Top
Overview
Introduction
Variant Dependence
Results
RCTs
Exclusions
Heterogeneity
Discussion
Perspective
Conclusion
 
Study Notes
Methods and Data
Supplementary
References
 
All studies
Mortality
Ventilation
ICU admission
Hospitalization
Progression
Recovery
COVID‑19 cases
Viral clearance
Peer reviewed
Exclusions
All RCTs
RCT mortality
 
Feedback
Home
c19early.org COVID-19 treatment researchCasirivimab/imdevimabCasirivimab/i.. (more..)
Melatonin Meta
Metformin Meta
Azvudine Meta
Bromhexine Meta Molnupiravir Meta
Budesonide Meta
Colchicine Meta
Conv. Plasma Meta Nigella Sativa Meta
Curcumin Meta Nitazoxanide Meta
Famotidine Meta Paxlovid Meta
Favipiravir Meta Quercetin Meta
Fluvoxamine Meta Remdesivir Meta
Hydroxychlor.. Meta Thermotherapy Meta
Ivermectin Meta

Loading...
More

Casirivimab/imdevimab for COVID-19: real-time meta analysis of 27 studies

@CovidAnalysis, March 2024, Version 44V44
 
0 0.5 1 1.5+ All studies 52% 27 58,886 Improvement, Studies, Patients Relative Risk Mortality 40% 8 32,929 Ventilation -1% 3 10,248 ICU admission 53% 3 9,896 Hospitalization 42% 12 46,106 Progression 56% 3 680 Recovery 33% 5 8,277 Cases 80% 4 3,265 Viral clearance 55% 2 1,709 RCTs 61% 9 21,306 RCT mortality 20% 3 15,162 Peer-reviewed 43% 17 43,746 Prophylaxis 93% 3 3,061 Early 47% 21 42,887 Late 33% 3 12,938 Casirivimab/imdevimab for COVID-19 c19early.org March 2024 after exclusions Favorscasirivimab/im.. Favorscontrol
Abstract
Statistically significant lower risk is seen for mortality, hospitalization, progression, recovery, cases, and viral clearance. 20 studies from 14 independent teams in 4 countries show statistically significant improvements.
Meta analysis using the most serious outcome reported shows 52% [34‑65%] lower risk. Results are similar for Randomized Controlled Trials, higher quality studies, and peer-reviewed studies.
Results are robust — in exclusion sensitivity analysis 13 of 27 studies must be excluded to avoid finding statistically significant efficacy in pooled analysis.
Efficacy is variant dependent. In Vitro studies suggest a lack of efficacy for many omicron variants Haars, Liu, Pochtovyi, Sheward, Tatham, VanBlargan. ADE shown In Vitro Shimizu. mAb use may create new variants that spread globally Focosi, Leducq, and may be associated with prolonged viral loads, clinical deterioration, and immune escape Choudhary, Günther, Leducq.
Prescription treatments have been preferentially used by patients at lower risk Wilcock. Retrospective studies may overestimate efficacy, for example patients with greater knowledge of effective treatments may be more likely to access prescription treatments but result in confounding because they are also more likely to use known beneficial non-prescription treatments.
No treatment or intervention is 100% effective. All practical, effective, and safe means should be used based on risk/benefit analysis. Multiple treatments are typically used in combination, and other treatments may be more effective.
All data to reproduce this paper and sources are in the appendix. Wicaksono present another meta analysis for casirivimab/imdevimab, showing significant improvements for mortality, hospital discharge, progression, and viral clearance.
Evolution of COVID-19 clinical evidence Casirivimab/imdevimab p=0.0000087 Acetaminophen p=0.00000029 2020 2021 2022 2023 Effective Harmful c19early.org March 2024 meta analysis results (pooled effects) 100% 50% 0% -50%
Highlights
Casirivimab/imdevimab reduces risk for COVID-19 with very high confidence for hospitalization, progression, recovery, and in pooled analysis, high confidence for mortality and ICU admission, and low confidence for cases and viral clearance. Efficacy is variant dependent.
Casirivimab/imdevimab was the 17th treatment shown effective with ≥3 clinical studies in March 2021, now with p = 0.0000087 from 27 studies, and recognized in 42 countries.
We show traditional outcome specific analyses and combined evidence from all studies, incorporating treatment delay, a primary confounding factor in COVID-19 studies.
Real-time updates and corrections, transparent analysis with all results in the same format, consistent protocol for 66 treatments.
A
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ Regeneron (RCT) 38% 0.62 [0.29-1.33] recov. time 92 (n) 91 (n) Improvement, RR [CI] Treatment Control Regeneron (RCT) 71% 0.29 [0.17-0.48] death/hosp. 18/1,355 62/1,341 Weinreich (RCT) 50% 0.50 [0.09-2.72] death 2/2,091 4/2,089 Webb 98% 0.0 [0.00-2e+05] death 0/115 57/5,536 Cooper 77% 0.23 [0.03-1.65] death 1/1,148 33/8,534 Kakinoki 58% 0.42 [0.17-0.92] progression 13/55 22/53 Komagamine 77% 0.23 [0.01-4.63] ventilation 0/53 2/75 Suzuki (PSM) -200% 3.00 [0.12-73.3] death 1/222 0/222 O'Brien (DB RCT) 85% 0.15 [0.01-2.78] hosp. 0/100 3/104 Shopen -46% 1.46 [0.73-2.67] severe case 24/116 26/243 Osugi 24% 0.76 [0.23-2.49] hosp. 4/30 15/74 Wei 61% 0.39 [0.26-0.60] death/hosp. 23/1,116 27/5,291 Wilden 82% 0.18 [0.05-0.50] hosp. n/a n/a Faraone 92% 0.08 [0.01-0.83] death 0/11 8/23 Miyashita 33% 0.67 [0.11-3.97] ventilation 2/461 3/461 Levey 31% 0.69 [0.07-7.37] ICU 1/36 2/50 Kneidinger 97% 0.03 [0.00-264] severe case 0/3 34/215 Williams -21% 1.21 [0.14-9.86] oxygen 1/88 6/676 Gershengorn -95% 1.95 [0.86-4.18] hosp. 369 (n) 5,915 (n) Hussein (PSM) 60% 0.40 [0.38-0.42] death/hosp. population-based cohort Kip 46% 0.54 [0.41-0.71] death/hosp. 61/1,479 227/2,954 Tau​2 = 0.15, I​2 = 64.4%, p < 0.0001 Early treatment 47% 0.53 [0.40-0.71] 151/8,940 531/33,947 47% lower risk Horby (RCT) 6% 0.94 [0.86-1.02] death 943/4,839 1,029/4,946 Improvement, RR [CI] Treatment Control Somersa.. (DB RCT) 36% 0.64 [0.44-0.93] death 59/804 45/393 McCreary (PSM) 93% 0.07 [0.01-0.51] death 1/652 29/1,304 Tau​2 = 0.15, I​2 = 80.8%, p = 0.16 Late treatment 33% 0.67 [0.39-1.17] 1,003/6,295 1,103/6,643 33% lower risk Regeneron (RCT) 94% 0.06 [0.01-0.50] symp. case 0/186 8/223 Improvement, RR [CI] Treatment Control Regeneron (DB RCT) 92% 0.08 [0.01-0.79] hosp. 0/841 6/842 Isa (DB RCT) 93% 0.07 [0.01-0.28] symp. case 3/729 13/240 Tau​2 = 0.00, I​2 = 0.0%, p < 0.0001 Prophylaxis 93% 0.07 [0.03-0.21] 3/1,756 27/1,305 93% lower risk All studies 52% 0.48 [0.35-0.66] 1,157/16,991 1,661/41,895 52% lower risk 27 casirivimab/imdevimab COVID-19 studies c19early.org March 2024 Tau​2 = 0.32, I​2 = 93.0%, p < 0.0001 Effect extraction pre-specified(most serious outcome, see appendix) Favors casirivimab/im.. Favors control
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ Regeneron (RCT) 38% recovery Improvement Relative Risk [CI] Regeneron (RCT) 71% death/hosp. Weinreich (RCT) 50% death Webb 98% death Cooper 77% death Kakinoki 58% progression Komagamine 77% ventilation Suzuki (PSM) -200% death O'Brien (DB RCT) 85% hospitalization Shopen -46% severe case Osugi 24% hospitalization Wei 61% death/hosp. Wilden 82% hospitalization Faraone 92% death Miyashita 33% ventilation Levey 31% ICU admission Kneidinger 97% severe case Williams -21% oxygen therapy Gershengorn -95% hospitalization Hussein (PSM) 60% death/hosp. Kip 46% death/hosp. Tau​2 = 0.15, I​2 = 64.4%, p < 0.0001 Early treatment 47% 47% lower risk Horby (RCT) 6% death Somers.. (DB RCT) 36% death McCreary (PSM) 93% death Tau​2 = 0.15, I​2 = 80.8%, p = 0.16 Late treatment 33% 33% lower risk Regeneron (RCT) 94% symp. case Regeneron (DB RCT) 92% hospitalization Isa (DB RCT) 93% symp. case Tau​2 = 0.00, I​2 = 0.0%, p < 0.0001 Prophylaxis 93% 93% lower risk All studies 52% 52% lower risk 27 casirivimab/imdevimab C19 studies c19early.org March 2024 Tau​2 = 0.32, I​2 = 93.0%, p < 0.0001 Effect extraction pre-specifiedRotate device for details Favors casirivimab/im.. Favors control
B
Loading..
Figure 1. A. Random effects meta-analysis. This plot shows pooled effects, see the specific outcome analyses for individual outcomes, and the heterogeneity section for discussion. Effect extraction is pre-specified, using the most serious outcome reported. For details see the appendix. B. Timeline of results in casirivimab/imdevimab studies. The marked dates indicate the time when efficacy was known with a statistically significant improvement of ≥10% from ≥3 studies for pooled outcomes, one or more specific outcome, and pooled outcomes in RCTs. Efficacy based on specific outcomes was delayed by 7.6 months, compared to using pooled outcomes.
SARS-CoV-2 infection primarily begins in the upper respiratory tract and may progress to the lower respiratory tract, other tissues, and the nervous and cardiovascular systems, which may lead to cytokine storm, pneumonia, ARDS, neurological issues Duloquin, Hampshire, Scardua-Silva, Yang, cardiovascular complications Eberhardt, organ failure, and death. Minimizing replication as early as possible is recommended.
