. 25-fold reduction in risk of hospital admission or death

At the time of this report, a total of 6,239 hospital admissions and 1,263 deaths have occurred in vaccinated patients. 98% of cases in Michigan and 97% of all cases nationwide are in unvaccinated or incompletely vaccinated people. This is an incredible thing, considering COVID-19 was the LEADING cause of death in the United States just eight months ago.

Source: Peterson-KFF Health System Tracker

Will variants eventually evolve to evade vaccines completely?

So, we know that mutations are occurring, and there is concern those mutations could eventually evade the current protective response to the vaccines. In the UK, the expert advisory board SAGE predicted that new variants would eventually overcome existing vaccines. Just as antibiotics breed resistance in bacteria, vaccines can incite changes that enable diseases to escape their control.

Fortunately, we have data that shows the vaccines can lower the rate at which mutations are generated. In a pre-print longitudinal analysis of over 1.8 million SARS-CoV-2 genomes from 183 countries or territories, vaccine breakthrough patients harbored viruses with significantly lower diversity than unvaccinated patients. Meaning, this could be evidence that COVID-19 vaccines are fundamentally restricting the evolution of new variants.

Of course, this will only matter if we become more aggressive with vaccination on a global scale. One of the best hopes of winning this contest is to get as many people immunized now as possible to reduce the likelihood of even more variants appearing that might evade protection for the current vaccines.

How does natural infection compare to the protection of the vaccine?

Evidence of natural immunity from SARS-CoV-2 infection versus vaccination is a bit mixed and something that should be more aggressively studied, particularly in the face of vaccine resistance.

In a November 2020 study from the University of Missouri School of Medicine, researchers showed that < 1% of patients who recovered from a severe COVID-19 infection were re-infected. Of those that were, the average time of reinfection was 3.5 months, and 3.2% of those patients died.

A large multicenter study published in The Lancet in April, showed that those with a previous COVID-19 infection had an 84% lower risk of becoming re-infected and a 93% lower risk of symptomatic disease over the 7-month observation period. Further, data published this month show antibody levels to SARS-CoV-2 remain high up to 13 months post-infection, even with mild infections.

Then, on August 13th, the CDC released a study comparing the effectiveness of COVID-19 vaccines versus natural immunity from prior SARS-CoV-2 infection. In this study, being unvaccinated was associated with 2.34 times the odds of reinfection compared with being fully vaccinated. A concurrent study showed the Pfizer and Moderna vaccines prevented 96% of hospitalizations, and the Johnson & Johnson vaccine prevented 84% of hospitalizations in adults aged 65-74 years old. It is important to note that these studies took place before the Delta variant showed up in the United States. Newer data shows antibody response from natural infection is likely similarly suppressed as is seen with the vaccines.

It is essential to point out that none of these studies included the Delta variant in the analysis. If you have had prior infection, you likely have some level of protection. Getting vaccinated after an infection has been shown to give people a substantial boost in neutralizing antibodies.

While there isn’t as much robust data on protection from natural infection as there is for vaccines, it is reasonable based on current data to infer that your risk of reinfection would be similar to those who are partially vaccinated. This aligns with data from the CDC study showing 2.34 times increased odds of reinfection. In this study, patients requiring hospitalization had antibody levels that were much higher, effectively identical to those who have received both doses of an mRNA vaccine, but this started to wane after 6-8 months.

Another study in JAMA showed that, compared with unvaccinated participants, those who had received at least ONE dose had higher antibodies and a nearly 50-fold increase in neutralizing activity.

Bottom line: Reinfection is rare due to the complex nature of our immune systems. While you likely have a good deal of protection from natural immunity, you would most certainly benefit from vaccination, especially if your course was mild on your initial infection. Based on timing on reinfection and waning antibodies, the time at which this should be done hypothetically appears to be ideal, around 1-2 months following a mild infection and 3-6 months following a severe infection. Some evidence suggests those with prior infection (even if mild) may have an equal or higher benefit to a single dose of the vaccine compared to those who were uninfected but received two doses.

Is herd immunity still even possible?

The herd immunity threshold is generally agreed to be the proportion of the population that needs to be immune to tip a disease into decline. It occurs when the “typical” person goes on to infect fewer than one other person due to naturally acquired or vaccine-induced immunity. The idea underlying herd immunity is that the proximity of immune individuals shields others who are still susceptible to infection, Fine explains. And, with enough immune people in the population, the herd becomes a defensive wall that denies the virus pathways to keep spreading. Pre-variant models predicted that 67% of the people would need to get vaccinated to reach herd immunity.

With data showing variants have the potential to decrease the effectiveness of vaccines against asymptomatic infection and with newer data showing vaccines may not reduce the rate of transmission as they initially did, this certainly seems like a less obtainable goal long term.

Our best tool in the fight to herd immunity would be to get everyone vaccinated before we meet a variant that renders our vaccines ineffective. This is seemingly becoming unobtainable given the apparent war against vaccination. In some sense, vaccination is now more relevant to personal protection instead of protecting the herd, which was not the case 8 months ago.

Some people say the vaccines can make COVID-19 worse if you get infected...is that true?

When people say this, they are referring to a process called antibody-dependent enhanced (ADE). ADE is when a disease is made worse or more severe in a person already exposed to the virus through previous infection or vaccination compared to people who were never exposed or vaccinated. ADE has occurred with vaccines in the past in the 1960s to Respiratory Syncytial Virus and Measles and in 2016 to Dengue. However, it isn’t unique to just vaccines but seen from the natural illness itself.

A quick primer…

There are four different strains of the Dengue virus. If you get infected and recover from one strain and get infected to another strain, ADE occurs, and your illness is significantly more severe than it was the first time.

People are worried that ADE could happen with the SARS-CoV-2 virus. This is because there was suspicion from some of the animal models with vaccines studied with the initial SARS-CoV-1 virus in 2002. In these studies, hypersensitivity reactions similar to ADE were seen. However, there are several reasons why it’s improbable to happen with the current vaccines.

Since the early stages of vaccine development, scientists targeted a protein on the virus that was least likely to cause ADE.
Most people have been infected with other coronaviruses in their lifetime, and ADE has not been identified as a result of these infections.
Experimental animals vaccinated against SARS-CoV-2 did not develop enhanced disease when challenged, or infected, with the virus.
In human studies, people previously infected with coronavirus were infected with different types of coronavirus, and they did not experience enhanced disease.
When people with COVID-19 received plasma containing SARS-CoV-2 antibodies, they did not experience enhanced disease.
If ADE was occurring, you wouldn’t just see cases with vaccinated patients. You would see significantly worse disease for those who are re-infected or infected after vaccination. We aren’t seeing that. In fact, we are seeing the opposite. ADE is an acute problem, if it was going to be an issue, we would have seen it by now. At least for the current known strains.

Bottom Line: The concerns that were raised by what happened with SARS-1 are understandable, but we now have six separate pieces of evidence that suggest that ADE is not currently an observed problem with this virus or with this vaccine associated with this virus.

But, I heard these vaccines are toxic to my cells...

A video is currently circulating saying the mRNA vaccines are toxic to the body. Specifically, they claim in the video that the mRNA vaccines produce a spike protein that is toxic to cells based on a paper saying the spike protein impairs blood vessel function. The only problem with this is the article was written based on the spike protein from natural SARS-CoV-2 infection and NOT from the vaccine.

The spike protein produced from the mRNA vaccines is similar but not identical to that of a natural infection. Research shows that only 1% of the spike protein injected by the vaccine even enters circulation, if at all. The liver rapidly destroys the part that does. The mRNA does not stay in the body and is gone within two weeks. There is no actual evidence that the spike protein from the vaccine can hurt normal, healthy cells.

So, what is the current known risk of getting COVID-19?

The age-adjusted death rate increased by 15.9% in 2020, compared to 2019. 345K deaths had COVID-19 as a contributing cause in 377.883 deaths (91.5 per 100,000 people or 11% of deaths). Throughout most of 2020, COVID-19 was the 3rd leading cause of death in the United States, rising to the #1 spot in January before abruptly falling to 7th place after initiation of vaccines.

For most of the pandemic, assessing the actual number of patients who have been infected or died from COVID-19 has been difficult. Johns Hopkins has a well-organized tracker of case fatalities (the number of deaths vs. the number of known positive cases) for those interested in this data. Meaning, for all patients who tested positive in the U.S. by swab, 1.7% of them have died.

As discussed in previous posts on this topic, the case-fatality rate is not the most accurate measure of mortality from a virus. Not all cases obtain a diagnostic swab, and tracking all cases is a nearly impossible feat. The CDC estimates that only 24% of all infections and 26% of symptomatic infections are reported. Further estimates suggest that only 55% of hospitalizations and 77% of COVID-19 related deaths were reported. Therefore, in July of 2021, the CDC released estimated adjustments of symptomatic illnesses, hospitalizations, and deaths in the United States. Following this, social media exploded with misleading claims minimizing the overall risks of the SARS-CoV-2 virus.

For example, based on the CDC adjusted estimates, if someone between 18 and 49 years old develops a symptomatic COVID-19 infection, they would have just a 0.07% chance of dying. That means there is a 99.97% that person will ultimately survive. But is this the only measurable outcome that matters to the population as a whole? Absolutely not.

LOWER mortality does not always mean LESS mortality...

Using this same data set, that same age bracket has a 2.5% chance of being hospitalized if they develop symptoms of COVID-19. That means, for every 50 people infected, one will require hospitalization. In a community where 2,000 people get infected simultaneously, 40 of them will need to be hospitalized in just this seemingly low-risk age group alone. With hospital and ICU shortages at critical levels across the country, this is an enormous issue from a public health perspective. This is one way that negating the risk of SARS-CoV-2 on an individual level has the very real potential to increase the risk to the entire community.

When scientific researchers define the quality of evidence, expert opinions and case reports have the least evidence, while randomized controlled clinical trials are near the highest quality of evidence. The large studies for the COVID-19 vaccines gave us a rather good insight into the overall safety expectations of these vaccines.

The results of these studies are covered in detail in an earlier post. We know that the overall incidence of serious adverse events is relatively low. These studies included a large number of people compared to other vaccines.

The average size of phase 3 vaccine trials to assess early adverse events ranges from 2,358 to 80,427 participants. The mRNA trials for the COVID-19 vaccine included 70,000 participants.

I believe a big misconception about safety monitoring from this point out is that people are waiting for some larger trial showing more information years down the road. This is unlikely to happen because it would be very abnormal for this to occur with vaccine studies. Once a vaccine is approved by the FDA in phase 3 trials, it is rolled out to the general population. At that point, it would not be ethical to keep a control group for the vaccine.

Vaccine history tells us that while a delayed adverse effect of a vaccine can occur, it will most likely happen in the first 6-8 weeks. Vaccines are not like a medication you take for years and years and then develop some rare cancer. With the mRNA vaccines particularly, the effective risk of an adverse event is substantially lower than the risk of natural infection (more on this later). Your body uses the mRNA, and it is degraded within two weeks and excreted from the body. It doesn’t hang around. Even if the spike protein made by the mRNA were toxic to your body, it wouldn’t be more harmful than the spike protein produced by the SARS-CoV-2 virus itself. It just isn’t probable.

So, instead of long-term trials, vaccine adverse events are monitored with self-reporting systems such as the Vaccine Adverse Event System (VAERS) in the United States and Yellow Card in the United Kingdom. At this point, most governmental bodies have some sort of reporting system for this purpose.

It is critical to understand that these systems are not designed to catch every person with a vaccine adverse event. That baseline data is obtained from the original safety trials. Instead, they are intended to pick up trends in conditions that are so rare that they could have been missed in the initial studies (i.e., something that occurs in more than 1 in 70,000 cases for the mRNA vaccines).

It is also essential to know that these reporting systems are like the app “Yelp.” Anyone can report something into the database, and just because it is there doesn’t mean it is accurate or that there aren’t multiple reports for the same incident. I can go on there and say I got a vaccine and my head fell off, and it would add to the count of reported deaths. So, when you see 9,000 death reports listed on this system, it does NOT mean there were 9,000 deaths from the vaccine by any means.

The CDC reviews every report that is made in VAERS. Medical charts are reviewed, and those cases are followed up for accuracy. There have been 4.78 billion doses of COVID-19 vaccines delivered. It is a statistical probability that a portion of those people would have developed a disease or died regardless of whether they got the vaccine. If a medication or a vaccine causes disease, it isn’t going to do it 1,000 different ways. Again, the purpose of these reporting systems is to find TRENDS in disease that occurs at a higher than expected rate in the general population. Knowing the background rate for a particular condition is extremely important when determining disease trends.

So, what adverse events have been identified?

Thrombosis-Thrombocytopenia Syndrome (TTS)

General background rate: 2-5 cases per million people per year (CVST)
Rate from COVID-19 INFECTION: 39 cases per 1 million infections
Rate from COVID-19 VACCINES:
- CDC: 7 cases per 1 million vaccines
- Australia: 7.5 cases per 1 million vaccines (14 cases per 1 million AstraZeneca vaccines) – 6 deaths
- Canada: 1.4 cases per 1 million vaccines

TTS is a syndrome characterized by a blood clot in the brain’s veins (central venous sinus thrombosis) in conjunction with thrombocytopenia (low blood platelet counts). As of August 11th, this phenomenon has been seen in 42 patients who received the Johnson & Johnson vaccine and a few reports in Europe in people who received the AstraZeneca vaccine. Two cases were reported in VAERS from the Moderna vaccine. No cases have been reported from the Pfizer vaccine.

