Rahul Ganatra Profile picture
Feb 3 18 tweets 6 min read
1/
Should you use Sotrovimab (SOT) to treat high-risk outpatients with #COVID19?

Spoiler alert: Yes, if you can find it.

Here's #HowIReadThisPaper on the COMET-ICE trial by Gupta et al in @NEJM

nejm.org/doi/full/10.10…

(Thread)
2/
The origin story of SOT is amazing:

It was developed from an antibody in a frozen blood sample from a patient who survived the SARS epidemic of 2003.

It binds to a highly conserved part of the coronavirus spike protein and blocks cell entry.

nature.com/articles/d4158…
3/
Returning to COMET-ICE: what was studied?

Patients were randomized (double-blind) to receive a one-time IV infusion of SOT or placebo.

The primary outcome was the relative reduction in patients hospitalized for >24h or who died from any cause through day 29.
4/
Who was studied?

583 unvaccinated outpatients

> 18 years old

With symptomatic COVID19 (but without hypoxemia)

For <5 days

At high risk for severe disease: >1 of the following risk factors: Age > 55, DM2 requiring treatment, obesity, CKD, CHF, COPD, mod/severe asthma
5/
~90% of patients enrolled in USA

Characteristics and risk factors well-balanced

Median age: 53 years

Most common comorbidities: Age >55, obesity, DM2

Most common variant not reported

% with prior infection not reported

60% of patients had symptom onset <3 days
6/
What were the main findings?

Primary outcome: 85% relative reduction (97.24% CI: 44 - 96)

Absolute risk reduction: 6% (7% vs 1%)

All patients admitted to ICU (5), requiring intubation (2), or who died (1) were in the placebo group.

No concerning safety signals
7/
Another very positive study.

How confident should we be in the conclusions?

Let’s look for sources of chance and bias that could threaten them.

First, the study was stopped for efficacy.

Did this make a positive result more likely by chance?
8/
No - it makes a negative result more likely:

Usually, enrolling fewer people than planned = ↓ power

However, these data suggest a large effect of SOT.

As a result, fewer people than expected were needed to find it.

Here, this increases my confidence in the results.
9/
Another source of confidence in these results:

The secondary outcomes suggest SOT = ↓ emergency department visits, disease progression, ICU admission, and death.

Though the numbers are small, the pattern is in-line with what we expect based on the mechanism.
10/
Other positives:

✅Because the binding site of SOT is highly conserved, it should work against future variants

✅No safety signals, no drug interactions

✅Long half-life (49 days!) = good option for immunosuppressed patients who have received B-cell depleting therapies
11/
Two important things were omitted:

Patients’ autologous antibody status

&

The dominant circulating variant.

Are either of these sources of chance or bias that could have influenced the results?

Let’s first examine antibody positivity.
12/
Seropositivity would indicate one of two things:

Prior infection

Or

Immune response to the current infection.

This would have been a useful subgroup analysis to infer how these data might apply to patients with some immunity from prior infection or vaccination.
13/
It does not appear that patients with prior infection were excluded (only patients with prior hospitalization for COVID were excluded).

How many people could this be? Hard to say. 20% of patients had prior infection in the MOVe-OUT trial:

nejm.org/doi/full/10.10…
14/
Since any degree of prior immunity would likely attenuate the benefit of SOT

And

Since patients with prior infection are likely to be distributed evenly,

This creates a bias towards a negative (null) finding and increases my confidence in these results.
15/
Turning now to the dominant variant:

The study was completed in 3/2021, before the emergence of delta & omicron.

Based on the mechanism of action of SOT, this shouldn’t matter, and it should still be effective.

In vitro studies support this:
biorxiv.org/content/10.110…
16/
Finally, the major downside:

Producing a biologic in large amounts is time-consuming and resource-intensive.

We should expect limited availability.

As of today, the number of doses distributed is <1% of the total reported number of cases in the US:

phe.gov/emergency/even…
17/
Bottom line:

SOT led to a large reduction in hospitalizations, disease progression, and death from #COVID19 through day 29 in high-risk unvaccinated outpatients.

It appears safe and is expected to retain activity against future variants.

(End)
18/
My deepest gratitude to @tony_breu for the thoughtful peer review.

If you haven't already, please read the paper and add your observations below!

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More from @rbganatra

Jan 28
1/
Should we use #remdesivir (RDV) to treat high-risk outpatients with #SARSCoV2 #COVID19?

Here's #HowIReadThisPaper on the PINETREE trial by Gottleib et al in @NEJM

(Thread)

nejm.org/doi/full/10.10…
2/
High-quality evidence suggests RDV shortens time to clinical improvement in hospitalized patients with #COVID19 and hypoxemia (ACTT-1).