SARS-CoV-2 infection and replication involves the complex interplay of 50+ host and viral proteins and other factors Note A, Malone, Murigneux, Lv, Lui, Niarakis, providing many therapeutic targets for which many existing compounds have known activity. Scientists have predicted that over 7,000 compounds may reduce COVID-19 risk c19early.org, either by directly minimizing infection or replication, by supporting immune system function, or by minimizing secondary complications.
We analyze all significant controlled studies of casirivimab/imdevimab for COVID-19. Search methods, inclusion criteria, effect extraction criteria (more serious outcomes have priority), all individual study data, PRISMA answers, and statistical methods are detailed in Appendix 1. We present random effects meta-analysis results for all studies, studies within each treatment stage, individual outcomes, peer-reviewed studies, Randomized Controlled Trials (RCTs), and higher quality studies.
Figure 2 shows stages of possible treatment for COVID-19. Prophylaxis refers to regularly taking medication before becoming sick, in order to prevent or minimize infection. Early Treatment refers to treatment immediately or soon after symptoms appear, while Late Treatment refers to more delayed treatment.
Figure 2. Treatment stages.
Efficacy for monoclonal antibodies is typically variant dependent. Table 1 shows efficacy by variant for several monoclonal antibodies.
Table 1. Predicted efficacy by variant from Davis (not updated for more recent variants).    : likely effective    : likely ineffective    : unknown. Submit updates.
Bamlanivimab/
etesevimab
Casirivimab/
imdevimab
Sotrovimab Bebtelovimab Tixagevimab/
cilgavimab
Alpha B.1.1.7
Beta/ ​Gamma BA1.351/ ​P.1
Delta B.1.617.2
Omicron BA.1/ ​BA.1.1
Omicron BA.2
Omicron BA.5
Omicron BA.4.6
Omicron BQ.1.1
Table 2 summarizes the results for all stages combined, for Randomized Controlled Trials, for peer-reviewed studies, after exclusions, and for specific outcomes. Table 3 shows results by treatment stage. Figure 3 plots individual results by treatment stage. Figure 4, 5, 6, 7, 8, 9, 10, 11, 12, and 13 show forest plots for random effects meta-analysis of all studies with pooled effects, mortality results, ventilation, ICU admission, hospitalization, progression, recovery, cases, viral clearance, and peer reviewed studies.
Table 2. Random effects meta-analysis for all stages combined, for Randomized Controlled Trials, for peer-reviewed studies, after exclusions, and for specific outcomes. Results show the percentage improvement with treatment and the 95% confidence interval. * p<0.05  ** p<0.01  *** p<0.001  **** p<0.0001.
Improvement Studies Patients Authors
All studies52% [34‑65%]
****
27 58,886 402
After exclusions53% [36‑66%]
****
24 42,920 378
Peer-reviewed studiesPeer-reviewed43% [15‑61%]
**
17 43,746 260
Randomized Controlled TrialsRCTs61% [32‑78%]
***
9 21,306 178
Mortality40% [1‑64%]
*
8 32,929 216
VentilationVent.-1% [-13‑11%]3 10,248 42
ICU admissionICU53% [-0‑78%]
*
3 9,896 19
HospitalizationHosp.42% [17‑59%]
**
12 46,106 133
Recovery33% [22‑43%]
****
5 8,277 76
Cases80% [39‑93%]
**
4 3,265 71
Viral55% [13‑76%]
*
2 1,709 39
RCT mortality20% [-11‑42%]3 15,162 105
Table 3. Random effects meta-analysis results by treatment stage. Results show the percentage improvement with treatment, the 95% confidence interval, and the number of studies for the stage.treatment and the 95% confidence interval. * p<0.05  ** p<0.01  *** p<0.001  **** p<0.0001.
Early treatment Late treatment Prophylaxis
All studies47% [29‑60%]
****
33% [-17‑61%]93% [79‑97%]
****
After exclusions49% [29‑63%]
****
33% [-17‑61%]93% [79‑97%]
****
Peer-reviewed studiesPeer-reviewed49% [31‑62%]
****
19% [-17‑44%]
Randomized Controlled TrialsRCTs63% [42‑76%]
****
19% [-17‑44%]93% [79‑97%]
****
Mortality65% [-6‑88%]33% [-17‑61%]
VentilationVent.50% [-134‑89%]-1% [-14‑10%]
ICU admissionICU53% [-0‑78%]
*
HospitalizationHosp.39% [9‑59%]
*
48% [18‑67%]
**
92% [21‑99%]
*
Recovery29% [19‑37%]
****
30% [6‑48%]
*
62% [39‑77%]
***
Cases33% [2‑57%]
*
85% [74‑91%]
****
Viral40% [19‑55%]
**
69% [45‑83%]
****
RCT mortality50% [-172‑91%]19% [-17‑44%]
Loading..
Figure 3. Scatter plot showing the most serious outcome in all studies, and for studies within each stage. Diamonds shows the results of random effects meta-analysis.
Loading..
Loading..
Figure 4. Random effects meta-analysis for all studies with pooled effects. This plot shows pooled effects, see the specific outcome analyses for individual outcomes, and the heterogeneity section for discussion. Effect extraction is pre-specified, using the most serious outcome reported. For details see the appendix.
Loading..
Loading..
Figure 5. Random effects meta-analysis for mortality results.
Loading..
Figure 6. Random effects meta-analysis for ventilation.
Loading..
Figure 7. Random effects meta-analysis for ICU admission.
Loading..
Figure 8. Random effects meta-analysis for hospitalization.
Loading..
Figure 9. Random effects meta-analysis for progression.
Loading..
Figure 10. Random effects meta-analysis for recovery.
Loading..
Figure 11. Random effects meta-analysis for cases.
Loading..
Figure 12. Random effects meta-analysis for viral clearance.
Loading..
Figure 13. Random effects meta-analysis for peer reviewed studies. Effect extraction is pre-specified, using the most serious outcome reported, see the appendix for details. Zeraatkar et al. analyze 356 COVID-19 trials, finding no significant evidence that preprint results are inconsistent with peer-reviewed studies. They also show extremely long peer-review delays, with a median of 6 months to journal publication. A six month delay was equivalent to around 1.5 million deaths during the first two years of the pandemic. Authors recommend using preprint evidence, with appropriate checks for potential falsified data, which provides higher certainty much earlier. Davidson et al. also showed no important difference between meta analysis results of preprints and peer-reviewed publications for COVID-19, based on 37 meta analyses including 114 trials.
Figure 14 shows a comparison of results for RCTs and non-RCT studies. Random effects meta analysis of RCTs shows 61% improvement, compared to 45% for other studies. Figure 15 and 16 show forest plots for random effects meta-analysis of all Randomized Controlled Trials and RCT mortality results. RCT results are included in Table 2 and Table 3.
Loading..
Figure 14. Results for RCTs and non-RCT studies.
Loading..
Figure 15. Random effects meta-analysis for all Randomized Controlled Trials. This plot shows pooled effects, see the specific outcome analyses for individual outcomes, and the heterogeneity section for discussion. Effect extraction is pre-specified, using the most serious outcome reported. For details see the appendix.
Loading..
Figure 16. Random effects meta-analysis for RCT mortality results.
Bias in clinical research may be defined as something that tends to make conclusions differ systematically from the truth. RCTs help to make study groups more similar and can provide a higher level of evidence, however they are subject to many biases Jadad, and analysis of double-blind RCTs has identified extreme levels of bias Gøtzsche. For COVID-19, the overhead may delay treatment, dramatically compromising efficacy; they may encourage monotherapy for simplicity at the cost of efficacy which may rely on combined or synergistic effects; the participants that sign up may not reflect real world usage or the population that benefits most in terms of age, comorbidities, severity of illness, or other factors; standard of care may be compromised and unable to evolve quickly based on emerging research for new diseases; errors may be made in randomization and medication delivery; and investigators may have hidden agendas or vested interests influencing design, operation, analysis, reporting, and the potential for fraud. All of these biases have been observed with COVID-19 RCTs. There is no guarantee that a specific RCT provides a higher level of evidence.
RCTs are expensive and many RCTs are funded by pharmaceutical companies or interests closely aligned with pharmaceutical companies. For COVID-19, this creates an incentive to show efficacy for patented commercial products, and an incentive to show a lack of efficacy for inexpensive treatments. The bias is expected to be significant, for example Als-Nielsen et al. analyzed 370 RCTs from Cochrane reviews, showing that trials funded by for-profit organizations were 5 times more likely to recommend the experimental drug compared with those funded by nonprofit organizations. For COVID-19, some major philanthropic organizations are largely funded by investments with extreme conflicts of interest for and against specific COVID-19 interventions.
High quality RCTs for novel acute diseases are more challenging, with increased ethical issues due to the urgency of treatment, increased risk due to enrollment delays, and more difficult design with a rapidly evolving evidence base. For COVID-19, the most common site of initial infection is the upper respiratory tract. Immediate treatment is likely to be most successful and may prevent or slow progression to other parts of the body. For a non-prophylaxis RCT, it makes sense to provide treatment in advance and instruct patients to use it immediately on symptoms, just as some governments have done by providing medication kits in advance. Unfortunately, no RCTs have been done in this way. Every treatment RCT to date involves delayed treatment. Among the 66 treatments we have analyzed, 63% of RCTs involve very late treatment 5+ days after onset. No non-prophylaxis COVID-19 RCTs match the potential real-world use of early treatments. They may more accurately represent results for treatments that require visiting a medical facility, e.g., those requiring intravenous administration.
Evidence shows that non-RCT trials can also provide reliable results. Concato et al. found that well-designed observational studies do not systematically overestimate the magnitude of the effects of treatment compared to RCTs. Anglemyer et al. summarized reviews comparing RCTs to observational studies and found little evidence for significant differences in effect estimates. Lee et al. showed that only 14% of the guidelines of the Infectious Diseases Society of America were based on RCTs. Evaluation of studies relies on an understanding of the study and potential biases. Limitations in an RCT can outweigh the benefits, for example excessive dosages, excessive treatment delays, or Internet survey bias may have a greater effect on results. Ethical issues may also prevent running RCTs for known effective treatments. For more on issues with RCTs see Deaton, Nichol.
