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Bamlanivimab/etesevimab for COVID-19: real-time meta analysis of 14 studies
Covid Analysis, May 23, 2022, DRAFT
https://c19ly.com/meta.html
0 0.5 1 1.5+ All studies 55% 14 24,423 Improvement, Studies, Patients Relative Risk Mortality 56% 10 22,988 ICU admission 51% 2 12,628 Hospitalization 41% 9 21,880 Progression 66% 2 513 Recovery 11% 2 1,129 Cases 57% 1 965 Viral clearance 50% 2 1,101 RCTs 45% 5 2,784 RCT mortality 58% 2 1,349 Peer-reviewed 56% 11 22,673 Prophylaxis 57% 1 965 Early 69% 8 17,980 Late 29% 5 5,478 Bamlanivimab/etesevimab for COVID-19 c19ly.com May 2022 Favorsbamlanivimab/e.. Favorscontrol after exclusions
Statistically significant improvements are seen for mortality, ICU admission, hospitalization, recovery, and cases. 11 studies from 9 independent teams (all from the same country) show statistically significant improvements in isolation (4 for the most serious outcome).
Meta analysis using the most serious outcome reported shows 55% [30‑71%] improvement. Results are similar for Randomized Controlled Trials, similar after exclusions, and similar for peer-reviewed studies. Early treatment is more effective than late treatment.
Results are robust — in exclusion sensitivity analysis 6 of 14 studies must be excluded to avoid finding statistically significant efficacy in pooled analysis.
0 0.5 1 1.5+ All studies 55% 14 24,423 Improvement, Studies, Patients Relative Risk Mortality 56% 10 22,988 ICU admission 51% 2 12,628 Hospitalization 41% 9 21,880 Progression 66% 2 513 Recovery 11% 2 1,129 Cases 57% 1 965 Viral clearance 50% 2 1,101 RCTs 45% 5 2,784 RCT mortality 58% 2 1,349 Peer-reviewed 56% 11 22,673 Prophylaxis 57% 1 965 Early 69% 8 17,980 Late 29% 5 5,478 Bamlanivimab/etesevimab for COVID-19 c19ly.com May 2022 Favorsbamlanivimab/e.. Favorscontrol after exclusions
Efficacy is highly variant dependent. In Vitro studies suggest a lack of efficacy for omicron [Liu, Sheward, VanBlargan]. Monoclonal antibody use with variants can be associated with prolonged viral loads, clinical deterioration, and immune escape [Choudhary].
While many treatments have some level of efficacy, they do not replace vaccines and other measures to avoid infection. Only 7% of bamlanivimab/etesevimab studies show zero events in the treatment arm. Multiple treatments are typically used in combination, and other treatments may be more effective.
No treatment, vaccine, or intervention is 100% available and effective for all variants. All practical, effective, and safe means should be used. Denying the efficacy of treatments increases mortality, morbidity, collateral damage, and endemic risk.
All data to reproduce this paper and sources are in the appendix.
Highlights
Bamlanivimab/etesevimab reduces risk for COVID-19 with very high confidence for hospitalization, recovery, cases, and in pooled analysis, high confidence for mortality and ICU admission, low confidence for viral clearance, and very low confidence for progression. Efficacy is highly variant dependent. Unlikely to be effective for omicron.
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 42 treatments.