This adverse event is rare, with an overall occurrence rate of about 7 per 1 million vaccinated women between 18 and 49 years old. For women 50 years and older and men of all ages, this adverse event is even rarer. Australian monitoring systems have reported a rate of 14 per 1 million vaccines (104 cases, 6 died) from AstraZeneca.

However, it is crucial to understand that this disease is not unique to the vaccine. The American Heart Association/American Stroke Association Stroke Council Leadership published a report in the journal Stroke, showing that the risk of developing CVST blood clots is 8 to 10 times higher following a COVID-19 infection compared to the risk associated with receipt of a COVID-19 vaccine.

Anaphylaxis

Rate from NON-COVID-19 VACCINES: 1.3 cases per 1 million vaccines
Rate from COVID-19 VACCINES:
- CDC: 2-5 cases per 1 million vaccines
- Canada: 3 cases per 1 million vaccines

Severe allergic reactions, including anaphylaxis, can occur after any vaccination. Prior to COVID-19, the general rate of anaphylaxis following any vaccine was about 1.3 cases per 1 million vaccines. The current estimated rate of anaphylaxis from the COVID-19 vaccines is 2 to 5 cases per 1 million vaccines.

Guillain-Barré Syndrome

General background rate: 10-20 cases per million people per year
Rate from COVID-19 INFECTION: 150 cases per 1 million infections
Rate from COVID-19 VACCINES:
- CDC: 1.2 cases per 1 million vaccines (mRNA) and 8 cases per 1 million J&J vaccines
- Australia: 10 cases per 1 million AstraZeneca vaccines (suspected, not confirmed)
- Canada: 1.1 cases per 1 million vaccines

GBS is a rare disorder where the body’s immune system damages nerve cells, causing muscle weakness and sometimes paralysis. While most people fully recover from GBS, some can have permanent nerve damage. As of August 11th, there have been 161 cases of GBS entered into the VAERS reporting system. These are still being investigated to see if there is a causal link to the vaccine. The only vaccine in which this was reported is the Johnson & Johnson vaccine. These cases are primarily in men over the age of 50.

The estimated incidence of GBS cases following an mRNA vaccine was 1.2 per 1 million vaccines, and following the Johnson & Johnson vaccine was 8 per 1 million vaccines.

The incidence of GBS in the general population is 10-20 cases per million people per year. With 161 cases reported following the 13,784,136 J&J vaccines delivered, would put an estimated incidence of 11 cases per 1 million vaccines. For reference, the influenza vaccine causes an extra 1-2 cases per 1 million vaccines given. Again, an actual causal link to COVID-19 vaccines causing GBS is still being investigated. As with other adverse events, GBS also occurs at a higher rate from infection with SARS-CoV-2 than it does from vaccination, with an incidence of 150 cases per 1 million infections.

Myocarditis/Pericarditis

General background rate: 100-200 cases per million people per year in all age groups. 8 cases per 1 million children per year. 18 cases per 1 million adolescents between the ages of 15-18.
Rate from COVID-19 INFECTION: 450 cases per 1 million infections
Rate from COVID-19 VACCINES:
- CDC: 4.8 cases per 1 million vaccines
- Canada: 8 cases per 1 million vaccines
- Europe: 1.4 cases per 1 million vaccines

As of August 11, 2021, VAERS has received 1,306 reports of myocarditis or pericarditis. The CDC and FDA have confirmed 762 of these cases after more than 300 million doses. Most cases have been reported after mRNA COVID-19 vaccination (Pfizer-BioNTech or Moderna), particularly in male adolescents and young adults. The highest incidence was in males between the ages of 16 and 19 years—the average onset of symptoms around 3.5 days following administration of the vaccine.

The CDC estimates the incidence of myocarditis/pericarditis following vaccines to 4.8 cases per 1 million vaccines. In an independent review of 2 million patients vaccinated across 40 hospital systems in the US, the incidence of myocarditis was found to be higher than the CDC estimate. Researchers determined the true incidence to be closer to 10 cases per 1 million vaccines for myocarditis and 18 cases per 1 million vaccines for pericarditis. This suggests the actual incidence is likely under-reported. Again, myocarditis and pericarditis occur at a much higher rate from COVID-19 infection than from the vaccine, occurring in 450 people per 1 million infections.

The overall incidence of myocarditis/pericarditis is higher than would be expected in the general population, suggesting it is likely a true adverse event occurring from vaccination. A risk-benefit analysis for COVID-19 vaccination and risk of myocarditis/pericarditis was done by the CDC and the benefits of vaccination (prevention of COVID-19 disease and associated hospitalizations, ICU admissions, and deaths) outweighed the risks in all populations for which vaccination has been recommended.

The balance of benefits and risks varied by age and sex because cases of myocarditis were primarily identified among males aged <30 years, and the risks of poor outcomes related to COVID-19 increase with age. Per million second doses of mRNA, COVID-19 vaccine administered to males aged 12–29 years, 11,000 COVID-19 cases, 560 hospitalizations, 138 ICU admissions, and six deaths due to COVID-19 could be prevented, compared with 39–47 expected myocarditis cases after COVID-19 vaccination.

Among males aged ≥30 years, 15,300 COVID-19 cases, 4,598 hospitalizations, 1,242 ICU admissions, and 700 deaths could be prevented, compared with three to four expected myocarditis cases after COVID-19 vaccination. This analysis did not include the potential benefit of preventing post-COVID-19 conditions, such as prolonged symptoms and MIS-C.

In a June analysis of 323 patients with myocarditis following COVID-19 vaccination, 309 (96%) were hospitalized. Acute clinical courses were generally mild; among 304 hospitalized patients with known clinical outcomes, 95% had been discharged at the time of review, and none had died. Most patients experienced resolution of symptoms with conservative treatment, such as receipt of nonsteroidal anti-inflammatory drugs.

Death

There have been no definitive numbers as to the number of people who have died due to the vaccine. As of August 16th, VAERS has a total of 6,789 reports of deaths following vaccination for a rate of 0.0019%. Remember, this comes with the massive caveat that these cases have not been reviewed to establish a causal link to COVID-19 vaccines. Remember, anyone can make a report in this system. So, it is highly improbable that all of these reported deaths will ultimately be linked to the vaccine.

For the sake of argument, let’s say that you don’t trust the CDC and you think they are hiding vaccine-related deaths. We do have data from other countries that can offer some insight. Let’s look at Canada. As of August 6th, a total of 50,254,577 COVID-19 vaccine doses had been administered. There was a total of 169 deaths reported following vaccines. Of these, only six deaths following a diagnosis of TTS were confirmed to be related to the vaccine. Sixty-nine reported deaths were felt unlikely linked to the vaccine, and 94 are either still under investigation or has insufficient information to determine a causal link.

International Vaccine Safety Reporting Systems

How do these risks compare to the risks from COVID-19 infection?

We certainly can’t get any straight data from the CDC at this time about most definitive risks. However, Canada is a reasonable population to poll as they offer a breakdown of specific reports suspected to be from vaccine administration. A total of 50,254,577 vaccine doses have been administered in Canada. The following chart uses risks compiled from the ECDC, the Government of Canada, and the Australian Department of Health compared to peer-reviewed publications of disease incidence associated with acute COVID-19 infections. While it is highly probable that the incidence of these diseases may be underestimated in vaccine reporting systems, this gives a summary of data that is CURRENTLY available. The following table is a summary of the current risk per 100,000 people between the vaccines and COVID-19.

ECDC¹, Canada², Australia³, Palaiodimous, 2021⁴, Katsoularis, et al. 2021⁵, Singer, 2021⁶, Miro, et al. 2021⁷, Furie, et al. 2021⁸, Chang, 2021⁹

COVID-19 infection has other risks

The age-adjusted death rate in the United States increased by 22.9% in 2020, compared to 2019. Based on population growth, the yearly expected excess death rate increase is typically no greater than 2.5% per year. COVID-19 was a contributing cause in 377,883 deaths in 2020 (91.5 per 100,000 people or 11% of deaths). Throughout most of 2020, COVID-19 was the 3rd leading cause of death in the United States, rising to the #1 spot in January before falling to 7th place in June. In the united states, 188 per 100,000 people have already died from COVID-19 (0.18% of the population).

Source: CDC

"Not Dead" doesn't mean "Recovered"

The chances of dying if you catch Covid-19 vary significantly according to your age and overall health, with older people and those with underlying conditions facing a much higher risk. Different countries are likely to have different death rates, depending partly on the age and health of their populations, the quality of their healthcare, and other factors that we may not yet understand. Even if your age group is at low risk of dying from COVID-19, this doesn’t mean this is the number of people who will recover without complication or long-term issues.

Multisystem Inflammatory Syndrome in Children (MIS-C)

Severe hyperinflammatory syndrome occurring 2–6 weeks after acute SARS-CoV-2 infection among persons < 21 years old. The majority of cases occur between the ages of 12 and 20 years. It results in a wide range of manifestations, including myocarditis. Estimates of myocarditis in patients with MIS-C have ranged from 23% to 60%, though a more significant proportion (80% in one study) do have some form of cardiac involvement. Even without myocarditis, MIS-C is a severe illness. 60-70% of cases require hospitalization, and 1-2% will die. It has an estimated occurrence is 1 in every 3,200 children infected with SARS-CoV-2.

Long COVID Syndrome

COVID-19 can involve persistence, sequelae, and other medical complications that last weeks to months after initial recovery. A systematic review and meta-analysis (remember, these are the highest quality evidence) of 18,251 publications were published on August 9th, assessing the long-term effects of COVID-19. In this study, they found a total of 55 long-term effects associated with a SARS-CoV-2 infection. The prevalence of residual symptoms is about 35% in patients treated for COVID-19 outpatient, but around 87% among cohorts of hospitalized patients.

In the first study of long covid in children suggests that more than 50% of children aged between 6 and 16 years old who contract the virus have at least one symptom lasting more than 120 days, with 42.6% impaired by these symptoms during daily activities.

Source: Lopez-Leon, et al.

Conclusion

Overall, the decision to vaccinate (especially in younger age groups) should consider the individual benefit-risk ratio and take into account the public health benefits of vaccination. As for adults, the children who will benefit most from vaccination will be those with underlying conditions, such as cancer, cardiac disorder, diabetes, hypertension, or kidney disease, which have been shown to confer a risk of hospitalization that is similar to the risk in some adult age groups without underlying conditions.

Vaccinating children and adolescents will also prevent long-term sequelae associated with SARS-CoV-2 infection, for which the burden in children is uncertain, and multisystem inflammatory syndrome, which has been shown to affect some children who have experienced only mild acute infections.

Tocilizumab for COVID-19

Nicholas McManus — Sun, 14 Mar 2021 19:21:15 +0000

REMAP-CAP and RECOVERY trials...a little background...

So, the REMAP-CAP study published on January 9th set out to determine if the IL-6 receptor antagonists, tocilizumab and Sarilumab, compared with standard care, improve respiratory and cardiovascular organ support free days up to day 21 in critically ill patients with COVID-19. The critically ill patient is the emphasis here as the first 5 studies looking at Tocilizumab were fairly negative studies and for the most part (with the exception of the EMPACTA trial), excluded anyone on High Flow Nasal Cannula (HFNC) or higher support. Results of this study were published January 9th.

The RECOVERY trial, which was published February 11th set out to determine if Tocilizumab decreased 28-day mortality when compared to usual care.

Let’s highlight a couple of important features about these studies to set the stage. The REMAP-CAP trial initially started in 2016 to evaluate various interventions in patients with community acquired pneumonia. It branched out in early 2020 to target patients with COVID-19. Therefore, the newly named REMAP-COVID group is really a group of trials with different domains within the larger REMAP-CAP trial. Each domain also has several arms, which can get quite difficult to keep track of.

Current ongoing study domains include….

This is important to point out as patients were allowed to be enrolled in multiple domains at once. Further, the REMAP-CAP/REMAP-COVID trial also coordinates patients with the RECOVERY trial, which also includes several domains (i.e. azithromycin, tocolizumab, convalescent plasma, monoclonal antibodies and aspirin). A statement on the coordinated effort of these two trials can be found here.

The focus of this discussion is pertinent to the immunomodulation domain in these trials. In the REMAP-CAP study, this included 5 interventions (see table below), but Tocilizumab and usual care overwhelmingly had the vast majority of patients. So, this study is really a study on Tocilizumab vs usual care only. Similarly, the immunomoduation domain of the RECOVERY trial only looked at Tocilizumab vs standard care.

The Tocilizumab arm of the REMAP-CAP trial started April 19, 2020 and the Tocilizumab arm of the RECOVERY trial started April 23, 2020. This timing is important, as they both compared Tocilizumab to usual care, and the definition of “usual care” changed frequently throughout the summer. While Tocilizumab patients were able to be enrolled concurrently in the steroid domain as well, usual care at the time these studies started enrolling did not necessarily include steroids and in-hospital mortality was much higher than it was when these studies concluded (Nov 19thfor the REMAP-CAP study and Jan 24th for the RECOVERY trail). The steroid domain of the REMAP-CAP trial stopped enrolling June 17^th following preliminary results of the steroid domain of the RECOVERY trial showing benefit from steroids and steroids were considered usual care in all arms from that point on.

In the REMAP-CAP trial, there were 399 patients in the Tocilizumab group and 412 in the usual care group at study completion. 158 patients were recruited before steroids were considered usual care and 107 of them were also included in the steroid domain of the REMAP-CAP trial. 707 patients were randomized after June 17th. In total, 93% of all patients in this study were also treated with steroids within 48 hours of enrollment with 88% of patients in the Tocilizumab group receiving steroids.