Currently, 44 of the treatments we analyze show statistically significant efficacy or harm, defined as ≥10% decreased risk or >0% increased risk from ≥3 studies. Of the 44 treatments with statistically significant efficacy/harm, 28 have been confirmed in RCTs, with a mean delay of 5.7 months. When considering only low cost treatments, 23 have been confirmed with a delay of 6.9 months. For the 16 unconfirmed treatments, 3 have zero RCTs to date. The point estimates for the remaining 13 are all consistent with the overall results (benefit or harm), with 10 showing >20%. The only treatments showing >10% efficacy for all studies, but <10% for RCTs are sotrovimab and aspirin.
We need to evaluate each trial on its own merits. RCTs for a given medication and disease may be more reliable, however they may also be less reliable. For off-patent medications, very high conflict of interest trials may be more likely to be RCTs, and more likely to be large trials that dominate meta analyses.
To avoid bias in the selection of studies, we analyze all non-retracted studies. Here we show the results after excluding studies with major issues likely to alter results, non-standard studies, and studies where very minimal detail is currently available. Our bias evaluation is based on analysis of each study and identifying when there is a significant chance that limitations will substantially change the outcome of the study. We believe this can be more valuable than checklist-based approaches such as Cochrane GRADE, which can be easily influenced by potential bias, may ignore or underemphasize serious issues not captured in the checklists, and may overemphasize issues unlikely to alter outcomes in specific cases (for example certain specifics of randomization with a very large effect size and well-matched baseline characteristics).
The studies excluded are as below. Figure 17 shows a forest plot for random effects meta-analysis of all studies after exclusions.
Cooper, unadjusted results with no group details.
Gershengorn, substantial unadjusted confounding by indication possible.
Hussein, substantial unadjusted confounding by indication possible.
Loading..
Figure 17. Random effects meta-analysis for all studies after exclusions. This plot shows pooled effects, see the specific outcome analyses for individual outcomes, and the heterogeneity section for discussion. Effect extraction is pre-specified, using the most serious outcome reported. For details see the appendix.
Heterogeneity in COVID-19 studies arises from many factors including:
The time between infection or the onset of symptoms and treatment may critically affect how well a treatment works. For example an antiviral may be very effective when used early but may not be effective in late stage disease, and may even be harmful. Oseltamivir, for example, is generally only considered effective for influenza when used within 0-36 or 0-48 hours McLean, Treanor. Baloxavir studies for influenza also show that treatment delay is critical — Ikematsu et al. report an 86% reduction in cases for post-exposure prophylaxis, Hayden et al. show a 33 hour reduction in the time to alleviation of symptoms for treatment within 24 hours and a reduction of 13 hours for treatment within 24-48 hours, and Kumar et al. report only 2.5 hours improvement for inpatient treatment.
Table 4. Studies of baloxavir for influenza show that early treatment is more effective.
Treatment delayResult
Post exposure prophylaxis86% fewer cases Ikematsu
<24 hours-33 hours symptoms Hayden
24-48 hours-13 hours symptoms Hayden
Inpatients-2.5 hours to improvement Kumar
Figure 18 shows a mixed-effects meta-regression of efficacy as a function of treatment delay in COVID-19 casirivimab/imdevimab studies. For comparison, Figure 19 shows a meta-regression for all studies providing specific values across 66 treatments. Efficacy declines rapidly with treatment delay. Early treatment is critical for COVID-19.
Loading..
Figure 19. Early treatment is more effective. Meta-regression showing efficacy as a function of treatment delay in COVID-19 casirivimab/imdevimab studies.
Loading..
Figure 19. Early treatment is more effective. Meta-regression showing efficacy as a function of treatment delay in COVID-19 studies from 66 treatments.
Details of the patient population including age and comorbidities may critically affect how well a treatment works. For example, many COVID-19 studies with relatively young low-comorbidity patients show all patients recovering quickly with or without treatment. In such cases, there is little room for an effective treatment to improve results (as in López-Medina et al.).
Efficacy may differ significantly depending on the effect measured, for example a treatment may be very effective at reducing mortality, but less effective at minimizing cases or hospitalization. Or a treatment may have no effect on viral clearance while still being effective at reducing mortality.
Efficacy may depend critically on the distribution of SARS-CoV-2 variants encountered by patients. Risk varies significantly across variants Korves, for example the Gamma variant shows significantly different characteristics Faria, Karita, Nonaka, Zavascki. Different mechanisms of action may be more or less effective depending on variants, for example the degree to which TMPRSS2 contributes to viral entry can differ across variants Peacock, Willett.
Effectiveness may depend strongly on the dosage and treatment regimen.
The use of other treatments may significantly affect outcomes, including supplements, other medications, or other kinds of treatment such as prone positioning. Treatments may be synergistic Alsaidi, Andreani, De Forni, Fiaschi, Jeffreys, Jitobaom, Jitobaom (B), Ostrov, Said, Thairu, Wan, therefore efficacy may depend strongly on combined treatments.
The quality of medications may vary significantly between manufacturers and production batches, which may significantly affect efficacy and safety. Williams et al. analyze ivermectin from 11 different sources, showing highly variable antiparasitic efficacy across different manufacturers. Xu et al. analyze a treatment from two different manufacturers, showing 9 different impurities, with significantly different concentrations for each manufacturer.
We present both pooled analyses and specific outcome analyses. Notably, pooled analysis often results in earlier detection of efficacy as shown in Figure 20. For many COVID-19 treatments, a reduction in mortality logically follows from a reduction in hospitalization, which follows from a reduction in symptomatic cases, etc. An antiviral tested with a low-risk population may report zero mortality in both arms, however a reduction in severity and improved viral clearance may translate into lower mortality among a high-risk population, and including these results in pooled analysis allows faster detection of efficacy. Trials with high-risk patients may also be restricted due to ethical concerns for treatments that are known or expected to be effective.
Pooled analysis enables using more of the available information. While there is much more information available, for example dose-response relationships, the advantage of the method used here is simplicity and transparency. Note that pooled analysis could hide efficacy, for example a treatment that is beneficial for late stage patients but has no effect on viral replication or early stage disease could show no efficacy in pooled analysis if most studies only examine viral clearance. While we present pooled results, we also present individual outcome analyses, which may be more informative for specific use cases.
Currently, 44 of the treatments we analyze show statistically significant efficacy or harm, defined as ≥10% decreased risk or >0% increased risk from ≥3 studies. 85% of treatments showing statistically significant efficacy/harm with pooled effects have been confirmed with one or more specific outcomes, with a mean delay of 3.7 months. When restricting to RCTs only, 50% of treatments showing statistically significant efficacy/harm with pooled effects have been confirmed with one or more specific outcomes, with a mean delay of 6.1 months.
Loading..
Loading..
Figure 20. The time when studies showed that treatments were effective, defined as statistically significant improvement of ≥10% from ≥3 studies. Pooled results typically show efficacy earlier than specific outcome results. Results from all studies often shows efficacy much earlier than when restricting to RCTs. Results reflect conditions as used in trials to date, these depend on the population treated, treatment delay, and treatment regimen.
The distribution of studies will alter the outcome of a meta analysis. Consider a simplified example where everything is equal except for the treatment delay, and effectiveness decreases to zero or below with increasing delay. If there are many studies using very late treatment, the outcome may be negative, even though early treatment is very effective. This may have a greater effect than pooling different outcomes such as mortality and hospitalization. For example a treatment may have 50% efficacy for mortality but only 40% for hospitalization when used within 48 hours. However efficacy could be 0% when used late.
All meta analyses combine heterogeneous studies, varying in population, variants, and potentially all factors above, and therefore may obscure efficacy by including studies where treatment is less effective. Generally, we expect the estimated effect size from meta analysis to be less than that for the optimal case. Looking at all studies is valuable for providing an overview of all research, important to avoid cherry-picking, and informative when a positive result is found despite combining less-optimal situations. However, the resulting estimate does not apply to specific cases such as early treatment in high-risk populations. While we present results for all studies, we also present treatment time and individual outcome analyses, which may be more informative for specific use cases.
Wilcock et al. show that COVID-19 prescription treatments have been preferentially used by patients at lower risk. Retrospective studies may overestimate efficacy, and data for accurate adjustment may not be available. For example, patients with greater knowledge of effective treatments may be more likely to access prescription treatments but result in confounding because they are also more likely to use known beneficial non-prescription treatments.
Publishing is often biased towards positive results. Trials with patented drugs may have a financial conflict of interest that results in positive studies being more likely to be published, or bias towards more positive results. For example with molnupiravir, trials with negative results remain unpublished to date (CTRI/2021/05/033864 and CTRI/2021/08/0354242).
One method to evaluate bias is to compare prospective vs. retrospective studies. Prospective studies are more likely to be published regardless of the result, while retrospective studies are more likely to exhibit bias. For example, researchers may perform preliminary analysis with minimal effort and the results may influence their decision to continue. Retrospective studies also provide more opportunities for the specifics of data extraction and adjustments to influence results.
Figure 21 shows a scatter plot of results for prospective and retrospective studies. Prospective studies show 65% [39‑80%] improvement in meta analysis, compared to 42% [19‑59%] for retrospective studies, suggesting possible negative publication bias, with a non-significant trend towards retrospective studies reporting lower efficacy. However, many of the prospective studies for casirivimab/imdevimab have very high conflict of interest, which could also explain the improved results.
Loading..
Figure 21. Prospective vs. retrospective studies. The diamonds show the results of random effects meta-analysis.
Studies for casirivimab/imdevimab were primarily for early treatment, in contrast with typical low cost treatments that were mostly tested with late treatment.
Figure 22. Patented treatments received mostly early treatment studies, while low cost treatments were typically tested for late treatment.