A
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ Gottlieb (RCT) 71% 0.29 [0.09-0.96] hosp./ER 4/101 7/52 Improvement, RR [CI] Treatment Control Webb 80% 0.20 [0.03-1.46] death 1/479 57/5,536 Dougan (DB RCT) 95% 0.05 [0.00-0.90] death 0/518 9/517 Cooper 45% 0.55 [0.07-3.99] death 1/473 33/8,534 Rubin 44% 0.56 [0.07-4.33] death 1/191 10/1,066 Delasobera -119% 2.19 [0.23-20.9] death 3/253 1/185 Dale 89% 0.11 [0.02-0.55] death 5/56 9/19 Wilden 51% 0.49 [0.23-1.04] hosp. n/a n/a Tau​2 = 0.31, I​2 = 37.9%, p = 0.00058 Early treatment 69% 0.31 [0.16-0.60] 15/2,071 126/15,909 69% improvement ACTIV-3/T.. (RCT) -100% 2.00 [0.69-5.83] death 9/163 5/151 Improvement, RR [CI] Treatment Control Bariola 67% 0.33 [0.10-1.01] death 4/234 12/234 Ganesh 74% 0.26 [0.05-1.20] death 2/1,789 8/1,832 Chew (RCT) 25% 0.75 [0.26-2.10] hosp. 6/159 8/158 Priest (PSM) 0% 1.00 [0.33-3.07] death 6/379 6/379 Tau​2 = 0.29, I​2 = 45.8%, p = 0.35 Late treatment 29% 0.71 [0.35-1.44] 27/2,724 39/2,754 29% improvement Lilly (RCT) 57% 0.43 [0.28-0.67] symp. case 483 (n) 482 (n) Improvement, RR [CI] Treatment Control Tau​2 = 0.00, I​2 = 0.0%, p = 0.00021 Prophylaxis 57% 0.43 [0.28-0.67] 0/483 0/482 57% improvement All studies 55% 0.45 [0.29-0.70] 42/5,278 165/19,145 55% improvement 14 bamlanivimab/etesevimab COVID-19 studies c19ly.com May 2022 Tau​2 = 0.28, I​2 = 47.9%, p = 0.00041 Effect extraction pre-specified(most serious outcome, see appendix) Favors bamlanivimab/e.. Favors control
Figure 1. A. Random effects meta-analysis. This plot shows pooled effects, discussion can be found in the heterogeneity section, and results for specific outcomes can be found in the individual outcome analyses. Effect extraction is pre-specified, using the most serious outcome reported. For details of effect extraction see the appendix. B. Scatter plot showing the distribution of effects reported in studies. C. History of all reported effects (chronological within treatment stages).
Introduction
We analyze all significant studies concerning the use of bamlanivimab/etesevimab 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, for studies within each treatment stage, for individual outcomes, for peer-reviewed studies, for Randomized Controlled Trials (RCTs), and after exclusions.
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.
Variant Dependence
Efficacy is variant dependent, for example in vitro studies suggest that bamlanivimab/etesevimab is not effective for the omicron variant [Liu, Sheward, VanBlargan, Zhou].
Results
Figure 3 shows a visual overview of the results, with details in Table 1 and Table 2. Figure 4, 5, 6, 7, 8, 9, 10, 11, and 12 show forest plots for a random effects meta-analysis of all studies with pooled effects, mortality results, ICU admission, hospitalization, progression, recovery, cases, viral clearance, and peer reviewed studies.
0 0.5 1 1.5+ ALL STUDIES MORTALITY ICU ADMISSION HOSPITALIZATION PROGRESSION RECOVERY CASES VIRAL CLEARANCE RANDOMIZED CONTROLLED TRIALS RCT MORTALITY PEER-REVIEWED After Exclusions ALL STUDIES All Prophylaxis Early Late Bamlanivimab/etesevimab for COVID-19 C19LY.COM MAY 2022
Figure 3. Overview of results.
Treatment timeNumber of studies reporting positive effects Total number of studiesPercentage of studies reporting positive effects Random effects meta-analysis results
Early treatment 7 8 87.5% 69% improvement
RR 0.31 [0.16‑0.60]
p = 0.00058
Late treatment 3 5 60.0% 29% improvement
RR 0.71 [0.35‑1.44]
p = 0.35
Prophylaxis 1 1 100% 57% improvement
RR 0.43 [0.28‑0.67]
p = 0.00021
All studies 11 14 78.6% 55% improvement
RR 0.45 [0.29‑0.70]
p = 0.00041
Table 1. Results by treatment stage.
Studies Early treatment Late treatment Prophylaxis PatientsAuthors
All studies 1469% [40‑84%]29% [-44‑65%]57% [33‑72%] 24,423 197
With exclusions 1272% [37‑88%]29% [-44‑65%]57% [33‑72%] 14,159 181
Peer-reviewed 1169% [40‑84%]10% [-164‑69%] 22,673 151
Randomized Controlled TrialsRCTs 579% [19‑95%]-21% [-218‑54%]57% [33‑72%] 2,784 85
Table 2. Results by treatment stage for all studies and with different exclusions.