For the RECOVERY trial, 82% of patients enrolled in the Tocilizumab group were also treated with steroids before June 17th and this increased to 97% of patients after steroids became usual care. Keep these number in mind when I review the other studies on Tocilizumab later on.

So what role does IL-6 really play?

I really had high hopes early last year when people started to theorize that IL-6 was a key player in the cytokine storm phenomenon. However, I don’t know if the data in favor of IL-6 as the only player is as robust as people think.

A systematic review and meta-analysis of cytokine elevation was published in the Lancet on Dec 8^th. They essentially reviewed different cytokine concentrations in COVID compared to other non-COVID inflammatory conditions including non-severe COVID, severe COVID, critical COVID, hypo and hyper-inflammatory ARDS, Sepsis in general and cytokine release syndrome (which was described in literature years before COVID was a thing). The bottom line is, while IL-6 levels are elevated in COVID, they aren’t the only cytokine on the playing field and IL-6 levels are actually much higher in non-COVID related illnesses as well and these results question the role of a cytokine storm in COVID-19 induced organ dysfunction.

Following results of the RECOVERY trial steroid arm and the WHO meta-analysis, steroids have been the only medication shown to improve mortality. The way in which steroids were included in previous trials of Tocilizumab is significantly different and likely significant, as well as the population of patients that were included.

Let’s quickly review the available studies assessing Tocilizumab and how they vary in regards to steroid usage and respiratory support…

Final points to highlight...

The REMAP-CAP trial is a trial within a trial within a trial. Patients were not only also allowed to be enrolled in any domain of the REMAP-CAP trial, they could potentially be included in pre-ICU arms of the RECOVERY trial and be subsequently included in the REMAP-CAP trial if they require transfer to the ICU. I can’t find a break-down of the concentration of any of these patients in other trial arms.

Tocilizumab appears to generally be very safe suggesting little downside to giving it from this standpoint. So far, no studies have shown a significant increase in harm with the drug. There were 3 serious adverse events reported in the RECOVERY trial, all of which were successfully treated with standard therapy. Up to 15% of patients will get neutropenic, but this wasn’t associated with a higher rate of infection. If anything, those in the Tocilizumab group had fewer subsequent bacterial infections than those that weren’t, even in those that became neutropenic.

Cost and supply may be an issue. I am not entirely certain of the cost. My google search suggests an 800 mg dose could cost upwards of $5,000 for the brand name Actemra injectable solution. Further, Tocilizumab is certainly not available to all hospital systems. Supply was an issue even in the REMAP-CAP trial, which is why they started using Sarilumab. These issues are likely to limit Tocilizumab as a standard treatment option for most patients.

Timing when to use Tocilizumab is still not entirely certain, in my opinion. These studies (with the exception of the COVACTA trial) mainly focused on patients early in the disease process, before requiring more than nasal cannula and did not show benefit in these groups. However, the RECOVERY trial showed no significant difference in patients who received Tocilizumab < 2 days or > 2 days of hospitalization which contradicts earlier studies.

There does not seem to be any robust evidence that Tocilizumab has any benefit in patients outside of the ICU. This is interesting because in the theory of IL-6 induced cytokine storm, you would think blocking this cascade before it occurs would offer the best outcome, and that doesn’t seem to be the case. The REMAP-CAP trial excluded patients in the ICU for > 24 hours, so we can’t really conclude that the timing of administration of the drug is what leads to favorable outcomes. However, both the CONVACTA trial and now the RECOVERY trial, has shown a decrease in requiring mechanical ventilation. It is important to note that patients included in the RECOVERY trial had very high CRP levels, suggesting that perhaps this may be a better target for identifying patients who may benefit outside of the ICU.

Only 1 study (RCT-TCZ-COVID-19) measured and reported measured IL-6 levels, which were higher in the Tocilizumab cohort of that study which still doesn’t answer the question if IL-6 levels are really the cause of clinical severity. Perhaps steroids (which block multiple inflammatory processes) combined with IL-6 specific inhibition is more beneficial. The RECOVERY trial only included hypoxemic patients with a CRP > 75 mg/L. The data from both this trial and the REMAP-CAP trial suggest the greatest benefit is seen as CRP levels increase.

The REMAP-CAP Tocilizumab arm (published January 9th) and the REMAP-CAP steroid arm (published September 2nd) used the same study design. While no statistical triggers were reached in the steroid arm of this study, using the Bayesian approach, the authors suggest a high probability (80-93%) of superiority of corticosteroid use (compared to no steroids) in organ support free days within 21 days and an increased probability of lower mortality (54-62%). Given the endpoints and study design are identical, it would be nice to see some sort of subgroup analysis between the 2 studies to see how much of a factor steroids really play. One thing that has been consistent between all studies is that patients do not benefit from Tocilizumab alone. The benefit is only seen when combined with steroid therapy.

IDSA Guidelines (last updated 2/17/2021)

“Among hospitalized adults with progressive severe* or critical** COVID-19 who have elevated markers of systemic inflammation, the IDSA guideline panel suggests tocilizumab in addition to standard of care (i.e., steroids) rather than standard of care alone. (Conditional recommendation, Low certainty of evidence)”

Remarks:

- “Patients, particularly those who respond to steroids alone, who put a high value on avoiding possible adverse events of tocilizumab and a low value on the uncertain mortality reduction, would reasonably decline tocilizumab.”
- “In the largest trial on the treatment of tocilizumab, criterion for systemic inflammation was defined as CRP ≥75 mg/L.”

Severity definitions:

*Severe illness is defined as patients with SpO₂ ≤94% on room air, including patients on supplemental oxygen

**Critical illness is defined as patients on mechanical ventilation and ECMO. Critical illness includes end organ dysfunction as is seen in sepsis/septic shock. In COVID-19, the most commonly reported form of end organ dysfunction is ARDS.

You can view the full discussion of IDSA recommendations for all treatments in COVID-19 here.

Choosing a Research Project Design

Nicholas McManus — Thu, 25 Feb 2021 05:46:24 +0000

Deciding on the type of research design that is best suited to answer your research question can get a bit confusing. This article aims to summarize the basic understanding of the general research design methodologies as well as the type of answers each design can provide.

Ultimately, the question you want to answer will likely dictate the design of your overall project. However, understanding what the research methodology is able to answer is paramount to a well designed project. For example, if your clinical question is simply to determine the prevalence of a disease, then a cross-sectional study is probably what you want to be designing. If it is the incidence you are after, then a cohort study will give you that answer. Having a fundamental understanding of the different design options and the types of questions they can answer will serve you well early in the design process.

One way to look at the different types of clinical trials is those that are observational versus those that are interventional. Observational studies allow researchers to observe the effects of various risk factors, diagnostic tests and treatments without influencing who is or is not exposed to it. Specifically, with observational studies, researchers do not intervene, they just observe study subjects. Conversely, Interventional studies as the name would suggest, allow researchers to introduce an intervention and study the effects of that intervention. The hierarchy of clinical trials is outlined in the figure below. Understanding that each study design has its own purpose will help understand the global picture. Stick with me…

Observational (non-experimental) Studies

Observational studies can be prospective (forward-looking) or retrospective (backward-looking), depending on the specific design. However, you can’t exactly just make up what you want to do. For example, cohort studies can be designed prospective or retrospectively, while case control studies are typically just retrospective. A summary is outlined in the figure below.

Prospective studies: observe a group of people, or compare different groups (cohorts) over time, These studies look for relationships between lifestyle factors or environmental exposures and the development of conditions or diseases.

Retrospective studies: rely on study subjects who have already been diagnosed with a condition or disease, as well as a comparison group of subjects who do not have the condition or disease, called controls. Cases and controls are then asked about past exposures to observe any associations between exposure and disease.

Observational studies by design are typically quicker, cheaper and easier to conduct than interventional studies. Not to mention, significantly easier to get IRB approval. If you have the opportunity to design and implement an interventional study, go for it! However, unless you are working with a team or researchers or residents, this may serve quite difficult to accomplish alone during the course of your residency. In the figure above, I outlined the hierarchy of clinical trials in order of their quality of information.

Don’t get overwhelmed by the information in this article. The overall goal is to generate a baseline understanding of the different research methods, and to serve as a point of reference to point you in the right direction when you begin designing your project.

Let’s take a look at the different designs of observation studies…

Case Reports

Case reports are a description of clinical events of one or several patients in a narrative form. They are a low-hanging fruit for residents looking for a project as they can be written rather quickly. Case reports typically involve a literature search to gain understanding of current knowledge on the topic and this is reviewed in the form of discussion in the published case report and expanded on using the patient case as en example. The key here is the case can’t simply be rare. Case reports aren’t exactly easy to get published, because the market is flooded with them.

Finding cases that provide the reader with a unique clinical case that offers awareness and expanded knowledge will have the highest likelihood of getting published. If you are presented with a unique case that will add to medical literature, I highly recommend writing up a case report. Just don’t spend your entire residency waiting for the opportunity to present itself.

Published examples:

- Laryngeal tuberculosis diagnosed by stool sample cultures: a case report
- Acute pancreatitis following medical abortion: Case report

Further readings:

Tips for writing a case report for the novice author

Case Series

There are several definitions of a case series. According to the Dictionary of Epidemiology, a case series is defined as “a collection of patients with common characteristics used to describe some clinical, pathophysiological or operational aspects of a disease, treatment or diagnostic procedures.” This can be retrospective or prospective and may be consecutive or nonconsecutive depending on whether all cases presenting to the reporting authors over a period were included, or only a selection.

While a case report is a description of clinical events of one or several patients, a case series will contain individual patient’s data like demography, diagnosis and management. This data can be presented as a table and pooled together if needed without the need for individual detailed description. There is no agreed upon definition for the minimum or maximum number of patients required to define a case series. Some authors suggest case series should contain no less than four patients, and no more than ten, but there does not appear to be a consensus definition.

Published examples:

Further readings:

Cross-Sectional Studies

A research design in which you collect data from many different individuals at a single point in time. There is no follow-up period, nor an assessment of the subject’s history. In cross-sectional research, you observe variables without influencing them. Such studies provide a snapshot of activity but often cannot determine which came first: the exposure or the disease.

Cross-sectional studies can he descriptive (describes) or analytical (explains). A cross-sectional descriptive survey assesses how frequently, widely, or severely the variable of interest occurs throughout a specific demographic (i.e. to assess the burden of a particular disease). Analytical design is used to investigate the association between a putative risk factor and a health outcome. In this design, investigators survey the risk factors and outcomes simultaneously. Again, you cannot determine which came first with this type of study. In practice, your study design might include descriptive or analytical components, or both.

Outcomes measured:

- Prevalence (fraction of a group of people possessing a clinical condition at a given point in time)
- Odds ratios

Potential Bias:

- Selection bias (sampling, response and non-response bias)
- Information bias (recall and detection bias)
- Confounding

Strengths/Weaknesses:

Cross sectional studies are relatively quick and easy to conduct since all the variables are collected at one point in time. Further, multiple outcomes and exposures can be studies rather rapidly.

These studies are useful at measuring prevalence, but cannot tell whether or not the outcome followed the exposure or in what time it occurred (cannot tell you incidence). Because it is an observational study, it is highly susceptible to bias. Because of this, cross-sectional studies are good for descriptive analysis and for generating hypotheses, but unlikely to give the level of evidence needed to change clinical guidelines.

Published examples:

- Antibiotic resistance in Propionibacterium acnes strains
- Cross-sectional study of prevalence of dementia, behavioral symptoms, mobility, pain and other health parameters in nursing homes

Protocol examples:

- A cross-sectional survey of seasonal affective disorder in populations with and without severe visual impairments
- Study Protocol of a Cross-Sectional Study to Assess the Oral Health of and Oral Health Care for Older People Who Regularly Visit the Dental Practice

Further readings:

Case Control Study

Case control studies look at groups of people. More specifically, it compares two groups: those with a disease or condition of interest (cases) and those who are similar in age and other demographic characteristics who do not have the condition or disease (controls). Researchers then compare the frequency of exposure prior to the disease diagnosis to one or more risk factors in both groups to help determine whether there’s a link between the past exposure and the development of the disease or condition being studied.

The study starts with an outcome, then traces back to investigate exposures and is therefore, by definition, always retrospective. When the subjects are enrolled in their respective groups, the outcome of each subject is already known by the investigator. This, and not the fact that the investigator usually makes use of previously collected data, is what makes case-control studies ‘retrospective’. Controls should be chosen who are similar to the cases. These factors (i.e., age, sex, time of exposure) are known as the “matching criteria.” This article and this article does a great job discussing the selection process and matching strategies.

Statistical Outcomes:

- Odds ratios (always include a confidence interval when calculating an odds ratio. This is usually done with computer programs such as Epi-info).
- CANNOT tell you anything about incidence or prevalence of a disease

4-steps to conducting a case-control:

Enroll patients who already have a disease or outcome
A second control group without the disease or outcome is sampled (should be of similar size and as identical in every other way)
Subjects are asked about exposures/risk factors
Calculate an Odds ratio

Potential Bias:

- Recall bias (patients with the outcome are likely to scrutinize the past, remembering negative details more clearly)
- Sampling bias (i.e. enrolling only patients who present to the hospital may not represent the community as a whole)
- Confounding (a variable which is associated with the exposure and is a cause of the outcome, which can be mitigated by matching controls to cases)

Strengths/Weaknesses:

Case-control studies are relatively quick with minimal funding needed. Unlike cross-sectional studies, they can be used for rare diseases (unlike cross-sectional studies) as smaller sample sizes are needed. Further, they can study multiple exposures. However, case-control studies, as with all other observational studies, are subject to bias. Further, case-control studies (like cross-sectional studies) cannot tell you the incidence of a disease.