Funnel plots have traditionally been used for analyzing publication bias. This is invalid for COVID-19 acute treatment trials — the underlying assumptions are invalid, which we can demonstrate with a simple example. Consider a set of hypothetical perfect trials with no bias. Figure 23 plot A shows a funnel plot for a simulation of 80 perfect trials, with random group sizes, and each patient's outcome randomly sampled (10% control event probability, and a 30% effect size for treatment). Analysis shows no asymmetry (p > 0.05). In plot B, we add a single typical variation in COVID-19 treatment trials — treatment delay. Consider that efficacy varies from 90% for treatment within 24 hours, reducing to 10% when treatment is delayed 3 days. In plot B, each trial's treatment delay is randomly selected. Analysis now shows highly significant asymmetry, p < 0.0001, with six variants of Egger's test all showing p < 0.05 Egger, Harbord, Macaskill, Moreno, Peters, Rothstein, Rücker, Stanley. Note that these tests fail even though treatment delay is uniformly distributed. In reality treatment delay is more complex — each trial has a different distribution of delays across patients, and the distribution across trials may be biased (e.g., late treatment trials may be more common). Similarly, many other variations in trials may produce asymmetry, including dose, administration, duration of treatment, differences in SOC, comorbidities, age, variants, and bias in design, implementation, analysis, and reporting.
Figure 23. Example funnel plot analysis for simulated perfect trials.
Summary statistics from meta analysis necessarily lose information. As with all meta analyses, studies are heterogeneous, with differences in treatment delay, treatment regimen, patient demographics, variants, conflicts of interest, standard of care, and other factors. We provide analyses by specific outcomes and by treatment delay, and we aim to identify key characteristics in the forest plots and summaries. Results should be viewed in the context of study characteristics.
Some analyses classify treatment based on early or late administration, as done here, while others distinguish between mild, moderate, and severe cases. Viral load does not indicate degree of symptoms — for example patients may have a high viral load while being asymptomatic. With regard to treatments that have antiviral properties, timing of treatment is critical — late administration may be less helpful regardless of severity.
Details of treatment delay per patient is often not available. For example, a study may treat 90% of patients relatively early, but the events driving the outcome may come from 10% of patients treated very late. Our 5 day cutoff for early treatment may be too conservative, 5 days may be too late in many cases.
Comparison across treatments is confounded by differences in the studies performed, for example dose, variants, and conflicts of interest. Trials affiliated with special interests may use designs better suited to the preferred outcome.
In some cases, the most serious outcome has very few events, resulting in lower confidence results being used in pooled analysis, however the method is simpler and more transparent. This is less critical as the number of studies increases. Restriction to outcomes with sufficient power may be beneficial in pooled analysis and improve accuracy when there are few studies, however we maintain our pre-specified method to avoid any retrospective changes.
Studies show that combinations of treatments can be highly synergistic and may result in many times greater efficacy than individual treatments alone Alsaidi, Andreani, De Forni, Fiaschi, Jeffreys, Jitobaom, Jitobaom (B), Ostrov, Said, Thairu, Wan. Therefore standard of care may be critical and benefits may diminish or disappear if standard of care does not include certain treatments.
This real-time analysis is constantly updated based on submissions. Accuracy benefits from widespread review and submission of updates and corrections from reviewers. Less popular treatments may receive fewer reviews.
No treatment, vaccine, or intervention is 100% available and effective for all current and future variants. Efficacy may vary significantly with different variants and within different populations. All treatments have potential side effects. Propensity to experience side effects may be predicted in advance by qualified physicians. We do not provide medical advice. Before taking any medication, consult a qualified physician who can compare all options, provide personalized advice, and provide details of risks and benefits based on individual medical history and situations.
Wicaksono present another meta analysis for casirivimab/imdevimab, showing significant improvements for mortality, hospital discharge, progression, and viral clearance.
Focosi (B) et al. present a review covering casirivimab/imdevimab for COVID-19.
SARS-CoV-2 infection and replication involves a complex interplay of 50+ host and viral proteins and other factors Lui, Lv, Malone, Murigneux, Niarakis, providing many therapeutic targets. Over 7,000 compounds have been predicted to reduce COVID-19 risk, either by directly minimizing infection or replication, by supporting immune system function, or by minimizing secondary complications. Figure 24 shows an overview of the results for casirivimab/imdevimab in the context of multiple COVID-19 treatments, and Figure 25 shows a plot of efficacy vs. cost for COVID-19 treatments.
Loading..
Figure 24. Scatter plot showing results within the context of multiple COVID-19 treatments. Diamonds shows the results of random effects meta-analysis. 0.6% of 7,095 proposed treatments show efficacy c19early.org (B).
Loading..
Loading..
Figure 25. Efficacy vs. cost for COVID-19 treatments.
Casirivimab/imdevimab is an effective treatment for COVID-19. Statistically significant lower risk is seen for mortality, hospitalization, progression, recovery, cases, and viral clearance. 20 studies from 14 independent teams in 4 countries show statistically significant improvements. Meta analysis using the most serious outcome reported shows 52% [34‑65%] lower risk. Results are similar for Randomized Controlled Trials, higher quality studies, and peer-reviewed studies. Results are robust — in exclusion sensitivity analysis 13 of 27 studies must be excluded to avoid finding statistically significant efficacy in pooled analysis.
Efficacy is variant dependent. In Vitro studies suggest a lack of efficacy for many omicron variants Haars, Liu, Pochtovyi, Sheward, Tatham, VanBlargan. ADE shown In Vitro Shimizu. mAb use may create new variants that spread globally Focosi, Leducq, and may be associated with prolonged viral loads, clinical deterioration, and immune escape Choudhary, Günther, Leducq.
Wicaksono present another meta analysis for casirivimab/imdevimab, showing significant improvements for mortality, hospital discharge, progression, and viral clearance.
Prescription treatments have been preferentially used by patients at lower risk Wilcock. Retrospective studies may overestimate efficacy, for example patients with greater knowledge of effective treatments may be more likely to access prescription treatments but result in confounding because they are also more likely to use known beneficial non-prescription treatments.
0 0.5 1 1.5 2+ Mortality 77% unadjusted Improvement Relative Risk ICU admission 48% unadjusted Hospitalization 52% unadjusted Casirivimab/i..  Cooper et al.  EARLY TREATMENT Is early treatment with casirivimab/imdevimab beneficial for COVID-19? Retrospective 9,682 patients in the USA Lower hospitalization with casirivimab/imdevimab (p<0.000001) c19early.org Cooper et al., Open Forum Infectious D.., Oct 2021 Favors casirivimab/im.. Favors control
Cooper: Retrospective 2,879 patients and matched controls in the USA, showing significantly lower mortality and hospitalization with bamlanivimab, bamlanivimab/etesevimab, and casirivimab/imdevimab. There was significantly lower hospitalization with casirivimab/imdevimab compared to bamlanivimab or bamlanivimab/etesevimab. PSM and multivariate analysis is only provided for all treatments combined.
0 0.5 1 1.5 2+ Mortality 92% Improvement Relative Risk Oxygen therapy 94% Casirivimab/i..  Faraone et al.  EARLY TREATMENT Is early treatment with casirivimab/imdevimab beneficial for COVID-19? Retrospective 34 patients in Italy (October 2020 - April 2021) Lower mortality (p=0.034) and lower oxygen therapy (p=0.017) c19early.org Faraone et al., Research Square, May 2022 Favors casirivimab/im.. Favors control
Faraone: Retrospective 34 patients with hospital-acquired COVID-19, showing lower mortality and oxygen requirements with early casirivimab/imdevimab treatment.
0 0.5 1 1.5 2+ Hospitalization, MV -95% Improvement Relative Risk Hospitalization, PSM -105% Hospitalization, delta -100% Hospitalization, omicron -111% Casirivimab/i..  Gershengorn et al.  EARLY TREATMENT Is early treatment with casirivimab/imdevimab beneficial for COVID-19? Retrospective 6,284 patients in the USA Higher hospitalization with casirivimab/imdevimab (not stat. sig., p=0.09) c19early.org Gershengorn et al., PLOS ONE, December 2022 Favors casirivimab/im.. Favors control
Gershengorn: Retrospective 2,083 outpatients in the USA, showing higher risk of hospitalization with casirivimab/imdevimab, without statistical significance. There may be significant unadjusted confounding by indication.
0 0.5 1 1.5 2+ Mortality 6% Improvement Relative Risk Ventilation -1% Mortality (b) 21% Ventilation (b) 13% Casirivimab/i..  Horby et al.  LATE TREATMENT  RCT Is late treatment with casirivimab/imdevimab beneficial for COVID-19? RCT 9,785 patients in the United Kingdom (September 2020 - May 2021) No significant difference in outcomes seen c19early.org Horby et al., The Lancet, June 2021 Favors casirivimab/im.. Favors control
Horby: RCT 9,785 hospitalized patients in the UK showing lower mortality with casirivimab/imdevimab, with statistical significance reached for baseline seronegative patients.
0 0.5 1 1.5 2+ Death/hospitalization 60% Improvement Relative Risk Casirivimab/i..  Hussein et al.  EARLY TREATMENT Is early treatment with casirivimab/imdevimab beneficial for COVID-19? PSM retrospective 384,447 patients in the USA (Dec 2020 - Sep 2021) Lower death/hosp. with casirivimab/imdevimab (p<0.000001) c19early.org Hussein et al., BMJ Open, December 2022 Favors casirivimab/im.. Favors control
Hussein: Retrospective 73,759 outpatients treated with casirivimab/imdevimab, showing lower mortality with treatment. This result is subject to potentially substantial confounding by indication - patients with more severe cases may be more likely to receive treatment, and severity information was unavailable in the database.
0 0.5 1 1.5 2+ Symp. case 93% Improvement Relative Risk Case 93% Casirivimab/i..  Isa et al.  Prophylaxis  DB RCT Is prophylaxis with casirivimab/imdevimab beneficial for COVID-19? Double-blind RCT 969 patients in the USA (July 2020 - May 2021) Fewer symptomatic cases (p=0.0019) and cases (p=0.0018) c19early.org Isa et al., medRxiv, November 2021 Favors casirivimab/im.. Favors control
Isa: RCT 969 patients, 729 treated with monthly subcutaneous casirivimab/imdevimab, showing significantly lower risk of COVID-19 with treatment. There were no grade 3 injection site reactions or hypersensitivity reactions. Slightly more TEAEs were reported with treatment (54.9% vs. 48.3%), due to grade 1-2 ISRs. Serious adverse events were rare and occurred with similar percentages for treatment and control groups. There were no deaths. NCT04519437.