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ Gottlieb (RCT) 71% 0.29 [0.09-0.96] hosp./ER 4/101 7/52 Improvement, RR [CI] Treatment Control Webb 80% 0.20 [0.03-1.46] death 1/479 57/5,536 Dougan (DB RCT) 95% 0.05 [0.00-0.90] death 0/518 9/517 Cooper 45% 0.55 [0.07-3.99] death 1/473 33/8,534 Rubin 44% 0.56 [0.07-4.33] death 1/191 10/1,066 Delasobera -119% 2.19 [0.23-20.9] death 3/253 1/185 Dale 89% 0.11 [0.02-0.55] death 5/56 9/19 Wilden 51% 0.49 [0.23-1.04] hosp. n/a n/a Tau​2 = 0.31, I​2 = 37.9%, p = 0.00058 Early treatment 69% 0.31 [0.16-0.60] 15/2,071 126/15,909 69% improvement ACTIV-3/T.. (RCT) -100% 2.00 [0.69-5.83] death 9/163 5/151 Improvement, RR [CI] Treatment Control Bariola 67% 0.33 [0.10-1.01] death 4/234 12/234 Ganesh 74% 0.26 [0.05-1.20] death 2/1,789 8/1,832 Chew (RCT) 25% 0.75 [0.26-2.10] hosp. 6/159 8/158 Priest (PSM) 0% 1.00 [0.33-3.07] death 6/379 6/379 Tau​2 = 0.29, I​2 = 45.8%, p = 0.35 Late treatment 29% 0.71 [0.35-1.44] 27/2,724 39/2,754 29% improvement Lilly (RCT) 57% 0.43 [0.28-0.67] symp. case 483 (n) 482 (n) Improvement, RR [CI] Treatment Control Tau​2 = 0.00, I​2 = 0.0%, p = 0.00021 Prophylaxis 57% 0.43 [0.28-0.67] 0/483 0/482 57% improvement All studies 55% 0.45 [0.29-0.70] 42/5,278 165/19,145 55% improvement 14 bamlanivimab/etesevimab COVID-19 studies c19ly.com May 2022 Tau​2 = 0.28, I​2 = 47.9%, p = 0.00041 Effect extraction pre-specified(most serious outcome, see appendix) Favors bamlanivimab/e.. Favors control
Figure 4. Random effects meta-analysis for all studies with pooled effects. This plot shows pooled effects, discussion can be found in the heterogeneity section, and results for specific outcomes can be found in the individual outcome analyses. Effect extraction is pre-specified, using the most serious outcome reported. For details of effect extraction see the appendix.
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ Webb 80% 0.20 [0.03-1.46] 1/479 57/5,536 Improvement, RR [CI] Treatment Control Dougan (DB RCT) 95% 0.05 [0.00-0.90] 0/518 9/517 Cooper 45% 0.55 [0.07-3.99] 1/473 33/8,534 Rubin 44% 0.56 [0.07-4.33] 1/191 10/1,066 Delasobera -119% 2.19 [0.23-20.9] 3/253 1/185 Dale 89% 0.11 [0.02-0.55] 5/56 9/19 Tau​2 = 0.64, I​2 = 42.3%, p = 0.012 Early treatment 72% 0.28 [0.10-0.76] 11/1,970 119/15,857 72% improvement ACTIV-3/T.. (RCT) -100% 2.00 [0.69-5.83] 9/163 5/151 Improvement, RR [CI] Treatment Control Bariola 67% 0.33 [0.10-1.01] 4/234 12/234 Ganesh 74% 0.26 [0.05-1.20] 2/1,789 8/1,832 Priest (PSM) 0% 1.00 [0.33-3.07] 6/379 6/379 Tau​2 = 0.54, I​2 = 59.3%, p = 0.45 Late treatment 31% 0.69 [0.27-1.76] 21/2,565 31/2,596 31% improvement All studies 56% 0.44 [0.20-0.95] 32/4,535 150/18,453 56% improvement 10 bamlanivimab/etesevimab COVID-19 mortality results c19ly.com May 2022 Tau​2 = 0.87, I​2 = 61.6%, p = 0.035 Favors bamlanivimab/e.. Favors control
Figure 5. Random effects meta-analysis for mortality results.