Published examples:

- Tobacco use and risk of myocardial infarction in 52 countries in the INTERHEART study
- Autoimmune and chronic inflammatory disorders and risk of non-Hodgkin lymphoma by subtype

Protocol examples:

- Pertussis vaccination and the risk of respiratory syncytial virus associated hospitalization
- Multicenter case-control study protocol of pneumonia etiology in children

Further readings:

Cohort Study

A cohort is a group of people with defined characteristics who are followed up to determine incidence of, or mortality from, some specific disease, all causes of death, or some other outcome. A cohort study can be retrospective (identifying diseased subjects by interview or written records) or prospective (identifying diseased subjects during a follow-up period).

Prospective cohort studies are designed with specific data collection methods and considered more complete. However, they can cost a lot of money and with a long follow-up period waiting for disease to occur, there is a high risk of losing subjects to follow-up. Loss to follow-up should not exceed 20% of the sample. This article does a great job discussing the selection process and methods to minimize loss to follow-up.

A retrospective (or historical) cohort study is advantageous in that it can be done at a low cost and in a relatively reasonable amount of time. This may be of particular importance to the resident who has 3-4 years to complete a project.

Subject Selection:

Selection of subjects is important, particularly in a cohort study. Subjects who are not at risk of developing an outcome should not be included in the study. The source population is determined by practical considerations, such as sampling. Subjects may be effectively sampled from the hospital, be members of a community, or from a doctor’s individual practice. A subset of these subjects will be eligible for the study. For in depth information about sample selection techniques, check out this article.

General steps of design:

1. Identify exposed and unexposed cohort groups
2. Prospective study: during follow-up period, identify diseased subjects (incidence of cases)
3. Retrospective study: identify diseased subjects by interview or written records
4. Analyze the differences (i.e., the incidence or relative risk) among those exposed (cohort 1) and those unexposed (cohort 2)

Outcomes measured:

- Incidence
- Mortality rate
- Case-fatality
- Odds Ratio (OR)
- Hazard Ratio (HR)
- Prevalence
- Relative Risk (RR)
- Risk Difference (RD)
- Standardized incidence ratio (SIR)
- Standardized Mortality Ratio (SMR)

Potential Bias:

- Attrition bias (prospective only)
- Selection bias (retrospective and prospective)
- Recall bias (retrospective only)
- Information bias (retrospective only)

Strengths:

Cohort studies can assess causality as information is gathered regarding a sequence of events. Further, they can examine multiple outcomes for a given exposure and can can determine rates of disease over time (i.e., incidence, relative risk). However, large number of subjects are needed for studying rare exposures. Like other observational trials, cohort studies are subject to bias. Prospective studies may be expensive and require long follow-up and susceptible to loss to follow-up. Retrospective studies are quick and cheaper, but susceptible to recall bias or information bias and there is less control over variables.

Published examples:

- Framingham Heart Study
- A longitudinal cohort study on quality of life in stroke patients and their partners: Restore4Stroke Cohort

Protocol examples:

- Study protocol for a multicentre prospective cohort study to identify predictors of adverse outcome in older medical emergency department patients
- Study protocol for a prospective, longitudinal cohort study investigating the medical and psychosocial outcomes of UK combat casualties from the Afghanistan war: the ADVANCE Study

Further readings:

Meta-analysis

A meta-analysis is a statistical procedure for combining numerical data from multiple separate studies. A meta-analysis cannot be done without also doing a systematic review of the literature. Therefore, this section will contain information that is pertinent to both. Where a systematic review summarizes available literature followed by a critical appraisal, a meta-analysis refers to the statistical analysis of the data from independent primary studies focused on the same question.

Depending on the purpose of a review, reviewers may choose to undertake a rapid or systematic review. While the meta-analytic methodology is similar for systematic and rapid reviews, the scope of literature assessed tends to be significantly narrower for rapid reviews permitting the project to proceed faster.

The stages in conducting a meta-analysis are:

Formulate a research question: define primary and secondary objectives.
Identify relevant literature: construct a search strategy (rapid or systematic), screen studies and determine eligibility.
Extract and consolidate study-level data:collect relevant study-level characteristics and experimental covarities and evaluate the quality of the studies.
Data appraisal and preparation: compute appropriate outcome measure and evaluate the extent of between-study inconsistency (heterogeneity), perform relevant data transformations and select a meta-analytic model.
Synthesize study-level data into summary measure: pool data and calculate summary measure and confidence intervals.
Exploratory analyses: explore potential sources of heterogeneity (biological or experimental) and perform subgroup and meta-regression analyses.
Knowledge synthesis: interpret findings and provide recommendations for future work.

Transparency and clarity in reporting can an issue for these studies. Reviews from organizations such as Campbell and Cochrane are particularly reliable, as all authors are required to adhere to the same standards of conduct and reporting. Lets briefly discuss these standards…

PRISMA (Preferred Reporting Items for Systematic reviews and Meta-Analyses)

In 2009 an international group of experienced authors and methodologists developed PRISMA, which is a 27-item checklist and a four-phase flow diagram (see figures below) that outlines items deemed essential for transparent reporting of a systematic review and meta-analysis. Most reputable journals will require a protocol that includes this formal process for publication.

MECIR (Methodological Expectations of Cochrane Intervention Reviews)

The MECIR is a methodological standard to which all Cochrane Protocols, Review and Updates are expected to adhere to. They provide authors and users of the Cochrane Library with clear and transparent expectations of review conduct and reporting.

The MECIR Standards are divided into four sections:

Standards for the conduct of new Cochrane Intervention Reviews (C1-C75).
Standards for reporting of protocols of new Cochrane Intervention Reviews (PR1-PR44).
Standards for reporting of new Cochrane Intervention Reviews (R1-R109).
Standards for planning, conducting and reporting of updates of Cochrane Intervention Reviews (U1-U11, UR1-UR7).

Protocol Examples:

Systematic Review

A systematic review is a detailed, systematic and transparent means of gathering, appraising and synthesizing evidence to answer a well-defined questions and summarizes available literature followed by a critical appraisal. It involves comprehensive search strategies that enable reviewers to identify ALL relevant studies of a topic. While it may end with a meta-analysis, it certainly does not have to. The goal of being systematic is to reduce bias by keeping a standardized approach to the review process. Following the appropriate reporting guidelines (PRISMA) and standards (MECIR) is recommended for all Systematic Review and Meta-analyses, as discussed in the previous section.

Comprehensive Review:

To comprehensively search the seemingly never-ending pool of available literature, search criteria must be sensitive enough not to miss any relevant studies. Using Boolean operators AND, OR and NOT should be used to combine keywords and index terms when searching for literature. A true comprehensive review can take up to 2 years to complete and will select a large amount of studies, most not relevant to the topic, yielding a specificity of < 10%. To minimize selection bias, it is recommended to have at least two independent reviewers.

Rapid Review:

The overall goal of a rapid review is to decrease the time needed to gather literature sources. Common shortcuts include narrowing search criteria, imposing date restrictions, using a single reviewer, omitting articles not in English, limiting database searches, etc. It is important to note that rapid reviews have not shown to sacrifice quality compared to comprehensive reviews.

Screening and Selection:

Inclusion and exclusion criteria must be defined before study screening can occur to ensure consistency. The entire screening and selection process should be reported in a PRISMA diagram.

Components of screening and selection include:

- Removing duplicates
- Screening for relevant studies by title and abstract
- Inspecting full texts to ensure they meet infusion and exclusion criteria

Free software tools that can assist with preparing reviews:

Protocol Examples:

- Systematic review to evaluate the evidence for an association between Bisphenol A (BPA) exposure and obesity
- A systematic review protocol examining the effects of vitamin D on endothelial function

Further readings:

Interventional (experimental) Studies

Interventional studies can be uncontrolled or controlled depending on whether or not they have control groups. Controlled studies can be further subcategorized as randomized (cohort allocation is based on random chance) on non-randomized (patients intentionally placed in different treatment arms).

Clinical trials can also be classified by their purpose:

- Prevention trials: assess ways to prevent diseases using medicine, vaccines, lifestyle changes, etc.
- Screening trials: assess the best way to detect diseases or health conditions
- Diagnostic trials: aim to improve methods to diagnose a disease or condition
- Treatment trials: tests new treatments, novel combinations of treatments or new approaches to surgeries or therapy
- Quality-of-life trials: attempts to find ways to improve the life for people living with diseases or health conditions

Clinical trials can have some extra flair as well:

Cross-Over: when participants receive both treatment and placebo over time
Double-blinded: when neither the participant nor the researcher know if the participant is receiving treatment or placebo
Open label studies: when both the participant and the researcher know the participant is receiving treatment and not placebo

Interventional trial can be conducted incrementally, in phases:

- Phase 1 trials: first-in-human studies conducted in small groups of people to evaluate a new drug, test or procedure. This can include determining the safe dosage of a drug, the most effective way to administer it and identifying any serious side effects. Uncontrolled trials are often conducted in the early phases of interventional trials
- Phase 2 trials: involve slightly larger groups of participants to test efficacy and further test safety.
- Phase 3 trials: involve a large study population and provide a complete picture of safety and efficacy and to determine if the drug, test or procedure is as good as the current standard of care for a disease or condition. This phrase is typically designed as randomized, controlled trials.
- Phase 4 trials: are conducted in large populations after a drug, test or procedure has been introduced on the market to further monitor safety and potential long-term adverse outcomes. Since this phase occurs after an intervention reaches the market, this phase may be done as observational, long-term cohort studies.

Uncontrolled Trials

A control group is made up of a group of patients that do not receive the investigational drug, but instead take the standard treatment, approved for the disease on which the study is being carried out, or takes a placebo, which is a simulation of the investigational drug. An uncontrolled trial is rightfully named because it contains NO control group.

Uncontrolled trials are often used in the early phases of drug research (phases I and II) to determine pharmacokinetic properties or to investigate tolerated dose ranges. They can also be useful to study side effects, biochemical changes in long-term therapies, tolerance, interactions or efficacy of drugs.

As they can generate bias, the results of uncontrolled trials are considered less valid than those of controlled trials. The results obtained are usually compared with those obtained in previous studies or that have been published by other researchers.

Non-randomized Controlled Trial

Non-randomized trials use controls, but the study participants are not randomly assigned into each study arm (treatment group vs control group).

Controls commonly used:

- Placebo control
- “No treatment” control
- Active treatment control (i.e. comparing a new drug to a standard drug or to standard care)
- Control with dose comparison
- Historical control (information from controls are from patients treated at an earlier time or in a different setting)

Randomized Controlled Trial

A Randomized Controlled Trial (RCT) is generally used in experiments testing the effectiveness and/or safety of one or more interventions. Subjects are randomly assigned participants into an experimental group or a control group. As the study is conducted, the only expected difference between the control and experimental groups is the outcome variable being studied.

RCTs are suitable both for preclinical and clinical research. There should be sufficient uncertainty about the utility of an intervention. This is referred to as equipoise. RCTs are not suitable for investigating etiology or natural history of disease.

Observational studies are prone to bias. Bias is the tendency of any factors associated with the design, implementation, evaluation and interpretation of the results of a study to make the estimate of the effect of a treatment or intervention deviate from its true value. If two or more groups are being compared in an observational study, there are often systematic differences between the groups, so much so that the outcome of the groups may be different because of these differences rather than actual exposure or intervention. This is known as confounding. Randomization is the best way to minimize confounding by increasing the probability that the observed outcome is likely to be due to the intervention rather than other factors.

Outcomes measured:

The outcomes assessed in interventional trials are pre-specified primary and secondary outcomes that should be collected by independent observers who are blinded of the allocation and treatment arms of subjects. Patients with missing outcome data should be minimized as far as possible. A high rate of attrition will lead to reduced confidence in the results and may lead to biased estimates.

Potential Bias:

- Volunteer bias (the population that participated may not be representative of the whole)
- Susceptibility
- Performance
- Detection follow-up

Strengths/Weaknesses:

Good randomization will wash out any population bias. RCT’s are easier to blind/mask than observational studies. Results can be analyzed with well known statistical tools and populations of participating individuals are clearly identified. However, RCT’s can be expensive to conduct, can take a very long time to conduct and therefore patient loss to follow-up is a concern.

Example Protocols:

- Randomized, controlled trial to determine the efficacy of nutraceutical vs control for recurrent urinary tract infections
- A double blind randomized controlled trial to assess the effectiveness of Amitriptyline compared to placebo in management of moderate to severe HIV related peripheral

Further readings:

- A simplified guide to randomized controlled trials
- Methodology Series Module 4: Clinical Trials

The details of designing each individual methodology here exceeds the scope of what I am hoping to introduce here. Hopefully this article will give resident physicians and other junior researches a structured overview of the methodologies used in clinical research trials. Stay tuned for future articles in our introduction to clinical research series.

How to do a literature review

Joseph Betcher — Mon, 22 Feb 2021 21:30:34 +0000

So, you have a research idea and want to see what else is out there on the topic. You need to performa a literature review. This task can be rather daunting and confusing. Having a systematic and organized approach will set you up for success. The objective of this article is to familiarize you with a basic strategy in conducting and organizing a review of current literature in preparation for any research project.