0 0.5 1 1.5 2+ Further treatment includin.. 58% Improvement Relative Risk Casirivimab/i..  Kakinoki et al.  EARLY TREATMENT Is early treatment with casirivimab/imdevimab beneficial for COVID-19? Retrospective 108 patients in Japan Lower progression with casirivimab/imdevimab (p=0.049) c19early.org Kakinoki et al., Int. J. Infectious Di.., Nov 2021 Favors casirivimab/im.. Favors control
Kakinoki: Retrospective 55 patients in Japan treated a median of 3 days from symptom onset with casirivimab/imdevimab, and 53 control patients, showing lower risk of further treatment including oxygen or antivirals.
0 0.5 1 1.5 2+ Death/hospitalization 46% Improvement Relative Risk Casirivimab/i..  Kip et al.  EARLY TREATMENT Is early treatment with casirivimab/imdevimab beneficial for COVID-19? Retrospective 2,571 patients in the USA (December 2020 - August 2022) Lower death/hosp. with casirivimab/imdevimab (p=0.000014) c19early.org Kip et al., Annals of Internal Medicine, Apr 2023 Favors casirivimab/im.. Favors control
Kip: Retrospective 2,571 patients treated with mAbs in the USA, and 5,135 control patients, showing lower combined mortality/hospitalization for bamlanivimab, bamlanivimab/etesevimab, casirivimab/imdevimab, sotrovimab, and bebtelovimab, with statistical significance only for casirivimab/imdevimab.

Confounding by treatment propensity. This study analyzes a population where only a fraction of eligible patients received the treatment. Patients receiving treatment may be more likely to follow other recommendations, more likely to receive additional care, and more likely to use additional treatments that are not tracked in the data (e.g., nasal/oral hygiene c19early.org (C), c19early.org (D), vitamin D c19early.org (E), etc.) — either because the physician recommending casirivimab/imdevimab also recommended them, or because the patient seeking out casirivimab/imdevimab is more likely to be familiar with the efficacy of additional treatments and more likely to take the time to use them. Therefore, these kind of studies may overestimate the efficacy of treatments.
0 0.5 1 1.5 2+ Severe case 97% Improvement Relative Risk Casirivimab/i..  Kneidinger et al.  EARLY TREATMENT Is early treatment with casirivimab/imdevimab beneficial for COVID-19? Retrospective 218 patients in Germany (January - March 2022) Lower severe cases with casirivimab/imdevimab (not stat. sig., p=0.45) c19early.org Kneidinger et al., Infection, September 2022 Favors casirivimab/im.. Favors control
Kneidinger: Retrospective 218 COVID+ lung transplant patients in Germany, showing no significant difference in severe cases with early casirivimab/imdevimab use.
0 0.5 1 1.5 2+ Ventilation 77% Improvement Relative Risk ICU admission 92% Progression 68% primary Hospitalization time 29% Casirivimab/i..  Komagamine et al.  EARLY TREATMENT Is early treatment with casirivimab/imdevimab beneficial for COVID-19? Retrospective 128 patients in Japan Lower ICU admission (p=0.041) and progression (p=0.006) c19early.org Komagamine et al., J. General and Fami.., Dec 2021 Favors casirivimab/im.. Favors control
Komagamine: Combined retrospective/prospective study in Japan with 53 casirivimab/imdevimab patients and 75 control patients, showing significantly lower progression with treatment.
0 0.5 1 1.5 2+ ICU admission 31% Improvement Relative Risk Oxygen therapy 7% Hospitalization -108% Casirivimab/i..  Levey et al.  EARLY TREATMENT Is early treatment with casirivimab/imdevimab beneficial for COVID-19? Retrospective 86 patients in the USA (March - October 2021) Higher hospitalization with casirivimab/imdevimab (not stat. sig., p=0.15) c19early.org Levey et al., American J. Obstetrics &.., Jun 2022 Favors casirivimab/im.. Favors control
Levey: Retrospective 86 pregnant COVID-19 patients, 36 treated with casirivimab/imdevimab, showing no significant difference in COVID-19 outcomes with treatment.
0 0.5 1 1.5 2+ Mortality 93% Improvement Relative Risk Death/hospitalization 56% primary Hospitalization 48% Hospitalization/ER 40% SQ vs. IV death 53% SQ vs. IV death/hosp. -71% SQ vs. IV hospitalization -79% SQ vs. IV ER/hosp. 15% Casirivimab/i..  McCreary et al.  LATE TREATMENT Is late treatment with casirivimab/imdevimab beneficial for COVID-19? Prospective study of 2,185 patients in the USA (Jul - Oct 2021) Lower mortality (p=0.009) and death/hosp. (p=0.00031) c19early.org McCreary et al., medRxiv, December 2021 Favors casirivimab/im.. Favors control
McCreary: Prospective study comparing subcutaneous and intravenous casirivimab/imdevimab, and comparing to a PSM matched control set, showing significantly lower mortality and hospitalization with treatment. Controls were matched with EUA-eligible risk factors only, authors were unable to determine symptom severity.
0 0.5 1 1.5 2+ Ventilation 33% Improvement Relative Risk Oxygen therapy 46% Casirivimab/i..  Miyashita et al.  EARLY TREATMENT Is early treatment with casirivimab/imdevimab beneficial for COVID-19? Retrospective 922 patients in Japan Lower need for oxygen therapy with casirivimab/imdevimab (p=0.0044) c19early.org Miyashita et al., J. Infection and Che.., May 2022 Favors casirivimab/im.. Favors control
Miyashita: Retrospective 461 patients treated with casirivimab/imdevimab in Japan, and 461 matched controls, showing lower oxygen requirements with treatment.
0 0.5 1 1.5 2+ Hospitalization 85% Improvement Relative Risk Hospitalization/ER 92% Symp. case 33% primary Weeks with high viral load 40% Casirivimab/i..  O'Brien et al.  EARLY TREATMENT  DB RCT Is early treatment with casirivimab/imdevimab beneficial for COVID-19? Double-blind RCT 204 patients in multiple countries (Jul 2020 - Jan 2021) Fewer hosp./ER visits (p=0.029) and symptomatic cases (p=0.04) c19early.org O'Brien et al., JAMA, January 2022 Favors casirivimab/im.. Favors control
O'Brien: RCT 204 asymptomatic COVID+ patients, 100 treated with subcutaneous casirivimab/imdevimab, showing lower development of symptoms, lower hospitalization, and faster viral clearance with treatment. Study conducted prior to widespread circulation of delta and omicron in the study locations.
0 0.5 1 1.5 2+ Hospitalization 24% Improvement Relative Risk Casirivimab/i..  Osugi et al.  EARLY TREATMENT Is early treatment with casirivimab/imdevimab beneficial for COVID-19? Retrospective 104 patients in Japan (August - September 2021) Study underpowered to detect differences c19early.org Osugi et al., Cureus, February 2022 Favors casirivimab/im.. Favors control
Osugi: Retrospective 104 outpatients in Japan, 30 treated with casirivimab/imdevimab, showing no significant difference in hospitalization.
0 0.5 1 1.5 2+ Hospitalization 92% Improvement Relative Risk Case 81% Case (b) 82% Hospitalization/ER 89% Symp. case 81% Recovery time 62% Time to viral- 69% Casirivimab/i..  Regeneron et al.  Prophylaxis  DB RCT Is prophylaxis with casirivimab/imdevimab beneficial for COVID-19? Double-blind RCT 1,683 patients in multiple countries (Jul 2020 - Oct 2021) Lower hospitalization (p=0.031) and fewer cases (p<0.0001) c19early.org Regeneron, Press Release, November 2021 Favors casirivimab/im.. Favors control
Regeneron (C): Long-term results for PEP RCT NCT04452318, with 841 baseline seronegative casirivimab/imdevimab patients and 842 placebo patients, showing significantly lower cases with treatment.
0 0.5 1 1.5 2+ Symp. case 94% Improvement Relative Risk Case 48% Casirivimab/i..  Regeneron et al.  Prophylaxis  RCT Is prophylaxis with casirivimab/imdevimab beneficial for COVID-19? RCT 409 patients in the USA Fewer symptomatic cases with casirivimab/imdevimab (p=0.0091) c19early.org Regeneron, Press Release, January 2021 Favors casirivimab/im.. Favors control
Regeneron (D): Interim results of REGEN-COV prophylaxis showing 100% prevention of symptomatic infection (8/223 placebo vs. 0/186 REGEN-COV), and approximately 50% lower overall rates of infection (symptomatic and asymptomatic) (23/223 placebo vs. 10/186 REGEN-COV).
0 0.5 1 1.5 2+ Death/hospitalization 71% Improvement Relative Risk Death/hospitalization (b) 70% Recovery time 29% Recovery time (b) 29% Casirivimab/i..  Regeneron et al.  EARLY TREATMENT  RCT Is early treatment with casirivimab/imdevimab beneficial for COVID-19? RCT 2,696 patients in the USA Lower death/hosp. (p<0.0001) and faster recovery (p=0.0001) c19early.org Regeneron, Press Release, March 2021 Favors casirivimab/im.. Favors control
Regeneron: Press release for new phase III data showing lower hospitalization/mortality, and faster symptom resolution among the subset of patients with at least one risk factor.

Some variants may escape antibodies cell.com.
0 0.5 1 1.5 2+ Recovery time 38% Improvement Relative Risk Recovery time (b) 54% Casirivimab/i..  Regeneron et al.  EARLY TREATMENT  RCT Is early treatment with casirivimab/imdevimab beneficial for COVID-19? RCT 183 patients in the USA Faster recovery with casirivimab/imdevimab (not stat. sig., p=0.22) c19early.org Regeneron, Press Release, September 2020 Favors casirivimab/im.. Favors control
Regeneron (B): Analysis of the first 275 patients in a trial of the REGN-COV2 antibody cocktail showing reductions in viral load and the time to alleviate symptoms in non-hospitalized patients with COVID-19. Greatest improvements were seen with patients that had not mounted their own effective immune response prior to treatment.

The mean time-weighted-average change from baseline nasopharyngeal viral load through Day 7 in the seronegative (no measurable antiviral antibodies) group was a 0.60 log10 copies/mL greater reduction (p=0.03) in patients treated with high dose, and a 0.51 log10 copies/mL greater reduction (p=0.06) in patients treated with low dose, compared to placebo. In the overall population, there was a 0.51 log10 copies/mL greater reduction (p=0.0049) in patients treated with high dose, and a 0.23 log10 copies/mL greater reduction (p=0.20) in patients treated with low dose, compared to placebo.