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ Cooper 58% 0.42 [0.10-1.72] 2/473 85/8,534 Improvement, RR [CI] Treatment Control Tau​2 = 0.00, I​2 = 0.0%, p = 0.23 Early treatment 58% 0.42 [0.10-1.72] 2/473 85/8,534 58% improvement Ganesh 49% 0.51 [0.24-1.09] 10/1,789 20/1,832 Improvement, RR [CI] Treatment Control Tau​2 = 0.00, I​2 = 0.0%, p = 0.082 Late treatment 49% 0.51 [0.24-1.09] 10/1,789 20/1,832 49% improvement All studies 51% 0.49 [0.25-0.95] 12/2,262 105/10,366 51% improvement 2 bamlanivimab/etesevimab COVID-19 ICU results c19ly.com May 2022 Tau​2 = 0.00, I​2 = 0.0%, p = 0.036 Favors bamlanivimab/e.. Favors control
Figure 6. Random effects meta-analysis for ICU admission.
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ Webb 53% 0.47 [0.31-0.72] hosp. 22/479 538/5,536 Improvement, RR [CI] Treatment Control Cooper 5% 0.95 [0.69-1.30] hosp. 37/473 703/8,534 Rubin 65% 0.35 [0.12-0.94] hosp. 16/191 121/1,065 Delasobera 52% 0.48 [0.27-0.85] hosp. 17/253 26/185 Wilden 51% 0.49 [0.23-1.04] hosp. n/a n/a Tau​2 = 0.16, I​2 = 73.0%, p = 0.0028 Early treatment 47% 0.53 [0.35-0.80] 92/1,396 1,388/15,320 47% improvement Bariola 61% 0.39 [0.22-0.70] hosp. 15/234 39/234 Improvement, RR [CI] Treatment Control Ganesh 37% 0.63 [0.43-0.91] hosp. 44/1,789 72/1,832 Chew (RCT) 25% 0.75 [0.26-2.10] hosp. 6/159 8/158 Priest (PSM) -4% 1.04 [0.78-1.38] hosp. 79/379 76/379 Tau​2 = 0.14, I​2 = 72.8%, p = 0.093 Late treatment 32% 0.68 [0.43-1.07] 144/2,561 195/2,603 32% improvement All studies 41% 0.59 [0.44-0.79] 236/3,957 1,583/17,923 41% improvement 9 bamlanivimab/etesevimab COVID-19 hospitalization results c19ly.com May 2022 Tau​2 = 0.13, I​2 = 72.4%, p = 0.00052 Favors bamlanivimab/e.. Favors control
Figure 7. Random effects meta-analysis for hospitalization.
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ Delasobera 20% 0.80 [0.46-1.40] 23/253 21/185 Improvement, RR [CI] Treatment Control Dale 86% 0.14 [0.04-0.52] 6/56 10/19 Tau​2 = 1.42, I​2 = 91.1%, p = 0.23 Early treatment 66% 0.34 [0.06-1.93] 29/309 31/204 66% improvement All studies 66% 0.34 [0.06-1.93] 29/309 31/204 66% improvement 2 bamlanivimab/etesevimab COVID-19 progression results c19ly.com May 2022 Tau​2 = 1.42, I​2 = 91.1%, p = 0.23 Favors bamlanivimab/e.. Favors control
Figure 8. Random effects meta-analysis for progression.