There are many different types of literature reviews, and they vary in terms of comprehensiveness. A traditional literature review will be used to define a general scope of current knowledge about a topic and specific examples of articles will need to be cited for just about every statement you make in your published manuscript. A systematic review, on the other hand is significantly more involved. It requires development of a predefined protocol to minimize bias. The scope of this article is to understand the basics of a traditional literature review, but just know a systematic review is a very different beast. The building blocks you learn from this article can be applied to larger projects in the future.

Ok, let's begin...

If you are at an academic institution, and have a library login, use it! This will likely give you a larger pool of available literature to access without requiring you to purchase the individual articles. You certainly don’t need an institutional affiliation and login to search for literature, but many journals will want to charge you some of your hard earned money to actually read the articles if you don’t. I also recommend reaching out to your institutional librarian for assistance in obtaining access if you do not already have it.

Our residency is part of the Michigan State University Statewide Campus System, and for the benefit of our residents, I will spend a little time discussing navigation of the MSU library site. If this does not apply to you, feel free to skip ahead. There is still a lot of super useful info ahead!

Step 1: Find Pubmed on your institutional library page

The first thing to do is log onto MSU’s library site and type “pubmed” into the search bar. If you have an affiliate university, this step may be different, but the premise is the same.

You will see “Pubmed” show on the right hand side of the screen.

Next, you will need to sign in with your MSU NETID. If you do not have this yet, get ahold of the IT peeps at MSU and get set up with one.

Step 2: Search for words related to your topic

When you are in PubMed, at the top, you’ll see another search bar. Type in the key words of whatever you’re trying to find. For example, if I wanted to compare using Cardizem to metoprolol for atrial fibrillation, I just typed those key words into the search bar.

Choosing the keywords to search requires some thought. Some keywords may return a scope that is too broad. Adding multiple keywords can be helpful. By clicking the “Advanced” tab under the search bar, you can add further filters to your search. This may include the types of studies (i.e. cohort, randomized-controlled trials, etc.). Further, lets say you only want to include articles from the last 5 years. These filters can help refine your search process, and I recommend you play around with them a bit.

Hopefully you’ll get a couple hits of something relevant. If not, try to refine the search terms you used. Scroll through the articles that come up, and find which ones seem useful.

I clicked on the top article, and here you can quickly scan through the background, methods, results, and conclusion and see if it is relevant.

There are also a couple other useful things on this page. The Full Text green button will typically bring you to a link where you can download the pdf, and hopefully it will be free (fingers crossed).

Your institution may have a link to a free version of the article as well. Above you will see the “Find Text @ MSU” white button, which may offer some access options as well. Also, one of the most useful parts of this is the related articles on the right side of the screen. One useful article will often lead to another, it can be quite the snowball effect. When I am searching for literature, I grab every possible article that is even remotely related and filter out the ones I don’t need later.

The green button link will bring you to various pages like this, which will allow you to download the pdf. If you encounter one that is difficult to download, contact your institutional librarian and see if they can assist you in locating the pdf. They most always can.

Step 3: Search other platforms

Believe it or not, Pubmed is not the only scientific search engine used in literature reviews. While this is not an all-inclusive list, some of the more prominent and frequently cited sources include…

PubMed/MEDLINE
EMBASE
Cochrane Library
PubMed Central
Ovid
Google Scholar

MedlinePlus
Directory of Open Access Journals (DOAJ)
PLOS ONE
ScienceDirect
Web of Science
Scopus

Step 4: Organize the literature you find

Searching for literature can start to get messy. You will want to have a process that will keep you organized. What may start out as 5-10 articles can quickly become 100 or more. A good starting point is to save the pdf’s in a single file folder. This may be enough organization for some, but more in depth reviews will require more organization.

A Microsoft Excel spreadsheet such as this one can help keep literature topics organized. This is a great way to set keywords to make it easier to organize your literature for when you go to write your research discussion. Putting in the work now will save you an incredibly large amount of frustration later on. Just trust me.

Further, web-based software such as Doodle Docs or Doodle Sheets could be helpful when multiple people are collaborating on a literature search. The bottom line is, there is no specific protocol for this. Get creative and find what works for you. Design your own organizational template to meet your needs.

Step 5: Organize your references

Once you’ve assembled some papers, there is a much easier way to organize these things once you’re writing a document. Mendeley is a free online program that will do this for you. Search for it and click download. Ever get confused on how to cite things, what the format should be, or hate switching around / moving citations? Mendeley does it for you.

The program has an add-on to Microsoft word, which will organize things for you. I recommend using this software for all of the articles that you will include in your article. Once installed, Mendeley can be opened from your desktop. From here, you can create folders and place all the pdf documents.

While in Microsoft Word, if you look under the references tab, you’ll see the Mendeley add-on.

When you want to start your References section, click on the ‘Insert Bibliography’ button. You’re probably going to place this at the end of your paper.

When you want to add a citation to your paper, find the spot you’d like to cite, and then click ‘Insert Citation’.

A search box will pop up. Type in a keyword from the title, the actual title itself, the author, etc, and then click on it. The citation will then automatically load into your reference section.

Continue to load all of your references in this manner. Once you get the hang of it, it’s a lot easier and will make adding citations much easier, especially if you need to reformat in a different style for a different journal.

Learning how to efficiently and effectively perform a literature search is paramount to any research project. Hopefully these tips and tricks will serve useful in this endeavor. Just remember, that even though this process may seem like extra work, it will save you an incredible amount of time and stress in the long run. I promise!

COVID-19 Vaccine – What you need to know

Nicholas McManus — Thu, 24 Dec 2020 00:19:30 +0000

How does the vaccine work?

SARS-CoV-2 is an RNA virus. The RNA that’s in the live virus codes for 29 different proteins. When the virus enters a cell during a natural infection, the RNA in the cell is chopped up into smaller pieces of mRNA, which serves as a template to code for 29 proteins to make more virus and the cycle continues.

Unlike most current vaccines, the Pfizer and Moderna vaccines do not contain material from the virus. Instead, it contains synthesized messenger RNA (mRNA), which serves as a blueprint that codes for just ONE of these proteins, the spike protein. This provides just enough training to the immune system to build antibodies. The mRNA itself is quite fragile, so it is encased in a shell made of lipids, or fats to keep the body’s immune system from destroying it before it gets into the cell.

Once inside the cell, the mRNA stays in the cytosol and does NOT enter the nucleus. Here, ribosomes transcribe the mRNA and make the spike protein. Our immune system then recognizes this spike protein and mounts an immune response against this protein. This is what causes the majority of mild symptoms from vaccines that may be similar to the real infection, but typically significantly more mild. After the mRNA is encoded, it is destroyed by the cell.

Why is the premise of mRNA vaccines so incredible?

Vaccines have given us great successes in the control of many diseases, including smallpox, polio, measles, mumps, rubella, and more. Can you imagine if we still had all these diseases, plus COVID-19?

Traditional vaccines use an inactivated virus or parts of a live but attenuated virus to stimulate an innate immune response and induce a T- and B-cell immune response. DNA vaccines do the same, but research has shown the potential for integration into human genome. However, an RNA vaccine CANNOT do this, as it never enters the nucleus of a cell. It couldn’t even if it wanted to as humans do not have the enzymes needed to do this. There is no way it can integrate into human DNA…it’s just not possible. Social media claims that this can happen are just not true.

Traditional vaccines take a long time because vaccine developers need to grow large amounts of virus, attenuate or inactivate the virus and this is quite difficult to do in a short period of time. That is why the influenza virus is a “best guess” of the strain that will be most prevalent the next year. It takes all year to produce it. With mRNA vaccines, you just need to know the genetic code and large amounts of vaccines can be produced within days to weeks. This could change the vaccine game forever.

Further, it is incredible that the effectiveness appears to be as high as it is for the Pfizer/BioNTech and Moderna vaccines (roughly 95% after the second dose). For comparison, the seasonal flu vaccine is only 40% effective at preventing the yearly flu (ranging 10-60% based on how good the guess is).

Without a vaccine, herd immunity is unlikely anytime soon.

Herd immunity is when the majority of the population becomes immune to a particular disease allowing transmission to be halted. This provides protection to individuals who aren’t immune. The number of people who will need to have immunity to reach herd status depends on the disease. In a previous post, we discussed the basic reproduction number, R₀ (pronounced R-naught).

Simply put, when the R₀is > 1, the infection will spread in a population and if it is < 1, it will fizzle out.

We can calculate the number of people who will need to be infected naturally, or obtain immunity through vaccine to reach herd immunity with the equation 1-1/R₀. There are a lot of variables to accurately determine an R₀. Most current estimates put the R₀ somewhere between 2.5 and 4. So, if we err on the side of caution and go with an R₀of 4, then 75% of the population will need to be infected naturally or achieve immunity to achieve herd immunity.

A recent study published in JAMA suggesting that < 10% of the U.S. has antibodies to COVID-19 at this time. As of November, the current rate of infection is roughly 1.3% of the population per month. If nobody gets the vaccine, it would take 4.5 years to reach herd immunity. More concerning would be the amount of time we would be allowing mutated strains to emerge.

If 60% of people get the vaccine, we theoretically reach herd immunity in just 2 months.

For a great explanation of the math behind this statement, check out this awesome article.

So, how many people are currently willing to get the vaccine?

September poll – 50% of Americans willing to get vaccine
November poll – 58% of Americans willing to get vaccine
December poll – 60% of Americans willing to get vaccine

Reasons people gave for not wanting the vaccine.

37% felt it was too rushed
26% want to wait for confirmation that vaccine is safe
12% don’t trust any vaccines
15% think the vaccine is too political
Despite the majority saying they would get a vaccine, only 37% said they were comfortable being in the first wave

What are the current known risks of the mRNA vaccines?

Nothing we do in healthcare is without risk. 10% of the population claims they have an allergy to Penicillin. However, we don’t avoid it’s use altogether because of this. We understand that the risk of allergies outweigh the risk of untreated infections. Adverse reactions to vaccines are to be expected. We can never have zero risk. The more important question should be, is the degree of risk worth the possible benefit?

The most common adverse effects from the Pfizer-BioNTech and Moderna vaccines are quite mild and resolve in a day or two. Preliminary data from the Moderna vaccine suggests up to 10% of people can experience mild symptoms for 7 days, but so did nearly 9% of the people in the placebo group.

The majority of people won’t have more than a sore arm for a day or two, some body aches, or a mild headache. This doesn’t mean you are infected with COVID. Its not possible to get COVID directly from an mRNA vaccine. It does produce a stronger immune response than some other vaccines, and that is the beauty of the design. Just understand that you will likely feel something, but it is unlikely dangerous and should resolve in a day or two with Tylenol, Motrin, and rest. An overview of published data from the Pfizer/BioNTech and Moderna vaccine trials are summarized below.

Pfizer – 36,621 participants

Ages > 16 years old
95% effective (52% after first dose)
2 doses (day 0, 21)

Ingredients

mRNA
Lipids
Potassium chloride
Monobasic potassium phosphate
Sodium chloride
Dibasic sodium phosphate dehydrate
Sucrose

Adverse Events

73% had NO symptoms after vaccine
Symptoms milder in those > 55 years old

Of the 27% who had side effects:

Injection site pain – 84%
Fatigue – 63%
Headache – 55%
Muscle pain – 38%
Chills – 14%
Joint pain – 11%
Fever – 16%
Bells Palsy – 4 patients

Serious adverse events – 0.6% (0.5% in placebo)

Anaphylaxis – 0%

Moderna – 30,350 participants

Ages > 18 years old
94.5% effective (80% after first dose)
2 doses (day 0, 28)

Ingredients

mRNA
Lipids
Tromethamine
Tromethamine hydrochloride
Acetic acid
Sodium acetate
Sucrose

Adverse Events

16% had NO symptoms after vaccine
Symptoms milder for those > 65 years old

Of the 84% who had side effects:

Injection site pain – 92%
Fatigue – 70%
Headache – 63%
Muscle pain – 60%
Chills – 45%
Joint pain – 45%
Fever – 15%
Bells Palsy – 4 patients (1 in placebo)

Serious adverse events – 1% (1% in placebo)

Anaphylaxis – 0%

There were a total of 6 people who died during the Pfizer/BioNTech study (2 in vaccine group and 4 in placebo group. Of those who died in the vaccine group, one was from cardiac arrest 62 days after the vaccine and 1 was from arteriosclerosis 3 days after the vaccine. There were a total of 13 people who died in the Moderna study (6 in the vaccine group and 7 in the placebo group). Of those who died in the vaccine group, 2 were > 74 years of age with pre-existing cardiac disease, 1 died of cardiopulmonary arrest 21 days after the first dose, 1 died of a myocardial infarction 45 days after the second dose, 1 died of trauma and 1 (a 70-year-old with a history of cardiac disease) was found deceased at home 57 days after the second dose. These deaths are unlikely due to the vaccine, as they occurred with higher prevalence in the placebo groups and occurred at rates similar to those of the general population.

What we don’t know

How long immunity will last after vaccination
If those who receive the vaccine can still transmit infection to others
Long-term safety data
Data in pregnant women, children, and those who are immunocompromised

But aren't mRNA vaccines new, how do we know they aren't dangerous?

It is important to realize that side effects to vaccines are common. I mean, we are literally trying to activate an immune response. Severe adverse reaction from all vaccines occur at a rate of 1.3 for every 1,000,000 vaccines given. There have been over 2,000,000 vaccines given in the first week with only 8 anaphylactoid type reactions reported, all treated without issue. We can expect common side effects to perhaps be slightly more prominent than the influenza vaccine based on what we know so far, and it may be worth scheduling your vaccine when you have a day off of work the next day. Available data suggests the vaccines appear relatively safe, which is why they were approved for Emergency Use Authorization through the FDA. It certainly seems more safe then COVID-19 at the moment.