Among seronegative patients, median time to symptom alleviation (defined as symptoms becoming mild or absent) was 13 days in placebo, 8 days in high dose (p=0.22), and 6 days in low dose (p=0.09).

Adverse reactions were similar with treatment and placebo. There were no deaths.
0 0.5 1 1.5 2+ Severe case -46% Improvement Relative Risk Casirivimab/i..  Shopen et al.  EARLY TREATMENT Is early treatment with casirivimab/imdevimab beneficial for COVID-19? Retrospective 359 patients in Israel (June - September 2021) Higher severe cases with casirivimab/imdevimab (not stat. sig., p=0.26) c19early.org Shopen et al., medRxiv, January 2022 Favors casirivimab/im.. Favors control
Shopen: Retrospective 359 COVID+ patients in Israel, 116 treated with casirivimab/imdevimab, showing no significant difference with treatment in multivariable analysis.
0 0.5 1 1.5 2+ Mortality 36% Improvement Relative Risk Mortality (b) 56% Mortality (c) 21% Death/intubation 31% Discharge 30% Casirivimab/i..  Somersan-Karakaya et al.  LATE TREATMENT  DB RCT Is late treatment with casirivimab/imdevimab beneficial for COVID-19? Double-blind RCT 1,197 patients in multiple countries (Jun 2020 - Apr 2021) Lower mortality (p=0.021) and death/intubation (p=0.027) c19early.org Somersan-Karakaya et al., The J. Infec.., Nov 2021 Favors casirivimab/im.. Favors control
Somersan-Karakaya: RCT 1,336 hospitalized patients with symptom onset <=10 days on low-flow or no supplemental oxygen, showing lower mortality with treatment. Cohorts 2&3 were paused mid-trial due to increased deaths in the treatment arm and these results were not included. NCT04426695.
0 0.5 1 1.5 2+ Mortality -200% Improvement Relative Risk Mortality (b) 60% Progression 45% Progression (b) 50% Casirivimab/i..  Suzuki et al.  EARLY TREATMENT Is early treatment with casirivimab/imdevimab beneficial for COVID-19? Retrospective 949 patients in Japan (July - September 2021) Lower progression with casirivimab/imdevimab (p=0.021) c19early.org Suzuki et al., medRxiv, December 2021 Favors casirivimab/im.. Favors control
Suzuki: Retrospective 949 patients in Japan, 314 treated with casirivimab/imdevimab showing significantly lower risk of deterioration with treatment.
0 0.5 1 1.5 2+ Mortality 98% Improvement Relative Risk Hospitalization 91% Casirivimab/i..  Webb et al.  EARLY TREATMENT Is early treatment with casirivimab/imdevimab beneficial for COVID-19? Retrospective 5,651 patients in the USA Lower hospitalization with casirivimab/imdevimab (p=0.00028) c19early.org Webb et al., Open Forum Infectious Dis.., Jun 2021 Favors casirivimab/im.. Favors control
Webb: Retrospective 115 patients treated with casirivimab/imdevimab showing lower mortality, hospital admission, and emergency department visits with treatment. Authors incorrectly state that "no other COVID-19 therapies for ambulatory patients have proven effective".
0 0.5 1 1.5 2+ Death/hospitalization 61% Improvement Relative Risk Hospitalization 61% Casirivimab/i..  Wei et al.  EARLY TREATMENT Is early treatment with casirivimab/imdevimab beneficial for COVID-19? Retrospective 19,564 patients in the USA (December 2020 - June 2021) Lower death/hosp. (p<0.0001) and hospitalization (p<0.0001) c19early.org Wei et al., medRxiv, February 2022 Favors casirivimab/im.. Favors control
Wei: Retrospective 4,396 casirivimab/imdevimab patients in the USA, showing lower combined mortality/hospitalization (CDM database) and lower hospitalization (PMTX+ database) with treatment.
0 0.5 1 1.5 2+ Mortality 50% Improvement Relative Risk Mortality (b) 67% Mortality (c) -2% Death/hospitalization 71% Death/hospitalization (b) 70% Recovery time 29% Recovery time (b) 29% Casirivimab/i..  Weinreich et al.  EARLY TREATMENT  RCT Is early treatment with casirivimab/imdevimab beneficial for COVID-19? RCT 4,180 patients in the USA (September 2020 - January 2021) Lower death/hosp. (p=0.001) and faster recovery (p=0.001) c19early.org Weinreich et al., NEJM, May 2021 Favors casirivimab/im.. Favors control
Weinreich: RCT 4,057 outpatients with >=1 risk factor for severe disease, showing significantly lower combined hospitalization/death, and significantly faster recovery with treatment. Median time from onset of symptoms 3 days. NCT04425629.
0 0.5 1 1.5 2+ Hospitalization 82% Improvement Relative Risk Casirivimab/i..  Wilden et al.  EARLY TREATMENT Is early treatment with casirivimab/imdevimab beneficial for COVID-19? Retrospective study in the USA (December 2020 - July 2021) Lower hospitalization with casirivimab/imdevimab (p=0.0036) c19early.org Wilden et al., J. the National Compreh.., Mar 2022 Favors casirivimab/im.. Favors control
Wilden: Retrospective 395 patients in the USA receiving casirivimab/imdevimab or bamlanivimab, showing lower risk of hospitalization with treatment, statistically significant for casirivimab/imdevimab.
0 0.5 1 1.5 2+ Oxygen therapy -21% Improvement Relative Risk Severe case -1% Hospitalization 14% Casirivimab/i..  Williams et al.  EARLY TREATMENT Is early treatment with casirivimab/imdevimab beneficial for COVID-19? Retrospective 764 patients in the USA Study underpowered to detect differences c19early.org Williams et al., American J. Obstetric.., Sep 2022 Favors casirivimab/im.. Favors control
Williams (B): Retrospective 764 pregnant patients with COVID-19 in the USA, 88 treated with casirivimab/imdevimab, showing no significant difference in outcomes.
We perform ongoing searches of PubMed, medRxiv, Europe PMC, ClinicalTrials.gov, The Cochrane Library, Google Scholar, Research Square, ScienceDirect, Oxford University Press, the reference lists of other studies and meta-analyses, and submissions to the site c19early.org. Search terms are casirivimab, imdevimab, REGEN-COV and COVID-19 or SARS-CoV-2. Automated searches are performed twice daily, with all matches reviewed for inclusion. All studies regarding the use of casirivimab/imdevimab for COVID-19 that report a comparison with a control group are included in the main analysis. Sensitivity analysis is performed, excluding studies with major issues, epidemiological studies, and studies with minimal available information. This is a living analysis and is updated regularly.
We extracted effect sizes and associated data from all studies. If studies report multiple kinds of effects then the most serious outcome is used in pooled analysis, while other outcomes are included in the outcome specific analyses. For example, if effects for mortality and cases are both reported, the effect for mortality is used, this may be different to the effect that a study focused on. If symptomatic results are reported at multiple times, we used the latest time, for example if mortality results are provided at 14 days and 28 days, the results at 28 days have preference. Mortality alone is preferred over combined outcomes. Outcomes with zero events in both arms are not used, the next most serious outcome with one or more events is used. For example, in low-risk populations with no mortality, a reduction in mortality with treatment is not possible, however a reduction in hospitalization, for example, is still valuable. Clinical outcomes are considered more important than viral test status. When basically all patients recover in both treatment and control groups, preference for viral clearance and recovery is given to results mid-recovery where available. After most or all patients have recovered there is little or no room for an effective treatment to do better, however faster recovery is valuable. If only individual symptom data is available, the most serious symptom has priority, for example difficulty breathing or low SpO2 is more important than cough. When results provide an odds ratio, we compute the relative risk when possible, or convert to a relative risk according to Zhang. Reported confidence intervals and p-values were used when available, using adjusted values when provided. If multiple types of adjustments are reported propensity score matching and multivariable regression has preference over propensity score matching or weighting, which has preference over multivariable regression. Adjusted results have preference over unadjusted results for a more serious outcome when the adjustments significantly alter results. When needed, conversion between reported p-values and confidence intervals followed Altman, Altman (B), and Fisher's exact test was used to calculate p-values for event data. If continuity correction for zero values is required, we use the reciprocal of the opposite arm with the sum of the correction factors equal to 1 Sweeting. Results are expressed with RR < 1.0 favoring treatment, and using the risk of a negative outcome when applicable (for example, the risk of death rather than the risk of survival). If studies only report relative continuous values such as relative times, the ratio of the time for the treatment group versus the time for the control group is used. Calculations are done in Python (3.12.2) with scipy (1.12.0), pythonmeta (1.26), numpy (1.26.4), statsmodels (0.14.1), and plotly (5.19.0).
Forest plots are computed using PythonMeta Deng with the DerSimonian and Laird random effects model (the fixed effect assumption is not plausible in this case) and inverse variance weighting. Results are presented with 95% confidence intervals. Heterogeneity among studies was assessed using the I2 statistic. Mixed-effects meta-regression results are computed with R (4.1.2) using the metafor (3.0-2) and rms (6.2-0) packages, and using the most serious sufficiently powered outcome. For all statistical tests, a p-value less than 0.05 was considered statistically significant. Grobid 0.8.0 is used to parse PDF documents.
We have classified studies as early treatment if most patients are not already at a severe stage at the time of treatment (for example based on oxygen status or lung involvement), and treatment started within 5 days of the onset of symptoms. If studies contain a mix of early treatment and late treatment patients, we consider the treatment time of patients contributing most to the events (for example, consider a study where most patients are treated early but late treatment patients are included, and all mortality events were observed with late treatment patients). We note that a shorter time may be preferable. Antivirals are typically only considered effective when used within a shorter timeframe, for example 0-36 or 0-48 hours for oseltamivir, with longer delays not being effective McLean, Treanor.
We received no funding, this research is done in our spare time. We have no affiliations with any pharmaceutical companies or political parties.
A summary of study results is below. Please submit updates and corrections at the bottom of this page.
A summary of study results is below. Please submit updates and corrections at https://c19early.org/rmeta.html.