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ Dougan (DB RCT) 11% 0.89 [0.82-0.97] recov. time 518 (n) 517 (n) Improvement, RR [CI] Treatment Control Tau​2 = 0.00, I​2 = 0.0%, p = 0.0071 Early treatment 11% 0.89 [0.82-0.97] 0/518 0/517 11% improvement Chew (RCT) -14% 1.14 [0.00-455] recov. time 48 (n) 46 (n) Improvement, RR [CI] Treatment Control Tau​2 = 0.00, I​2 = 0.0%, p = 0.97 Late treatment -14% 1.14 [0.00-455] 0/48 0/46 -14% improvement All studies 11% 0.89 [0.82-0.97] 0/566 0/563 11% improvement 2 bamlanivimab/etesevimab COVID-19 recovery results c19ly.com May 2022 Tau​2 = 0.00, I​2 = 0.0%, p = 0.0071 Favors bamlanivimab/e.. Favors control
Figure 9. Random effects meta-analysis for recovery.
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ Lilly (RCT) 57% 0.43 [0.28-0.67] symp. case 483 (n) 482 (n) Improvement, RR [CI] Treatment Control Tau​2 = 0.00, I​2 = 0.0%, p = 0.00021 Prophylaxis 57% 0.43 [0.28-0.67] 0/483 0/482 57% improvement All studies 57% 0.43 [0.28-0.67] 0/483 0/482 57% improvement 1 bamlanivimab/etesevimab COVID-19 case result c19ly.com May 2022 Tau​2 = 0.00, I​2 = 0.0%, p = 0.00021 Favors bamlanivimab/e.. Favors control
Figure 10. Random effects meta-analysis for cases.
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ Dougan (DB RCT) 67% 0.33 [0.25-0.45] viral+ 50/508 147/499 Improvement, RR [CI] Treatment Control Tau​2 = 0.00, I​2 = 0.0%, p < 0.0001 Early treatment 67% 0.33 [0.25-0.45] 50/508 147/499 67% improvement Chew (RCT) 26% 0.74 [0.62-0.90] viral load 48 (n) 46 (n) Improvement, RR [CI] Treatment Control Tau​2 = 0.00, I​2 = 0.0%, p = 0.002 Late treatment 26% 0.74 [0.62-0.90] 0/48 0/46 26% improvement All studies 50% 0.50 [0.23-1.10] 50/556 147/545 50% improvement 2 bamlanivimab/etesevimab COVID-19 viral clearance results c19ly.com May 2022 Tau​2 = 0.30, I​2 = 95.0%, p = 0.085 Favors bamlanivimab/e.. Favors control
Figure 11. Random effects meta-analysis for viral clearance.
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ Gottlieb (RCT) 71% 0.29 [0.09-0.96] hosp./ER 4/101 7/52 Improvement, RR [CI] Treatment Control Webb 80% 0.20 [0.03-1.46] death 1/479 57/5,536 Dougan (DB RCT) 95% 0.05 [0.00-0.90] death 0/518 9/517 Cooper 45% 0.55 [0.07-3.99] death 1/473 33/8,534 Rubin 44% 0.56 [0.07-4.33] death 1/191 10/1,066 Delasobera -119% 2.19 [0.23-20.9] death 3/253 1/185 Dale 89% 0.11 [0.02-0.55] death 5/56 9/19 Wilden 51% 0.49 [0.23-1.04] hosp. n/a n/a Tau​2 = 0.31, I​2 = 37.9%, p = 0.00058 Early treatment 69% 0.31 [0.16-0.60] 15/2,071 126/15,909 69% improvement ACTIV-3/T.. (RCT) -100% 2.00 [0.69-5.83] death 9/163 5/151 Improvement, RR [CI] Treatment Control Ganesh 74% 0.26 [0.05-1.20] death 2/1,789 8/1,832 Priest (PSM) 0% 1.00 [0.33-3.07] death 6/379 6/379 Tau​2 = 0.50, I​2 = 56.4%, p = 0.86 Late treatment 10% 0.90 [0.31-2.64] 17/2,331 19/2,362 10% improvement All studies 56% 0.44 [0.23-0.84] 32/4,402 145/18,271 56% improvement 11 bamlanivimab/etesevimab COVID-19 peer reviewed trials c19ly.com May 2022 Tau​2 = 0.62, I​2 = 57.8%, p = 0.013 Effect extraction pre-specified(most serious outcome, see appendix) Favors bamlanivimab/e.. Favors control
Figure 12. Random effects meta-analysis for peer reviewed studies. [Zeraatkar] analyze 356 COVID-19 trials, finding no significant evidence that peer-reviewed studies are more trustworthy. They also show extremely slow review times during a pandemic. Authors recommend using preprint evidence, with appropriate checks for potential falsified data, which provides higher certainty much earlier. Effect extraction is pre-specified, using the most serious outcome reported, see the appendix for details.