While this is the first mRNA vaccine to be widely distributed and approved for emergency use by the FDA, they aren’t exactly new by any means.

Research of mRNA vaccines really started 30 years ago when scientists began to explore ways to make vaccine development easier. The first trial of mRNA transfer occurred in 1990 and showed that injecting RNA directly into the muscle of mice lead to measurable protein production that lasted for at least 2 months (Wolff, 1990). This was really the first proof of concept that mRNA could be used for vaccine development. In 1992, injection of vasopressin mRNA in rats led to a reversal of diabetes insipidus in rats (Jirikowski, 1992). However, the interest in developing mRNA technology didn’t gain much steam at this point. The largest problem being that the body’s natural defenses would likely destroy the mRNA before it would reach the target cell and the low antibody responses seen (Zhang, 2019). Further, there was concern that by injecting naked mRNA into humans could activate the immune system and cause a dangerous overactive immune responses as seen in some early animal models (Zhang, 2019).

For these reasons, RNA vaccine development was put on the backburner and DNA vaccines were more actively pursued throughout much of the 1990’s. However, some believe that an early focus on DNA rather than RNA sent the field down the wrong path (DeFrancesco, 2017). mRNA vaccines may be more appealing as they cannot cause an infection like whole virus vaccines can and they cannot integrate into host DNA as they do not enter the nucleus of the cell, but are transcribed in the cytosol and rapidly degraded (Nanomedicine, 2020). Current advances in mRNA vaccine technology no longer use naked mRNA for injection, rather they protect the mRNA in a lipid nanoparticle (small balls of fats) that protect the mRNA to prevent both rapid degradation by the body as well as an overactive immune response. This technology is currently being used in the BioNTech/Pfizer and Moderna COVID-19 vaccines, and is also not new technology as using lipids to translate mRNA into cells has been studied since the 1970’s (Dimitriadis, 1978).

Prior to COVID-19, several companies had already been funding mRNA vaccine research (BioNTech, CureVac, Infectious Disease Research Institute, Moderna, and Synthetic Genomics). Let’s take a look at the available published data.

Rabies mRNA Vaccine (CureVac)

The first human trail for an mRNA vaccine actually began in 2013 against rabies virus (Alberer, 2017). This was a proof of concept trial with participants getting an initial series off 3 injections, followed by a booster 1 year later in non-pregnant adults age 18-40. The first bit of data from this trial, which is still ongoing, was published in 2017. Out of the 101 patients in the initial trial, 1 patient had what was considered a severe allergic reaction occurring on day 7, that resolved without issue. Other adverse events reported were rather mild (myalgias, pain at injection site). Ongoing monitoring for long-term adverse events are ongoing, with the last update published in 2018 (NCT02241135). While the vaccine has so far proven to be fairly safe, the major issue with this study is that the delivery methods trialed did not keep antibody titers for very long. Regardless, it showed proof of concept for mRNA vaccines in humans.

Influenza mRNA Vaccine (Moderna)

In 2019, Moderna published data from 2 placebo randomized controlled trials from 2015-2017 using mRNA vaccines against 2 avian influenza strains (Feldman, 2019). A total of 357 adults, ages 18-64, were included in the 2 trials. Not a single serious adverse event was reported from the vaccines. More importantly, no immune-mediated medical conditions or chronic illnesses have been reported. Further, antibody titers were better sustained than in the Rabies study.

Zika mRNA Vaccine (Moderna)

Data from the Moderna Phase 1 human trial of 120 patients that begain in July of 2019 (NCT04064905) was last updated in October of 2020. Common adverse effects were the same as most all vaccine trials (pain, redness, and swelling at the injections site, fever, headache, chills, body aches). Again, no severe adverse events have been reported and no immune-mediated medical conditions. Specific interim data from this ongoing study can be found here.

Cytomegalovirus mRNA Vaccine (Moderna)

Currently, this trial includes 252 patients and is in Phase 2, with the last data updated in September of 2020. Phase 1 showed adequate titers out to 12 months since the trial started in September of 2019. More importantly, adverse events were similar to those seen in other mRNA studies, such as local pain and swelling, fever, headache, myalgias, etc. No serious adverse events have been identified in the first 12 months of this study.

Other prophylactic mRNA vaccines currently being studied in various preclinical and clinical phase 1 development include vaccines against human metapneumovirus and parainfluenza virus 3 (hMPV/PIV3), pediatric respiratory syncytial virus (RSV), Epstein-Barr virus (EBV), and Influenza H7N9.

Further, therapeutic mRNA-based treatments are being studies for Chikungunya virus, autoimmune hepatitis, and IL-2 specific autoimmune disorders, propionic acidemia, methylmalonic acidemia, phenylketonuria, and glycogen storage disorder type 1a. Moderna is also studying mRNA vaccines in the prevention of multiple cancers (i.e., melanoma, non-small cell lung cancer, colorectal cancer, and pancreatic cancer).

What if I just take my chances with COVID-19

Influenza kills an average of 389,000 people yearly worldwide. Over the last 10 months, COVID-19 has killed 1,697,679 people and counting. This doesn’t include the unknown number of secondary consequences from an over-run healthcare system to include patients who will have a delayed diagnosis of other diseases such as cancers, diabetes, heart disease, mental health, and substance abuse as well as the economic impact of restrictions.

The case fatality rate is the number of deaths divided by confirmed cases. According to Johns Hopkins, case fatality rates are 1.8% in the United States, 3.3% in the United Kingdom, and 2.2% globally. Case fatality isn’t the exact number of people who die from the illness, because we can assume a number of people will get the disease and never get tested. Further, we can assume more people who have been diagnosed will eventually die. This number varies widely during the outbreak and can be affected by capabilities of treatment facilities and the ability to manage a surging population of patients.

You may hear of another statistic, known as the Crude Fatality Rate. This is the number of people who die of a disease in a given population. Currently, this value for the United States is 0.1% and often incorrectly used minimizes the deadliness of this disease. This means that roughly 100 people have died per 100,000 people in the population. This is incredibly misleading as 100% of the population has not been infected.

A recent study published in JAMA, revealed that less than 10% of the U.S. population currently has detectable antibodies, suggesting only 1 in 10 people have been infected after 10 months. So, the true number of people who are at risk of dying from COVID is certainly higher than frequently quoted 0.1%. I would suggest that based on this knowledge, if 100% of the U.S. population would get infected, somewhere around 1% can be expected to die as a result of infection as an educated estimate with control measures currently in place. The current estimates from the CDC, suggest this number is 0.5-1.5%. This value would no doubt be higher if everyone got infected at the same time as many hospital systems are already overwhelmed.

Just because you are young and healthy, doesn't mean you can't get incredibly sick.

A recent study of 513 young adults (age 18-49) with NO medical conditions hospitalized with COVID-19 in the United States showed that 22% (1 in 5) were admitted to the ICU, 10% were on a ventilator, and 0.6% died (Owusu, 2020). Data from early in the pandemic suggested that overall, 81% of patients will have mild disease, 14% will need to be hospitalized, and 5% will need the intensive care unit (Wu et al., 2020). In a study published in JAMA last week of 64,781 patients hospitalized with COVID-19 in the U.S. during the first wave, 20.3% of patients hospitalized for COVID-19, died.

Let's say you don't die...there may still be long-term effects of COVID.

While the exact long-term effects of COVID-19 are not entirely known, we do have 10 months of data and the long-term effects on different organ systems is quite concerning. Only 12% of patients who were hospitalized are free of symptoms after 60 days. Symptoms of fatigue, shortness of breath, cough, joint pain, chest pain, rash, or hair loss and loss of taste and smell has been reported to linger for months in some patients.

Cardiovascular Effects

Imaging tests taken months after recovery from COVID-19 have shown lasting damage to the heart muscle, even in people who experienced only mild COVID-19 symptoms. This may increase the risk of heart failure or other heart complications in the future.
In a German study of 100 patients recovered from COVID-19, 78% had cardiac involvement on cardiac MRI 2.5 months after infection and 60% of people have cardiac inflammation. More concerning, chronic comorbidities and severity of COVID-19 infection did not correlate with these findings.
In a study of 26 college athletes who did not require hospitalization, 46% of them had evidence of myocarditis or myocardial injury by cardiac MRI (mean test 12-53 days after infection).

Neurologic Effects

Even in young people, COVID-19 can cause strokes, seizures, and Guillain-Barre syndrome and may increase the risk of developing Parkinson’s disease and Alzheimer’s disease.
1 in 7 hospitalized patients develop neurological disorders (stroke, meningitis/encephalitis, seizures (Frontera, et al.).
- 50% of those with brain dysfunction were under the age of 63
- Inflammatory CNS syndromes
- Encephalopathies (Helms, et al.)
- Stroke (5.7% in severe disease, 0.8% in non-severe disease) (Mao, et al.)
- Guillain-Barré Syndrome (Toscano, et al.)
“Brain fog” and mood swings have been reported up to 2-3 months after illness.
1 in 5 patients may develop a mental health disorder within 3 months of getting the virus (Taquet, et al.).
Chronic cognitive decline, aging the brain by 10 years, even in mild cases not requiring hospitalization (Hampshire, et al., Zhou, et al.).

Lung Effects

The type of pneumonia often associated with COVID-19 can cause long-standing damage to the lungs. The resulting scar tissue can lead to long-term breathing problems.
16% of patients hospitalized with COVID-19 will have a pulmonary embolism (Desai, et al.).
In a study of 55 patients, 65% had persistent symptoms and 71% had imaging abnormalities such as interstitial thickening and fibrosis 3-months after hospital discharge.
In a study of 57 patients, significant lung dysfunction was seen in 50% of patients 1 month after discharge.

We also have some useful data from case series following the 2003 SARS outbreak.

In a 2-year prospective study of 123 patients who recovered from SARS, 53% had significant lung damage at 2 years. 30% of healthcare workers and 7% of non-healthcare workers were unable to work at 2 years. Further, if patients still had symptoms at 6 months, they still had them at 2 years.

In a 4-year follow-up study of 233 SARS survivors, 40% had active psychiatric illness and 30% were formally diagnosed with chronic fatigue syndrome.

In a 15-year follow up study of 78 SARS survivors, 38% still had abnormal lung imaging. 22% of patients had restrictive lung disease at the 4-year follow up in this study, and fortunately all had returned to normal function by pulmonary testing criteria at 15 years.

I already had COVID-19, should I get the vaccine?

The short answer is…eventually. We don’t know exactly how long people will keep antibodies against SARS-CoV-2 after natural infection. One thing we do know is, the Pfizer and Moderna vaccines produce antibody levels roughly 4-times higher than those seen in natural infections. So what does the data show?

In a study published in July of 2020, patients still had high levels of antibodies at 4 months post infection, while those with asymptomatic or mild cases may show a more rapid decay. Newer research suggests neutralizing antibodies are still present for at least 5-7 months in symptomatic patients, and perhaps longer. While the duration of antibody presence is still unknown, we do know that re-infection is unlikely within 90 days of initial infection.

Roughly 2% of participants in the Moderna vaccine trial had detectable antibodies before receiving the vaccine with no poorly associated outcomes. Currently, the CDC recommends patients who have been infected or have received monoclonal antibody treatment (i.e. Bamlanivimab) wait to get vaccinated until they have recovered from their illness. The terminal half life of Bamlanivimab is 17.6 days and was identified for at least 29 days after treatment. Until an abundance of vaccine is available, those who have been infected or received monoclonal antibody treatment should consider waiting 90 days to allow others, who have not been infected, to get the vaccine.

Pregnant and lactating women as well as those immunocompromised were excluded from the mRNA trials. What do their respective societies think?

Patients with Allergies

Allergic reactions to vaccines, in general, are rare with the incidence of anaphylaxis estimated at 1.31 in 1 million doses given. According to the American College of Allergy and Immunology, individuals with common allergies to medications, foods, inhalants, insects, and latex are no more likely than the general public to have an allergic reaction to the mRNA COVID-19 vaccines. Those with a history of severe allergic reaction to polyethylene glycol (in Miralax, Toothpaste, baby wipes, cosmetics), should not get the vaccine. Data related to risk in individuals with a history of allergic reactions to previous vaccinations and/or mast cell activation syndrome/idiopathic anaphylaxis is very limited and evolving. A decision to receive a vaccine should be undertaken by you with your physician. The CDC recommends that people who have had a severe allergic reaction to any vaccine or injectable therapy not receive the mRNA vaccine at this time. Those with a history of allergic reactions should be monitored for 30 minutes following injection, if they do receive the vaccine.

Immunocompromised Persons

People with HIV or other immunocompromising conditions or those who take immunosuppressive medications or therapies might be at an increased risk of severe COVID-19. The vaccine safety profile is not entirely known in this population.

The American College of Allergy and Immunology endorses the fact that mRNA vaccines are not living vaccines, and can be used in immunocompromised patients. They do mention that there is a possibility of a diminished immune response to the vaccine in patients on immunosuppressive medications and it is uncertain if patients with a weakened immune system will respond to the COVID-19 vaccine. The CDC recommends immunocompromised persons still receive the COVID-19 vaccine unless otherwise contraindicated.

Pregnant and Lactating Women

Pregnant and lactating women were excluded from the mRNA COVID-19 trials, as they are from almost all vaccine trials. However, there were women who became pregnant during the studies. Adverse outcomes of these patients have not been reported. The risks of any vaccine should be weighed against the risks of not getting the vaccine. Available data tells us that pregnant patients are at an increased risk for more severe disease, 5.4 times more likely to need hospitalization, 2.6 times more likely to require intensive care and mechanical ventilation.