Based on this, @NIH recommends RDV in hypoxemic inpatients:

covid19treatmentguidelines.nih.gov/management/cli…

However, its role in treating outpatients is unknown.
3/
What was studied?

Patients were randomized (double-blind) to receive IV RDV or placebo x 3 days

The primary outcome was the composite of COVID-related hospitalization or death from any cause by day 28.
Read 15 tweets
Jan 6
1/
Should we use #molnupiravir (MOV) to treat #SARSCoV2 #COVID19?

With new @NIH treatment guidelines out, it's time to review the evidence behind them.

Here's #HowIReadThisPaper on the MOVe-OUT trial by Bernal et al in @NEJM

(Thread)

nejm.org/doi/full/10.10…
2/
How does this drug work?

MOV is a RNA nucleotide prodrug of n-hydroxycytidine, a cytidine analogue that is a potent mutagen for viruses.

It works by tricking viral RNA polymerase into making errors during replication.

nature.com/articles/s4159…
3/
In which patients was this drug studied?

1,433 unvaccinated outpatients

>18 years old

with symptomatic #COVID19

for <5 days

and at least one risk factor for severe disease:
Read 18 tweets
Nov 28, 2020
1/
My appraisal of the Danish mask study (DANMASK-19): This was a negative trial - masks were not shown to prevent #COVID19.

Could chance or bias make this outcome more likely?
Does this mean we don’t need to wear masks?

Let’s take a deeper look.

#HowIReadThisPaper

(Thread)
2/
Before beginning, if you have not already done so, I implore you - read the paper!

acpjournals.org/doi/10.7326/M2…

Then, come back, and please comment, add what I have missed, and correct me where I am wrong.

Critical appraisal is a group effort.
3/
First, let’s agree on what was tested:

The hypothesis was that the recommendation to wear masks (added to other public health measures) would reduce the incidence of COVID19 among wearers from 2% to 1% over 1 month, in a setting where mask use was uncommon (Denmark).
Read 24 tweets
Jul 25, 2020
1/
#SARSCoV2 #COVID19 got you down? Me too.

Ready for some good news? Here it is: #Dexamethasone (dex) works.

But when, how much, and for which patients?

Here’s #HowIReadThisPaper on Horby et al: the RECOVERY trial prelim report: nejm.org/doi/full/10.10…

(Thread)
2/
Already read the paper, just want the appraisal? Go here:

Haven’t read it yet? Here are the highlights.

Based on my very informal poll, here’s how twitter respondents indicated they are using dex in COVID19 patients as of mid-July 2020:
3/
Background: COVID19 can induce a deadly hyper-inflammatory host response.

Prior observational data (↓quality, ↑risk of confounding by indication) suggested ↑mortality from steroids in influenza: pubmed.ncbi.nlm.nih.gov/30798570/

The role of steroids in treating COVID19 is unknown.
Read 17 tweets
Jul 25, 2020
1/
My appraisal of the RECOVERY trial: This was a (very) positive study.

How could chance or bias affect the validity of these results?
What was missing?
How should we apply these results?

Let’s take a deeper look.

#HowIReadThisPaper
2/
Regarding bias: Strict inclusion/exclusion criteria can introduce selection bias by creating a highly selected study population.

This was NOT so in RECOVERY.

In figure 1, we see that 83% of recruited* patients were ultimately included.

(*assuming “recruited” = “screened”)
3/
Amazingly, ~15% of all patients hospitalized for COVID19 in the UK during the study period were included in this trial.

No other Tx trial for COVID19 even comes close to that level of representation.

→These results should generalize broadly to hospitalized patients.
Read 15 tweets
May 30, 2020
1/
How common is loss of smell (anosmia) in #SARSCoV2 #COVID19, and how useful is it for ruling the diagnosis in or out? Let’s take a look at the data.

Here’s a quick #HowIReadThisPaper on two @AnnalsofEM papers addressing this question:

Chua et al

&

Peyroney et al

(Thread)
2/
First, a question:

Let’s assume you have a limited supply of swabs and need to prioritize which patients to test for COVID19.

In which skilled nursing facility (SNF) setting would you expect anosmia to be more useful in identifying patients who will test positive?
3/
Chua et al annemergmed.com/article/S0196-…

Question: What are the test characteristics of acute olfactory loss (hyposmia or anosmia for <14d) for Dx of COVID19, using oropharyngeal PCR as the gold standard?

Design: single-center cross-sectional study via chart review (retrospective)
Read 17 tweets

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