Exclusions
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 may underemphasize serious issues not captured in the checklists, overemphasize issues unlikely to alter outcomes in specific cases (for example, lack of blinding for an objective mortality outcome, or certain specifics of randomization with a very large effect size), or be easily influenced by potential bias. However, they can also be very high quality.
The studies excluded are as below. Figure 13 shows a forest plot for random effects meta-analysis of all studies after exclusions.
[Cooper], unadjusted results with no group details.
[Rubin], significant unadjusted confounding possible.
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ Gottlieb (RCT) 71% 0.29 [0.09-0.96] hosp./ER 4/101 7/52 Improvement, RR [CI] Treatment Control Webb 80% 0.20 [0.03-1.46] death 1/479 57/5,536 Dougan (DB RCT) 95% 0.05 [0.00-0.90] death 0/518 9/517 Delasobera -119% 2.19 [0.23-20.9] death 3/253 1/185 Dale 89% 0.11 [0.02-0.55] death 5/56 9/19 Wilden 51% 0.49 [0.23-1.04] hosp. n/a n/a Tau​2 = 0.49, I​2 = 52.6%, p = 0.0021 Early treatment 72% 0.28 [0.12-0.63] 13/1,407 83/6,309 72% improvement ACTIV-3/T.. (RCT) -100% 2.00 [0.69-5.83] death 9/163 5/151 Improvement, RR [CI] Treatment Control Bariola 67% 0.33 [0.10-1.01] death 4/234 12/234 Ganesh 74% 0.26 [0.05-1.20] death 2/1,789 8/1,832 Chew (RCT) 25% 0.75 [0.26-2.10] hosp. 6/159 8/158 Priest (PSM) 0% 1.00 [0.33-3.07] death 6/379 6/379 Tau​2 = 0.29, I​2 = 45.8%, p = 0.35 Late treatment 29% 0.71 [0.35-1.44] 27/2,724 39/2,754 29% improvement Lilly (RCT) 57% 0.43 [0.28-0.67] symp. case 483 (n) 482 (n) Improvement, RR [CI] Treatment Control Tau​2 = 0.00, I​2 = 0.0%, p = 0.00021 Prophylaxis 57% 0.43 [0.28-0.67] 0/483 0/482 57% improvement All studies 56% 0.44 [0.27-0.72] 40/4,614 122/9,545 56% improvement 12 bamlanivimab/etesevimab COVID-19 studies after exclusions c19ly.com May 2022 Tau​2 = 0.34, I​2 = 55.7%, p = 0.00098 Effect extraction pre-specified(most serious outcome, see appendix) Favors bamlanivimab/e.. Favors control
Figure 13. Random effects meta-analysis for all studies after exclusions. This plot shows pooled effects, discussion can be found in the heterogeneity section, and results for specific outcomes can be found in the individual outcome analyses. Effect extraction is pre-specified, using the most serious outcome reported. For details of effect extraction see the appendix.
Randomized Controlled Trials (RCTs)
Figure 14 shows the distribution of results for Randomized Controlled Trials and other studies, and a chronological history of results. The median effect size for RCTs is 57% improvement, compared to 51% for other studies. Figure 15 and 16 show forest plots for a random effects meta-analysis of all Randomized Controlled Trials and RCT mortality results. Table 3 summarizes the results.
Figure 14. The distribution of results for Randomized Controlled Trials and other studies, and a chronological history of results.