Effect extraction follows pre-specified rules as detailed above and gives priority to more serious outcomes. For pooled analyses, the first (most serious) outcome is used, which may differ from the effect a paper focuses on. Other outcomes are used in outcome specific analyses.
Cooper, 10/8/2021, retrospective, USA, peer-reviewed, 9 authors, excluded in exclusion analyses: unadjusted results with no group details. risk of death, 77.5% lower, RR 0.23, p = 0.18, treatment 1 of 1,148 (0.1%), control 33 of 8,534 (0.4%), NNT 334, unadjusted.
risk of ICU admission, 47.5% lower, RR 0.52, p = 0.14, treatment 6 of 1,148 (0.5%), control 85 of 8,534 (1.0%), NNT 211, unadjusted.
risk of hospitalization, 52.4% lower, RR 0.48, p < 0.001, treatment 45 of 1,148 (3.9%), control 703 of 8,534 (8.2%), NNT 23, unadjusted.
Faraone, 5/5/2022, retrospective, Italy, preprint, 12 authors, study period 25 October, 2020 - 30 April, 2021, average treatment delay 2.3 days. risk of death, 92.2% lower, RR 0.08, p = 0.03, treatment 0 of 11 (0.0%), control 8 of 23 (34.8%), NNT 2.9, relative risk is not 0 because of continuity correction due to zero events (with reciprocal of the contrasting arm).
risk of oxygen therapy, 94.5% lower, RR 0.06, p = 0.02, treatment 0 of 11 (0.0%), control 15 of 23 (65.2%), NNT 1.5, odds ratio converted to relative risk, relative risk is not 0 because of continuity correction due to zero events (with reciprocal of the contrasting arm).
Gershengorn, 12/2/2022, retrospective, USA, peer-reviewed, 6 authors, excluded in exclusion analyses: substantial unadjusted confounding by indication possible. risk of hospitalization, 95.0% higher, OR 1.95, p = 0.09, treatment 369, control 5,915, adjusted per study, multivariable, day 30, RR approximated with OR.
risk of hospitalization, 104.9% higher, RR 2.05, p = 0.009, treatment 21 of 369 (5.7%), control 41 of 1,476 (2.8%), propensity score matching, day 30, Figure 2, PSM cohort.
risk of hospitalization, 100% higher, RR 2.00, p = 0.07, treatment 11 of 213 (5.2%), control 22 of 852 (2.6%), delta, propensity score matching, day 30, Figure 2, PSM cohort.
risk of hospitalization, 110.5% higher, RR 2.11, p = 0.06, treatment 10 of 156 (6.4%), control 19 of 624 (3.0%), omicron, propensity score matching, day 30, Figure 2, PSM cohort.
Hussein, 12/19/2022, retrospective, USA, peer-reviewed, 9 authors, study period 1 December, 2020 - 30 September, 2021, excluded in exclusion analyses: substantial unadjusted confounding by indication possible. risk of death/hospitalization, 60.0% lower, HR 0.40, p < 0.001, NNT 35, propensity score matching, Cox proportional hazards, day 30.
Kakinoki, 11/4/2021, retrospective, Japan, peer-reviewed, 16 authors, average treatment delay 3.0 days. risk of further treatment including oxygen or antivirals, 57.6% lower, RR 0.42, p = 0.049, treatment 13 of 55 (23.6%), control 22 of 53 (41.5%), NNT 5.6, adjusted per study, odds ratio converted to relative risk, multivariable.
Kip, 4/4/2023, retrospective, USA, peer-reviewed, 16 authors, study period 8 December, 2020 - 31 August, 2022. risk of death/hospitalization, 46.0% lower, RR 0.54, p < 0.001, treatment 61 of 1,479 (4.1%), control 227 of 2,954 (7.7%), NNT 28, mainly delta variant, day 28.
Kneidinger, 9/9/2022, retrospective, Germany, peer-reviewed, 11 authors, study period 1 January, 2022 - 20 March, 2022, lung transplant patients. risk of severe case, 97.2% lower, RR 0.03, p = 0.45, treatment 0 of 3 (0.0%), control 34 of 215 (15.8%), NNT 6.3, relative risk is not 0 because of continuity correction due to zero events (with reciprocal of the contrasting arm).
Komagamine, 12/19/2021, retrospective, Japan, peer-reviewed, 4 authors, average treatment delay 5.0 days. risk of mechanical ventilation, 77.3% lower, RR 0.23, p = 0.51, treatment 0 of 53 (0.0%), control 2 of 75 (2.7%), NNT 38, relative risk is not 0 because of continuity correction due to zero events (with reciprocal of the contrasting arm).
risk of ICU admission, 92.3% lower, RR 0.08, p = 0.04, treatment 0 of 53 (0.0%), control 7 of 75 (9.3%), NNT 11, relative risk is not 0 because of continuity correction due to zero events (with reciprocal of the contrasting arm).
risk of progression, 67.8% lower, RR 0.32, p = 0.006, treatment 8 of 53 (15.1%), control 33 of 75 (44.0%), NNT 3.5, adjusted per study, odds ratio converted to relative risk, multivariable, primary outcome.
hospitalization time, 28.9% lower, relative time 0.71, p < 0.001, treatment 53, control 75.
Levey, 6/4/2022, retrospective, USA, peer-reviewed, 6 authors, study period March 2021 - October 2021. risk of ICU admission, 30.6% lower, RR 0.69, p = 1.00, treatment 1 of 36 (2.8%), control 2 of 50 (4.0%), NNT 82.
risk of oxygen therapy, 7.4% lower, RR 0.93, p = 1.00, treatment 2 of 36 (5.6%), control 3 of 50 (6.0%), NNT 225.
risk of hospitalization, 108.3% higher, RR 2.08, p = 0.15, treatment 9 of 36 (25.0%), control 6 of 50 (12.0%).
Miyashita, 5/26/2022, retrospective, Japan, peer-reviewed, 6 authors, average treatment delay 4.0 days. risk of mechanical ventilation, 33.3% lower, RR 0.67, p = 1.00, treatment 2 of 461 (0.4%), control 3 of 461 (0.7%), NNT 461.
risk of oxygen therapy, 46.4% lower, RR 0.54, p = 0.004, treatment 30 of 461 (6.5%), control 56 of 461 (12.1%), NNT 18.
O'Brien, 1/14/2022, Double Blind Randomized Controlled Trial, placebo-controlled, multiple countries, peer-reviewed, 38 authors, study period 13 July, 2020 - 28 January, 2021. risk of hospitalization, 85.5% lower, RR 0.15, p = 0.25, treatment 0 of 100 (0.0%), control 3 of 104 (2.9%), NNT 35, relative risk is not 0 because of continuity correction due to zero events (with reciprocal of the contrasting arm).
risk of hospitalization/ER, 92.2% lower, RR 0.08, p = 0.03, treatment 0 of 100 (0.0%), control 6 of 104 (5.8%), NNT 17, relative risk is not 0 because of continuity correction due to zero events (with reciprocal of the contrasting arm).
risk of symptomatic case, 33.0% lower, RR 0.67, p = 0.04, treatment 29 of 100 (29.0%), control 44 of 104 (42.3%), NNT 7.5, odds ratio converted to relative risk, day 14, primary outcome.
relative weeks with high viral load, 39.7% better, RR 0.60, p = 0.001, treatment 100, control 104.
Osugi, 2/3/2022, retrospective, Japan, peer-reviewed, mean age 47.8, 5 authors, study period 31 August, 2021 - 27 September, 2021. risk of hospitalization, 24.0% lower, HR 0.76, p = 0.65, treatment 4 of 30 (13.3%), control 15 of 74 (20.3%), adjusted per study, multivariable, Cox proportional hazards.
Regeneron, 3/23/2021, Randomized Controlled Trial, USA, preprint, 1 author. risk of death/hospitalization, 71.3% lower, RR 0.29, p < 0.001, treatment 18 of 1,355 (1.3%), control 62 of 1,341 (4.6%), NNT 30, 2,400mg IV, >=1 risk factor.
risk of death/hospitalization, 70.4% lower, RR 0.30, p = 0.003, treatment 7 of 736 (1.0%), control 24 of 748 (3.2%), NNT 44, 1,200mg IV, >=1 risk factor.
recovery time, 28.6% lower, relative time 0.71, p < 0.001, treatment 1,355, control 1,341, 2,400mg IV, >=1 risk factor.
recovery time, 28.6% lower, relative time 0.71, p < 0.001, treatment 736, control 748, 1,200mg IV, >=1 risk factor.
Regeneron (B), 9/29/2020, Randomized Controlled Trial, USA, preprint, 1 author. recovery time, 38.0% lower, relative time 0.62, p = 0.22, treatment 92, control 91, high dose median time to recovery, group sizes estimated because they were not supplied.
recovery time, 54.0% lower, relative time 0.46, p = 0.09, treatment 92, control 91, low dose median time to recovery, group sizes estimated because they were not supplied.
Shopen, 1/31/2022, retrospective, Israel, preprint, 11 authors, study period June 2021 - September 2021. risk of severe case, 45.6% higher, RR 1.46, p = 0.26, treatment 24 of 116 (20.7%), control 26 of 243 (10.7%), adjusted per study, odds ratio converted to relative risk.
Suzuki, 12/21/2021, retrospective, Japan, preprint, 49 authors, study period 24 July, 2021 - 30 September, 2021. risk of death, 200.0% higher, RR 3.00, p = 1.00, treatment 1 of 222 (0.5%), control 0 of 222 (0.0%), continuity correction due to zero event (with reciprocal of the contrasting arm), propensity score matching.
risk of death, 59.6% lower, RR 0.40, p = 0.67, treatment 1 of 314 (0.3%), control 5 of 635 (0.8%), NNT 213, unadjusted.
risk of progression, 45.2% lower, RR 0.55, p = 0.02, treatment 17 of 222 (7.7%), control 31 of 222 (14.0%), NNT 16, propensity score matching.
risk of progression, 49.9% lower, RR 0.50, p = 0.002, treatment 34 of 314 (10.8%), control 70 of 365 (19.2%), NNT 12, odds ratio converted to relative risk, multivariate.