The American College of Obstetricians and Gynecologists (ACOG) states that the vaccine should not be withheld from pregnant women. Further, the Society of Meternal Fetal Medicine (SMFM) states that the safety risk of mRNA vaccination for pregnant or lactating women appears low, and recommends that pregnant and lactating women should be offered vaccination as these vaccines are not live vaccines and are not thought to be a risk in vertical transmission or to a breastfeeding infant.

A study of the Moderna COVID-19 vaccine looking at animal developmental and reproductive toxicity in rats was submitted to the FDA on December 4, 2020. FDA review of this study concluded that a dose of 100 μg given prior to mating and during gestation periods did not have any adverse effects on female reproduction, fetal/embryonal development, or postnatal developmental except for skeletal variations which are common and typically resolve postnatally without intervention.

The CDC recommends the mRNA COVID vaccine be offered to pregnant and lactating women, particularly if part of a high-risk group (i.e. healthcare personnel) and this decision should be based on discussion with their obstetrician.

SMFM will continue to monitor data as it becomes available on COVID-19 vaccine efficacy and safety to evaluate appropriateness in pregnancy, and we will update recommendations on the SMFM COVID-19 website.

Pediatric Use

The Pfizer/BioNTech mRNA vaccine included people down to age 16, while the Moderna vaccine used the inclusion of 18 years or older. These are the age cutoffs for each vaccine under the FDA Emergency Use Authorization. Moderna does have an ongoing study using mRNA vaccine against RSV in children, but this is still in Phase 1 of development. Further, Moderna has started clinical trials on mRNA vaccines for those aged 12-17 years. So stay tuned.

Conclusion

There has been a polarization of opinions and a distrust in the medical sciences over the last year, which hurts my heart. I have no financial interests and I have no personal gain (other than the fact that I preferred life without COVID). I have never diagnosed anyone with COVID-19 who did not test positive for it, and I don’t know anyone who has. The people I do know spend countless hours at the hospital treating patients with this disease and spend countless hours at home dissecting the emerging literature to learn how to beat this thing.

I read the studies and I trust the peer reviewed nature of medical literature. More importantly, I have faith in the good nature of the people in my field. I see the ugliness that this disease causes on a daily basis. People in their 20’s with blood clots in their lungs. Pregnant women with heart failure. People in their 30’s who go to bed with a cough and never wake up. I see people in their 60’s with acute confusion that mimics that of advanced Alzheimer’s disease. In March, I was admitting people with COVID-19 to the hospital. In December, I am admitting families with COVID-19. The reports are not hype and this is not meant to be a scare tactic…it is our reality.

While I cannot say with 100% certainty that the vaccine will harm nobody, I have confidence in the evidence at present to know it is better than the alternative. That is why I got my vaccine on Friday, December 18, 2020. I hope you do the same when it’s your turn to choose.

FYI: My only side effect was a moderately sore arm for about a day. I will update after I get my second dose.

Calcium Emergencies

Nicholas McManus — Mon, 30 Nov 2020 17:26:06 +0000

80% of all calcium is bound to albumin in circulation. However, the biologically active form of calcium is the free, or ionized form, which is occasionally ordered as a separate test. Typically, a total serum calcium level should be used as a screening test. And if low, an ionized calcium level should be ordered prior to treatment, as the active form of calcium may actually be normal despite a low total calcium level.

Calcium plays many important biological functions, including building strong bones and teeth, clotting of blood, Sending and receiving nerve signals, muscle contraction and relaxation, cardiac contraction and in the release of many hormones from both the anterior and posterior pituitary in the brain.

Blood calcium levels are regulated to keep a total serum calcium concentration around 10 mg/dL. Serum levels are primarily controlled by 3 hormones (PTH, 1,25-dihydroxyvitamin D and Cacitonin). As blood calcium levels fall, the parathyroid gland, which are located within the thyroid, secretes the hormone parathyroid hormone, or PTH. PTH can directly stimulate Calcium uptake in the kidneys, resulting in an increased blood calcium levels. The kidney also activates Vitamin D to increase calcium uptake in the intestines, again increasing blood calcium levels. Finally, PTH also stimulates calcium reabsorption from calcium stores in bones, further increasing serum calcium levels. Calcitonin causes direct inhibition of bone resorption with increased calcium levels.

HYPERCALCEMIA

Hypercalcemia can be caused by hyperparathyroidism, where an excess amount of PTH is released, by excessive Vitamin D intake, which increases calcium reabsorption in the intestines, Thiazide diuretic use, which causes calcium sparing in the kidney, adrenal insufficiency, and certain types of cancers, such as multiple myeloma which cause hormone mediated increases in calcium similar to PTH. Patients with heartburn may take excessive amounts of calcium carbonate or tums, which increase serum calcium levels, which is known as milk-alkali syndrome.

Causes:

Hyperparathyroidism (usually mild, < 11.2)
Malignancy (Usually rapid rise)
Vit. D excess
Hyperthyroidism
Thiazide diuretics
Milk-alkali syndrome
Adrenal insufficiency

Patients experience the pathomnemonic symptoms of “stones, bones, groans and psychiatric overtones.” That is, patients can experience bone loss from higher levels of calcium reabsorption and inappropriate bone remodeling, kidney stones and kidney disease from increased calcium concentrations in the renal tubules, psychiatric disturbances and abdominal pain.

Additional Labs:

Lab values can give clues into the underlying process causing hypercalcemia. Lets quickly review the key players here…

PTH – a decrease in calcium levels leads to an increase in PTH secretion, which increases bone resorption, renal and intestinal absorption as well as increased urinary phosphate excretion.

Vitamin D – a decrease in calcium leads to activation of vitamin D, which increases bone and intestinal resorption

Calcitonin – causes direct inhibition of bone resorption with increased calcium levels

PTH
- ↑ – primary hyperparathyroidism
- If < 20 pg/mL = Consider Vit D and add on a PTH-rP (increased in some cancers)
Vitamin D
- 25-hydroxy Vit D = ↑ with exogenous intake
- 1,25-dihydroxy Vit D = ↑ with lymphoma, sarcoid

Hypercalcemia Treatment

Treatment Goals

Immediate therapy for corrected total > 14 mg/dL regardless of symptoms
Asymptomatic, mild hypercalcemia does not require emergent treatment

Step 1: Restore IV volume

200-300 mL/hr isotonic saline (titrate to UOP 100-150/hr)
Often need 2-5 L/day

Step 2: Renal Elimination

After volume expansion – Give Lasix if Ca still high or if fluid overload
Don’t use in children – may decrease GFR and worsen hypoCa

Step 3: Inhibit Osteoclastic activity

Reduce mobilization of Ca from bone with Bisphosphonates of Calcitonin
Likely safe in children

Admission Criteria:

Corrected total Ca > 13
Symptomatic or EKG changes
ICU admit if > 14

Discharge Criteria

Asymptomatic
Corrected Ca < 13

HYPOCALCEMIA

Hypocalcemia is seen when ionized calcium levels drop below 4.6 mg/dL. This can occur from an increased loss of calcium or from decreased entry of calcium into circulation. Roughly half of circulating calcium is pound to proteins (mainly albumin) and roughly half is ionized, which is thee free and active form. Therefore, it should not be surprising that hypoalbuminemia is the most common cause of hypocalcemia. can be due to an underactive parathyroid gland, vitamin D deficiency, renal failure or any disease process that causes calcium sequestration such as pancreatitis.

Causes

Hypoalbuminemia – most common
Hypoparathyroidism
Vitamin D deficiency
Chronic renal failure
Calcium sequestration (pancreatitis, citrate exess after blood transfusions, acute PO4 increase in rhabdo)
Hypomagnesemia
Medications – PPI, Bisphosphonates, Calcitonin, Phenytoin, Phenobaarbital, Colchicine

Symptoms of hypocalcemia typically occur when ionized calcium levels fall to < 3.2 mg/dL but are also dependent on the rate at which the level falls. These include psychiatric disturbances such as irritability, confusion, delusions, chorea and parkinsonisms. Cardiovascular disturbances include bradycardia , QT and ST prolongation that can progress to heart block and Torsades de pointes. Neurologic manifestations include paresthesias, hyperreflexia, muscle spasms, seizures and tetany.

Clinical signs such as Chvostek and Trousseau signs may be seen. Chvostek sign includes tapping your finger over the parotid gland over the facial nerve, which causes muscle spasm. Trousseau sign is when you see a slow carpopedal spasm when a blood pressure cuff is inflated over the upper arm.

Additional Labs:

Lab values can give clues into the underlying process causing hypocalcemia. Lets quickly review the key players here…

PTH – a decrease in calcium levels leads to an increase in PTH secretion, which increases bone resorption, renal and intestinal absorption as well as increased urinary phosphate excretion.

Vitamin D – a decrease in calcium leads to activation of vitamin D, which increases bone and intestinal resorption

Calcitonin – causes direct inhibition of bone resorption with increased calcium levels

PTH
- ↑↑ – Pseudohypoparathyroidism
- ↑ – Vitamin D Deficiency
- ↓ – Hypoparathyroidism

Phosphate
- ↑ – Hypoparathyroidism
- ↓ – Vitamin D Deficiency

Hypocalcemia Treatment

Treatment is to replace calcium. If the patient is symptomatic, this is given as calcium gluconate or calcium chloride IV.

Caution should be given to patients on Digoxin receiving IV calcium, specifically calcium gluconate, as there is a theoretical risk of causing calcium influx into myocardial cells resulting in a phenomenon known as “stone heart” resulting in malignant dysrhythmias. I will say, literature has not reproduced evidence that this is causation.

Basis of the theory…
- Digoxin inhibits Ca transport out of myocytes AND form Ca-channels in lipid bilayers – import Ca
- Ca was found to increase digoxin toxicity in animal models
- Only 5 total case reports showing a temporal increase in mortality (all from the 1930-1950’s)
Issues with this theory…
- Several case reports also showing no harm
- Of the 5 case reports, no report of digoxin levels and only 2 showed a temporal increase in mortality
- Animal models have not been able to reproduce early models (Hack et al, 2004)
- Early animal models were severely hypocalcemic (> 15 mM/L) prior to Digoxin administration (Noel, 1970)
- Levine et al, 2011
  - Showed no dysrhythmias or increased mortality with chronic Digoxin use and IV Calcium (2020 patients)
  - Only level of K associated with increased mortality (OR 1.5 for each 1 mEq/L increase in serum K)
  - Only 1 case was digoxin toxic (no clear evidence to date either way if dig toxic)

Acute Treatment – Should be done with IV Calcium if symptomatic

Bolus infusions over 20 min
Faster rates can cause cardiac dysrhythmias
Bolus doses only increase Ca for 1-2 hours, so patients with severe hypocalcemia should be followed with an infusion at 0.5-3 mg/kg/hr (will raise serum levels by 1.2-2 mg/dL over 4-6 hours)
Monitor ionized Ca levels every 1-2 hours and adjust infusion rate as needed.

Which Calcium formulation should I use?

Calcium Gluconate: 1–2 g in 50 mL D5W (1g=90mg [4.5 mEq] elemental Ca)
- Preferred form if patient is stable
Calcium Chloride: contains 3 x the elemental Ca (13.6 vs 4.6 mEq in 10 mL of a 10% solution)
- Preferred if unstable – make sure IV is a good one
- More likely to cause tissue necrosis with extravasation (best to use a central line)
Calcium Gluceptate: 1g in 5 mL (1g=90mg [4.5 mEq] elem Ca)
- Can be given IV or IM

Pediatric Considerations

Calcium Gluconate 1 – 2 mL/kg not to exceed 5 mL in premature infants or 10 mL in term infants

Replace Vitamin D

Calcitriol (1,25 dihydroxyvitamin D) is the most active vitamin D metabolite. Further, it does not require hydroxylation in liver or kidney and therefore has a rapid onset of action and can be used in patients with rental failure
Give at a dose of 0.25-1 mcg IV or PO 1-2 times daily
Give to all patients with severe hypocalcemia (don’t wait for PTH and Vitamin D levels to result)

Replace Magnesium

Magnesium converts Vitamin D into its active form.
2g IVPB 10% solution over 10 min
Faster rates can cause cardiac dysrhythmias

Admission Criteria:

Symptomatic or EKG changes
Ionized Ca < 3.2 mg/dL
Continuous IV calcium necessary

Discharge Criteria

Asymptomatic
Ionized Ca > 3.2 mg/dL in healthy patients with no comorbid illnesses

Chronic Treatment – Can be done with PO Calcium if asymptomatic

Typical starting doses are 1-2 grams of elemental calcium divided 2-3 times daily
May need up to 4 g/day in patients with malabsorption
Doses may need to be adjusted based on tolerance, compliance and treatment goals.