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ Gottlieb (RCT) 71% 0.29 [0.09-0.96] hosp./ER 4/101 7/52 Improvement, RR [CI] Treatment Control Dougan (DB RCT) 95% 0.05 [0.00-0.90] death 0/518 9/517 Tau​2 = 0.25, I​2 = 16.9%, p = 0.023 Early treatment 79% 0.21 [0.05-0.81] 4/619 16/569 79% improvement ACTIV-3/T.. (RCT) -100% 2.00 [0.69-5.83] death 9/163 5/151 Improvement, RR [CI] Treatment Control Chew (RCT) 25% 0.75 [0.26-2.10] hosp. 6/159 8/158 Tau​2 = 0.20, I​2 = 40.7%, p = 0.71 Late treatment -21% 1.21 [0.46-3.18] 15/322 13/309 -21% improvement Lilly (RCT) 57% 0.43 [0.28-0.67] symp. case 483 (n) 482 (n) Improvement, RR [CI] Treatment Control Tau​2 = 0.00, I​2 = 0.0%, p = 0.00021 Prophylaxis 57% 0.43 [0.28-0.67] 0/483 0/482 57% improvement All studies 45% 0.55 [0.26-1.18] 19/1,424 29/1,360 45% improvement 5 bamlanivimab/etesevimab COVID-19 Randomized Controlled Trials c19ly.com May 2022 Tau​2 = 0.42, I​2 = 62.4%, p = 0.12 Effect extraction pre-specified(most serious outcome, see appendix) Favors bamlanivimab/e.. Favors control
Figure 15. Random effects meta-analysis for all Randomized Controlled Trials. This plot shows pooled effects, discussion can be found in the heterogeneity section, and results for specific outcomes can be found in the individual outcome analyses. Effect extraction is pre-specified, using the most serious outcome reported. For details of effect extraction see the appendix.
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ Dougan (DB RCT) 95% 0.05 [0.00-0.90] 0/518 9/517 Improvement, RR [CI] Treatment Control Tau​2 = 0.00, I​2 = 0.0%, p = 0.042 Early treatment 95% 0.05 [0.00-0.90] 0/518 9/517 95% improvement ACTIV-3/T.. (RCT) -100% 2.00 [0.69-5.83] 9/163 5/151 Improvement, RR [CI] Treatment Control Tau​2 = 0.00, I​2 = 0.0%, p = 0.21 Late treatment -100% 2.00 [0.69-5.83] 9/163 5/151 -100% improvement All studies 58% 0.42 [0.01-14.2] 9/681 14/668 58% improvement 2 bamlanivimab/etesevimab COVID-19 RCT mortality results c19ly.com May 2022 Tau​2 = 5.42, I​2 = 81.9%, p = 0.64 Favors bamlanivimab/e.. Favors control
Figure 16. Random effects meta-analysis for RCT mortality results.
Treatment timeNumber of studies reporting positive effects Total number of studiesPercentage of studies reporting positive effects Random effects meta-analysis results
Randomized Controlled Trials 4 5 80.0% 45% improvement
RR 0.55 [0.26‑1.18]
p = 0.12
RCT mortality results 1 2 50.0% 58% improvement
RR 0.42 [0.01‑14.21]
p = 0.64
Table 3. Randomized Controlled Trial results.
Heterogeneity
Heterogeneity in COVID-19 studies arises from many factors including:
Treatment delay.
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]. Figure 17 shows a mixed-effects meta-regression for efficacy as a function of treatment delay in COVID-19 studies from 42 treatments, showing that efficacy declines rapidly with treatment delay. Early treatment is critical for COVID-19.
Figure 17. Meta-regression showing efficacy as a function of treatment delay in COVID-19 studies from 42 treatments. Early treatment is critical.
Patient demographics.
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]).
Effect measured.
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.
Variants.
There are many different variants of SARS-CoV-2 and efficacy may depend critically on the distribution of variants encountered by the patients in a study. 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 viral entry process for the omicron variant has moved towards TMPRSS2-independent fusion, suggesting that TMPRSS2 inhibitors may be less effective [Peacock, Willett].
Regimen.
Effectiveness may depend strongly on the dosage and treatment regimen.
Treatments.
The use of other treatments may significantly affect outcomes, including anything from supplements, other medications, or other kinds of treatment such as prone positioning.