Webb, 6/23/2021, retrospective, USA, peer-reviewed, 14 authors. risk of death, 98.3% lower, RR 0.02, p = 0.63, treatment 0 of 115 (0.0%), control 57 of 5,536 (1.0%), NNT 97, relative risk is not 0 because of continuity correction due to zero events (with reciprocal of the contrasting arm).
risk of hospitalization, 91.1% lower, RR 0.09, p < 0.001, treatment 1 of 115 (0.9%), control 538 of 5,536 (9.7%), NNT 11.
Wei, 2/28/2022, retrospective, database analysis, USA, preprint, 8 authors, study period December 2020 - June 2021. risk of death/hospitalization, 61.0% lower, HR 0.39, p < 0.001, treatment 23 of 1,116 (2.1%), control 27 of 5,291 (0.5%), Optum CDM, Cox proportional hazards.
risk of hospitalization, 61.0% lower, HR 0.39, p < 0.001, treatment 59 of 3,280 (1.8%), control 75 of 16,284 (0.5%), IQVIA PMTX+, Cox proportional hazards.
Weinreich, 5/21/2021, Randomized Controlled Trial, USA, peer-reviewed, 39 authors, study period 24 September, 2020 - 17 January, 2021, average treatment delay 3.0 days, trial NCT04425629 (history). risk of death, 50.0% lower, RR 0.50, p = 0.45, treatment 2 of 2,091 (0.1%), control 4 of 2,089 (0.2%), NNT 1044, Table S9.
risk of death, 67.0% lower, RR 0.33, p = 0.37, treatment 1 of 1,355 (0.1%), control 3 of 1,341 (0.2%), NNT 667, 2400mg,Table S9.
risk of death, 1.6% higher, RR 1.02, p = 1.00, treatment 1 of 736 (0.1%), control 1 of 748 (0.1%), 1200mg,Table S9.
risk of death/hospitalization, 71.3% lower, RR 0.29, p < 0.001, treatment 18 of 1,355 (1.3%), control 62 of 1,341 (4.6%), NNT 30, 2400mg.
risk of death/hospitalization, 70.4% lower, RR 0.30, p = 0.002, treatment 7 of 736 (1.0%), control 24 of 748 (3.2%), NNT 44, 1200mg.
recovery time, 28.6% lower, relative time 0.71, p < 0.001, treatment 1,355, control 1,341, 2400mg.
recovery time, 28.6% lower, relative time 0.71, p < 0.001, treatment 736, control 748, 1200mg.
Wilden, 3/31/2022, retrospective, USA, peer-reviewed, 9 authors, study period December 2020 - July 2021. risk of hospitalization, 82.0% lower, OR 0.18, p = 0.004, adjusted per study, multivariable, RR approximated with OR.
Williams (B), 9/12/2022, retrospective, USA, peer-reviewed, 6 authors. risk of oxygen therapy, 20.8% higher, RR 1.21, p = 0.87, treatment 1 of 88 (1.1%), control 6 of 676 (0.9%), odds ratio converted to relative risk.
risk of severe case, 1.0% higher, RR 1.01, p = 0.99, treatment 1 of 88 (1.1%), control 7 of 676 (1.0%), odds ratio converted to relative risk.
risk of hospitalization, 13.9% lower, RR 0.86, p = 0.90, treatment 1 of 88 (1.1%), control 8 of 676 (1.2%), NNT 2125, odds ratio converted to relative risk.
Effect extraction follows pre-specified rules as detailed above and gives priority to more serious outcomes. For pooled analyses, the first (most serious) outcome is used, which may differ from the effect a paper focuses on. Other outcomes are used in outcome specific analyses.
Horby, 6/16/2021, Randomized Controlled Trial, United Kingdom, peer-reviewed, 32 authors, study period 18 September, 2020 - 22 May, 2021, average treatment delay 9.0 days. risk of death, 6.0% lower, RR 0.94, p = 0.16, treatment 943 of 4,839 (19.5%), control 1,029 of 4,946 (20.8%), NNT 76, all patients.
risk of mechanical ventilation, 1.0% higher, RR 1.01, p = 0.88, treatment 484 of 4,556 (10.6%), control 488 of 4,642 (10.5%), all patients.
risk of death, 21.0% lower, RR 0.79, p = 0.001, treatment 396 of 1,633 (24.2%), control 452 of 1,520 (29.7%), NNT 18, seronegative patients.
risk of mechanical ventilation, 13.0% lower, RR 0.87, p = 0.13, treatment 190 of 1,599 (11.9%), control 202 of 1,484 (13.6%), NNT 58, seronegative patients.
McCreary, 12/1/2021, prospective, USA, preprint, 27 authors, study period 14 July, 2021 - 26 October, 2021, average treatment delay 6.0 days. risk of death, 93.0% lower, RR 0.07, p = 0.009, treatment 1 of 652 (0.2%), control 29 of 1,304 (2.2%), NNT 48, propensity score matching.
risk of death/hospitalization, 56.0% lower, RR 0.44, p < 0.001, treatment 22 of 652 (3.4%), control 101 of 1,304 (7.7%), NNT 23, propensity score matching, primary outcome.
risk of hospitalization, 48.0% lower, RR 0.52, p = 0.005, treatment 22 of 652 (3.4%), control 85 of 1,304 (6.5%), NNT 32, propensity score matching.
risk of hospitalization/ER, 40.0% lower, RR 0.60, p = 0.003, treatment 40 of 652 (6.1%), control 133 of 1,304 (10.2%), NNT 25, propensity score matching.
Somersan-Karakaya, 11/8/2021, Double Blind Randomized Controlled Trial, placebo-controlled, multiple countries, peer-reviewed, median age 62.0, 34 authors, study period 10 June, 2020 - 9 April, 2021, average treatment delay 6.0 days, trial NCT04426695 (history), conflicts of interest: research funding from the drug patent holder, employee of the drug patent holder. risk of death, 35.9% lower, RR 0.64, p = 0.02, treatment 59 of 804 (7.3%), control 45 of 393 (11.5%), NNT 24, day 28, mFAS.
risk of death, 55.6% lower, RR 0.44, p = 0.005, treatment 24 of 360 (6.7%), control 24 of 160 (15.0%), NNT 12, seronegative, day 28, mFAS.
risk of death, 21.3% lower, RR 0.79, p = 0.42, treatment 26 of 369 (7.0%), control 18 of 201 (9.0%), NNT 52, seropositive, day 28, mFAS.
risk of death/intubation, 30.9% lower, RR 0.69, p = 0.03, treatment 82 of 804 (10.2%), control 58 of 393 (14.8%), NNT 22, day 1-29, mFAS.
risk of no hospital discharge, 30.2% lower, RR 0.70, p = 0.02, treatment 90 of 804 (11.2%), control 63 of 393 (16.0%), NNT 21, day 1-29, mFAS.
Effect extraction follows pre-specified rules as detailed above and gives priority to more serious outcomes. For pooled analyses, the first (most serious) outcome is used, which may differ from the effect a paper focuses on. Other outcomes are used in outcome specific analyses.
Isa, 11/16/2021, Double Blind Randomized Controlled Trial, USA, preprint, 31 authors, study period 26 July, 2020 - 21 May, 2021, trial NCT04519437 (history), conflicts of interest: employee of the drug patent holder. risk of symptomatic case, 92.6% lower, RR 0.07, p = 0.002, treatment 3 of 729 (0.4%), control 13 of 240 (5.4%), NNT 20, odds ratio converted to relative risk.
risk of case, 92.7% lower, RR 0.07, p = 0.002, treatment 0 of 729 (0.0%), control 10 of 240 (4.2%), NNT 24, odds ratio converted to relative risk, relative risk is not 0 because of continuity correction due to zero events (with reciprocal of the contrasting arm), seroconversion.
Regeneron (C), 11/8/2021, Double Blind Randomized Controlled Trial, multiple countries, preprint, 1 author, study period 13 July, 2020 - 4 October, 2021, trial NCT04452318 (history). risk of hospitalization, 92.3% lower, RR 0.08, p = 0.03, treatment 0 of 841 (0.0%), control 6 of 842 (0.7%), NNT 140, relative risk is not 0 because of continuity correction due to zero events (with reciprocal of the contrasting arm), 8 months.
risk of case, 81.5% lower, RR 0.19, p < 0.001, treatment 20 of 841 (2.4%), control 108 of 842 (12.8%), NNT 9.6, months 1-8.
risk of case, 81.6% lower, RR 0.18, p < 0.001, treatment 7 of 841 (0.8%), control 38 of 842 (4.5%), NNT 27, months 2-8.
risk of hospitalization/ER, 88.9% lower, RR 0.11, p = 0.06, treatment 0 of 753 (0.0%), control 4 of 752 (0.5%), NNT 188, relative risk is not 0 because of continuity correction due to zero events (with reciprocal of the contrasting arm), day 29.
risk of symptomatic case, 81.4% lower, RR 0.19, p < 0.001, treatment 11 of 753 (1.5%), control 59 of 752 (7.8%), NNT 16, day 29.
recovery time, 62.5% lower, relative time 0.37, p < 0.001, treatment 753, control 752, short-term followup, relative time with symptoms.
time to viral-, 69.2% lower, relative time 0.31, p < 0.001, treatment 753, control 752, short-term followup, relative time with high viral load.
Regeneron (D), 1/26/2021, Randomized Controlled Trial, USA, preprint, 1 author. risk of symptomatic case, 93.6% lower, RR 0.06, p = 0.009, treatment 0 of 186 (0.0%), control 8 of 223 (3.6%), NNT 28, relative risk is not 0 because of continuity correction due to zero events (with reciprocal of the contrasting arm).
risk of case, 47.9% lower, RR 0.52, p = 0.07, treatment 10 of 186 (5.4%), control 23 of 223 (10.3%), NNT 20.
Please send us corrections, updates, or comments. c19early involves the extraction of 100,000+ datapoints from thousands of papers. Community updates help ensure high accuracy. Vaccines and treatments are complementary. All practical, effective, and safe means should be used based on risk/benefit analysis. No treatment, vaccine, or intervention is 100% available and effective for all current and future variants. We do not provide medical advice. Before taking any medication, consult a qualified physician who can provide personalized advice and details of risks and benefits based on your medical history and situation. FLCCC and WCH provide treatment protocols.
  or use drag and drop   
Submit