Calcium carbonate (1 g = 400 mg elem Ca)

Should be taken with food
GI upset and constipation can occur
Requires acidic environment for absorption
Do not use this form if on a PPI

Calcium citrate (1 g = 211 mg elem Ca)

Preferred in patients on a PPI
Less GI adverse effects
Does not need to be taken with food

Calcium glubiomate (1 g = 65 mg elem Ca)

Small dose of elemental Ca, would need many pills

Calcium gluconate (1 g = 90 mg elem Ca)

Small dose of elemental Ca, would need many pills

Calcium lactate (1 g = 130 mg elem Ca)

Small dose of elemental Ca, would need many pills

Don’t forget to supplement Vitamin D as well

- Ergocalciferol (Vitamin D2) or Cholecalciferol (Vitamin D3) if no history of hypoparathyroidism or renal failure
  - 50,000 IU weekly or 6,000 IU daily for 6 weeks
  - Consider increased dose 2-3 fold if obese, malabsorption syndrome or drug induced Vitamin D deficiency
  - Recheck Vitamin D levels every 1-3 months to avoid toxicity
- Calcitriol if patient has a history of liver or renal failure

Calcium content in food

Milk or yogurt (8 oz) = 300 mg

Cheddar cheese (1 oz) = 200 mg

Ca-fortified cereal (1 cup) = 300 mg

Ca-fortified orange juice (1 cup) = 270 mg

Shrimp (3 oz) = 50 mg

Peanuts = 130 mg

Orange = 50 mg

Bamlanivimab for COVID-19 – what you need to know

Nicholas McManus — Tue, 17 Nov 2020 23:08:46 +0000

As hospitals around the country reach critical capacity of patients with COVID-19, treatment focus shifts to ways we can treat people more aggressively before they even need hospitalization at all. At this point, just about every medication already on the market has you been proposed as a possible treatment option. Honestly, it’s a bit overwhelming to keep up. Over the next few days to weeks, you will be hearing about a few new monoclonal antibodies identified as a potential treatment option for those patients who are identified as being at risk of getting worse, but don’t meet criteria for needing hospitalization. From what we know, 10% of those patients who are initially asymptomatic or have a mild disease at the time of diagnosis will develop severe disease requiring hospitalization later in the disease course. It would be ideal to target this population with treatment, before they worsen and would require hospitalization. This article focuses on one particularly monoclonal antibody, Bamlanivimab, as it was approved on November 9th by the FDA for emergency use in the treatment for a specific group of patients with COVID-19. At present, this medication is being allocated to each state at no cost by the U.S. Department of Health and Human Services. Once this allocation runs out, it is uncertain how costly the medication will be.

What is Bamlanivimab?

Bamlinivimab (LY-CoV555) is a human IgG1 antibody developed by Eli Lilly and company, a pharmaceutical company headquartered in Indianapolis, Indiana. But you may hear it called other names….

How does it Work?

Bamlanivimab blocks the spike protein on the SARS-CoV-2 virus, which prevents it from binding to the ACE-2 receptor in human cells. These receptors are scattered throughout the body, including the lungs, heart, bladder, pancreas, testis, kidney, nose, eye and brain (Muus, 2020). Its literally everywhere. This receptor has been a prime target for treatment development since it was first identified as playing a pivotal role in viral entry into the cell.

What does the ACE-2 receptor have to do with it?

After the virus binds to the ACE2 receptor in human cells, it enters the cell. Once the virus enters a cell, it begins to replicate and eventually kill the host cell. This triggers an inflammatory response that produces pro-inflammatory cytokines, activates macrophages and Th1 cells that leads to cytokine storm, respiratory distress syndrome and secondary hemophagoytic lymphohistiocytosis (Gubernatorova, 2020).

Who is our target population for this drug?

The bad outcomes we see from COVID-19 are strongly associated with those who develop severe respiratory distress syndrome from an over-active inflammatory response. People identified as being at risk for this response are those aged > 65 OR those aged > 55 with a history of chronic cardiovascular or respiratory diseases (i.e. pulmonary fibrosis, COPD, Asthma), diabetes, hypertension, obesity (BMI >35) and chronic immunosuppression (i.e. cancers, on immune suppressing medications) are > 65 years old. Further identified risk factors are pediatric patients between 12-17 years of age with a BMI > 85th percentile for their age, sickle cell disease, congenital heart disease, neurodevelopment disorders (i.e. cerebral palsy), dependent on a chronic medical device (i.e. tracheostomy, gastrostomy) and those with history of chronic lung disease (i.e. asthma) requiring daily medication for control. Growth charts for pediatric patients can be found here on the CDC website.

The goal of this medication is not to “cure” COVID-19. It is to decrease the amount of virus that is replicating in hopes that it will prevent an inflammatory cascade and limit the number of people who will progress to requiring oxygen supplementation and hospitalization. Below, I will discuss the actual data from the BLAZE-1 trial. For now, just know that patients who received this medication after they were already sick enough needing to be admitted to the hospital did worse. The only benefit was its use in patients BEFORE they developed severe pulmonary disease, and this is the population that we need to be targeting. The benefits are therefore time dependent. Give it early, or don’t give it at all.

Bamlanivimab is ONLY authorized for specific criteria…

Has a positive SARS-CoV-2 test, PLUS
Age 12 years or older with a BMI of at lease 40kg, PLUS
Not sick enough to require hospitalization, PLUS
Not sick enough to require oxygen therapy (this includes an increase flow rate for those on chronic oxygen), PLUS
Considered high risk for progressing to severe COVID-19, PLUS
Less than 10 days since symptom onset

Criteria to be considered high risk for progression to Severe COVID-19

Have a body mass index (BMI) ≥ 35
Have chronic kidney disease
Have diabetes
Have immunosuppressive disease
Are currently receiving immunosuppressive treatment
Are ≥ 65 years of age
Are ≥ 55 years of age AND have
- cardiovascular disease, OR
- hypertension, OR
- chronic obstructive pulmonary disease/other chronic respiratory disease.
Are 12 – 17 years of age AND have
- BMI ≥85th percentile for their age and gender, OR
- sickle cell disease, OR
- congenital or acquired heart disease, OR
- neurodevelopmental disorders, for example, cerebral palsy, OR
- a medical-related technological dependence, for example, tracheostomy, gastrostomy, OR
- positive pressure ventilation (not related to COVID-19), OR
- asthma, reactive airway or other chronic respiratory disease that requires daily medication for control

A few considerations on administration…

The window of opportunity is just 10 days from symptom onset
The patient must have a documented positive COVID-19 test
It will take roughly 3 hours to administer the medication
- It infuses over 1 hour
- Patient must be observed for 1 hour after the completion of the infusion
The mixture is stable for 7 hours at room temperature and 24 hours under refrigeration.

What are the risks?

Bamlanivimab is a new drug, and unfortunately the adverse effects are limited to only those seen in the BLAZE-1 trail (NCT04427501).

309 patients were included in the treatment arms of this study and out of these, 2 patients had severe reactions, 1 requiring epinephrine for anaphylaxis. Neither patient died. From the overall data of all 309 patients in the 3 arms that received Bamlanivimab at varying doses in the BLAZE-1 study, we get a number needed to harm (NNH) of 156.

One important thing to note is that there were 4 arms in the Blaze-1 trial (Placebo, 700mg, 2800mg and 7000mg). There were 0 severe or serious adverse events at the 700mg dose, which is the current dose authorized for emergency use by the FDA.

Interestingly, there was 1 serious adverse event in the PLACEBO group (defined at anaphylaxis, life threatening laryngospasm or laryngeal edema) with ZERO serious events in any of the 3 arms that actually received the drug.

Another interesting point to make is that there were a higher number of patient reported adverse events in the PLACEBO group than there were in any other arm of the study. So, overall it appears the risk of this medication is fairly low at the dose of 700mg being given.

All reported adverse events at the 700mg dose include (from 101 patients)...

Nausea – 3%
Diarrhea – 1%
Dizziness – 4%
Headache – 3%
Pruritis – 2%
Vomiting – 1%
Pyrexia – 1%
Rash – 1%

Chest pain – 3%
Dyspepsia – 1%
Hypertension – 3%
Lipase increased – 1%
Thrombocytosis – 1%
Hypersensitivity – 1%
Nasal congestion – 1%

So, lets take a closer look at the study...

A full copy of the protocol can be found here.

The published interim analysis of the BLAZE-1 study can be found here.

Title: SARS-CoV-2 Neutralizing Antibody LY-CoV555 in Outpatients with Covid-19
Trial Type: Ongoing phase 2, randomized, double-blind, placebo-controlled, single-dose trial
Population: 453 patients at 41 hospitals across the United States, who tested positive for COVID-19 with one or more mild to moderate symptoms confirmed COVID-19 positive
Intervention: Single dose Bamlanivimab infusion over approximately 1 hour
Treatment Arms:
- Placebo (N=143)
- 700mg dose (N=101)
- 2800mg dose (N=107)
- 7000mg dose (N=101)

Design: Follow-up on day 1 was on-site. Follow-up on days 2,4,5 and 6 were done by telephone. Follow-up on days and 7-29 were done at an outpatient clinic or with home visits. Lab markers followed include hsCRP, Ferritin, D-dimer, Procalcitonin and Troponin measured before infusion, and on day 1, 3, 15 and 29. Patients were also allowed to receive local standard of care (including lopinavir/ritonavir, chloroquine, hydroxychloroquine or other investigational agents. However, convalescent plasma was not allowed.

Serious Adverse Events: Defined at anaphylaxis, life threatening laryngospasm or laryngeal edema

Inclusion Criteria:

Age > 18
Men and non-pregnant women
Not hospitalized at randomization
Have one or more of the following symptoms:

Fever, cough, sore throat, malaise, headache, muscle pain, GI symptoms, shortness of breathh with exertion
First positive swab < 3 days from infusion

Exclusion Criteria:

SpO2 < 93% on room air
Respiratory rate > 30
Heart Rate > 125
Requiring mechanical ventilation or anticipated need
Known allergies to drug
Hemodynamic instability
Suspected infection other than COVID-19
Co-morbidity requiring surgery < 7 days
Co-morbidity considered life threatening < 29 days
Serious concomitant systemic disease
Prior positive SARS-CoV-2 serology test
Prior positive SARS-CoV-2 swab
Received other treatment of prophylaxis (monoclonal antibody, convalescent plasma, vaccine, etc.)
Pregnant or breast feeding

Primary Objective:
- Change from baseline viral load to that seen on day 11 (+ 4 days)
Secondary Objectives:
- Safety assessments such as adverse events and serious adverse events
- Change from baseline viral load to Day 11 (+ 4 days) viral load enrolled with < 8 days of symptoms
- Time to resolution of symptoms
- Time to symptom improvement
- Time to SARS-CoV-2 clearance
- Mean SARS-CoV-2 concentration on day 29

Results:

The groups were balanced in regards to co-morbidities, age and risk factors
By day 11, all groups (including placebo) had more than 99.97% elimination of viral RNA
However, the biggest benefit to clearance was seen in the first 3 days, and this decrease was similar regardless of the medication dose given (see chart below)
Hospitalizations were significantly lower in all treatment arms. This also didn’t seem to be dose dependent
Symptom scores were better (although barely) in the pooled Bamlanivimab group compared to placebo

Conclusions: The current dose approved for emergency use by the FDA is 700mg infusion over 1 hour. Based on this study, we can currently discuss the following with our patients:

- There is a 1 in 4 chance of having mild side effects (nausea, headache, etc.). However, this was similar to people who do not receive the medication questioning if these are adverse effects of the medication, or just symptoms of COVID-19.
- There were NO serious adverse effects were not seen in the 101 patients who have received the dose we are giving you. 1 in 156 patients who have received higher doses of this medication had a serious reaction including anaphylaxis, but responded well to epinephrine without issue. No patients have died.
- This medication decreases the overall risk of hospitalization in patients in your similar situation from 6.3% to 1-2%.
- This medication will decrease the amount of virus you have over the next 3 days by nearly 35%, compared to if you do not get this medication. Our hope is this will prevent you from experiencing a more severe inflammatory response and keep you out of the hospital.
- You may have a slight improvement in the severity of your symptoms, but that is not the overall purpose of this medication.

Study Limitations:

This trial has yet to conclude. It is an ongoing study, with plans to enroll 1,200 patients.
It is an industry sponsored study, sponsored by Eli Lilly and Company, who manufactures the drug.
Patient were excluded who have a serious concomitant systemic disease, condition or disorder. This decision was made based on the opinion of the investigator and not apparent in the protocol.
The secondary outcome of decreased hospitalization wasn’t in the protocol. It is a nice bonus, but seems to be a shift in the entire focus of the study that occurred after the fact.
Patients were also allowed to receive local standard of care (including lopinavir/ritonavir, chloroquine, hydroxychloroquine or other investigational agents. The exact impact number of people who received these medications are not immediately apparent in the published data.

A quick note about another Monoclonal Antibody (Regeneron):

It seems important to quickly discuss Regeneron, which is currently in phase 3 of their trial with monoclonal antibodies in the treatment of COVID-19. While limited raw data is accessible, this is what I have found so far…

They are using a combination of 2 different monoclonal antibodies as a single infusion. Phases 1 and 2 occurred in mice and hamsters and also suggest a significant decrease in viral load at 3 days after infusion. Phase 3 is currently up to 550 patients enrolled. So far, reported outcomes seem similar to the BLAZE-1 trial, in that there does not seem to be any large difference in viral load between difference doses given, but there is benefit over placebo. Apparent downsides to this study is that it appears to be a prospective trial, and not randomly controlled. This is unfortunate, as it is also industry funded.

The company claims a 57% reduction in repeat medical visits (repeat ER visits or hospitalizations) for all patients and a 71% reduction in those patients with > 1 co-morbidity.

More important to our current knowledge is that they also had an arm looking for benefit in hospitalized patients requiring oxygen. This arm was abruptly stopped last week as they found an INCREASE in harm when used in these patients.

Regardless, early data does support the data we have seen in the BLAZE-1 study. Patients with mild to moderate symptoms who do not meet criteria for hospitalization, are not hypoxic and have 1+ co-morbidities are likely to benefit.