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 the treatment may be very effective when used earlier.
In general, by combining heterogeneous studies, as all meta analyses do, we run the risk of obscuring an effect by including studies where the treatment is less effective, not effective, or harmful.
When including studies where a treatment is less effective we expect the estimated effect size to be lower than that for the optimal case. We do not a priori expect that pooling all studies will create a positive result for an effective treatment. 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.
Discussion
Publication bias.
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). For bamlanivimab/etesevimab, there is currently not enough data to evaluate publication bias with high confidence.
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.
78% of retrospective studies report a statistically significant positive effect for one or more outcomes, compared to 80% of prospective studies, showing similar results. The median effect size for retrospective studies is 51% improvement, compared to 57% for prospective studies, suggesting a potential bias towards publishing results showing lower efficacy. Figure 18 shows a scatter plot of results for prospective and retrospective studies.
Figure 18. Prospective vs. retrospective studies.
Funnel plot analysis.
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 19 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 19. Example funnel plot analysis for simulated perfect trials.
Early/late vs. mild/moderate/severe.
Some analyses classify treatment based on early/late administration (as we do here), while others distinguish between mild/moderate/severe cases. We note that 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.
Conclusion
Bamlanivimab/etesevimab is an effective treatment for COVID-19. Statistically significant improvements are seen for mortality, ICU admission, hospitalization, recovery, and cases. 11 studies from 9 independent teams (all from the same country) show statistically significant improvements in isolation (4 for the most serious outcome). Meta analysis using the most serious outcome reported shows 55% [30‑71%] improvement. Results are similar for Randomized Controlled Trials, similar after exclusions, and similar for peer-reviewed studies. Early treatment is more effective than late treatment. Results are robust — in exclusion sensitivity analysis 6 of 14 studies must be excluded to avoid finding statistically significant efficacy in pooled analysis.
Efficacy is highly variant dependent. In Vitro studies suggest a lack of efficacy for omicron [Liu, Sheward, VanBlargan]. Monoclonal antibody use with variants can be associated with prolonged viral loads, clinical deterioration, and immune escape [Choudhary].
Study Notes
0 0.5 1 1.5 2+ Mortality -100% Improvement Relative Risk c19ly.com ACTIV-3/TICO et al. NCT04501978 Bamlaniv../e.. RCT LATE Favors bamlanivimab/e.. Favors control
[ACTIV-3/TICO] Late stage RCT of LY-CoV555 added to remdesivir, showing non-statistically significant higher mortality with the addition of LY-CoV555. NCT04501978.
0 0.5 1 1.5 2+ Mortality 67% Improvement Relative Risk Death/hospitalization 64% primary Hospitalization 61% c19ly.com Bariola et al. Bamlaniv../e.. for COVID-19 LATE Favors bamlanivimab/e.. Favors control
[Bariola] Retrospective 234 patients receiving bamlanivimab and 234 matched controls, showing lower hospitalization and mortality with treatment. Greater benefit was seen with administration within 4 days of their positive COVID-19 test.
0 0.5 1 1.5 2+ Hospitalization 25% Improvement Relative Risk Hospitalization (b) 52% Hospitalization (c) -1% Time to symptom improvement -14% primary Time to symptom improv.. (b) -17% primary Viral load 26% Viral load (b) 35% c19ly.com Chew et al. NCT04518410 Bamlaniv../e.. RCT LATE TREATMENT Favors bamlanivimab/e.. Favors control
[Chew] RCT 317 outpatients in the USA showing faster viral load and inflammatory biomarker decline, but no significant differences in clinical outcomes. ACTIV-2/A5401. NCT04518410. Supplementary data is not currently available.
0 0.5 1 1.5 2+ Mortality 45% unadjusted Improvement Relative Risk ICU admission 58% unadjusted Hospitalization 5% primary, unadjusted Mortality (b) -17% unadjusted ICU admission (b) 9% unadjusted Hospitalization (b) 28% unadjusted c19ly.com Cooper et al. Bamlaniv../e.. for COVID-19 EARLY Favors bamlanivimab/e.. 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 89% Improvement Relative Risk