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Famotidine for COVID-19: real-time meta analysis of 22 studies
Covid Analysis, May 22, 2022, DRAFT
https://c19early.com/fmmeta.html
0 0.5 1 1.5+ All studies 14% 22 76,267 Improvement, Studies, Patients Relative Risk Mortality 16% 15 70,199 Ventilation 12% 1 178 ICU admission -70% 3 846 Hospitalization 14% 4 377 Recovery 11% 5 739 Cases 0% 3 307 RCTs 33% 3 253 Peer-reviewed 13% 21 76,247 Prophylaxis 13% 9 28,827 Early 48% 1 55 Late 8% 12 47,385 Famotidine for COVID-19 c19early.com/fm May 2022 Favorsfamotidine Favorscontrol after exclusions
Statistically significant improvements are seen for mortality, hospitalization, and recovery. 11 studies from 11 independent teams in 5 different countries show statistically significant improvements in isolation (7 for the most serious outcome).
Meta analysis using the most serious outcome reported shows 14% [2‑24%] improvement. Results are better for Randomized Controlled Trials, similar after exclusions, and similar for peer-reviewed studies. Early treatment is more effective than late treatment.
In exclusion sensitivity analysis, statistical significance is lost after excluding only one of 22 studies in pooled analysis.
0 0.5 1 1.5+ All studies 14% 22 76,267 Improvement, Studies, Patients Relative Risk Mortality 16% 15 70,199 Ventilation 12% 1 178 ICU admission -70% 3 846 Hospitalization 14% 4 377 Recovery 11% 5 739 Cases 0% 3 307 RCTs 33% 3 253 Peer-reviewed 13% 21 76,247 Prophylaxis 13% 9 28,827 Early 48% 1 55 Late 8% 12 47,385 Famotidine for COVID-19 c19early.com/fm May 2022 Favorsfamotidine Favorscontrol after exclusions
While many treatments have some level of efficacy, they do not replace vaccines and other measures to avoid infection. None of the famotidine studies show zero events in the treatment arm. Multiple treatments are typically used in combination, and other treatments are significantly 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
Famotidine reduces risk for COVID-19 with very high confidence for hospitalization and recovery, and high confidence for mortality and in pooled analysis.
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+ Brennan (DB RCT) 48% 0.52 [0.20-1.32] no recov. 5/27 10/28 Improvement, RR [CI] Treatment Control Tau​2 = 0.00, I​2 = 0.0%, p = 0.17 Early treatment 48% 0.52 [0.20-1.32] 5/27 10/28 48% improvement Shoaibi -3% 1.03 [0.89-1.18] death 1,816 (n) 26,820 (n) Improvement, RR [CI] Treatment Control Zhou (PSM) -81% 1.81 [1.28-2.58] severe case 72/519 198/2,595 Yeramaneni -59% 1.59 [0.94-2.71] death 410 (n) 746 (n) Mura (PSM) 21% 0.79 [0.65-0.96] death 563 (n) 563 (n) Samim.. (SB RCT) 33% 0.67 [0.45-0.98] hosp. time 10 (n) 10 (n) Elhadi (ICU) 7% 0.93 [0.73-1.17] death 34/60 247/405 ICU patients Taşdemir 45% 0.55 [0.20-1.55] death 5/85 10/94 OT​1 Kuno (PSM) 0% 1.00 [0.86-1.17] death 1,593 (n) 7,972 (n) Stolow -519% 6.19 [2.10-18.3] death 137 (n) 352 (n) Wagner 70% 0.30 [0.20-0.44] death 638 (n) 819 (n) Pahwani (RCT) 11% 0.89 [0.36-2.20] death 8/89 9/89 Siraj 36% 0.64 [0.48-0.83] death 183/711 122/289 Tau​2 = 0.13, I​2 = 89.0%, p = 0.48 Late treatment 8% 0.92 [0.72-1.16] 302/6,631 586/40,754 8% improvement Freedberg (PSM) 57% 0.43 [0.21-0.86] death/int. 8/84 332/1,536 Improvement, RR [CI] Treatment Control Mather (PSM) 61% 0.39 [0.20-0.74] death 83 (n) 689 (n) Balouch 22% 0.78 [0.36-1.51] symp. case 18/80 49/227 Yeramaneni 51% 0.49 [0.16-1.52] death 351 (n) 6,807 (n) Cheung -34% 1.34 [0.24-6.06] severe case 23 (n) 929 (n) Fung 0% 1.00 [0.96-1.04] death population-based cohort Razjouyan 27% 0.73 [0.59-0.92] death 93 (n) 9,981 (n) Wallace -11% 1.11 [0.89-1.35] death 98/423 1,436/7,521 MacFadden 7% 0.93 [0.84-1.03] cases n/a n/a Tau​2 = 0.02, I​2 = 70.2%, p = 0.048 Prophylaxis 13% 0.87 [0.76-1.00] 124/1,137 1,817/27,690 13% improvement All studies 14% 0.86 [0.76-0.98] 431/7,795 2,413/68,472 14% improvement 22 famotidine COVID-19 studies c19early.com/fm May 2022 Tau​2 = 0.05, I​2 = 84.0%, p = 0.019 Effect extraction pre-specified(most serious outcome, see appendix) 1 OT: comparison with other treatment Favors famotidine 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 famotidine 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.
Preclinical Research
An In Vitro study supports the efficacy of famotidine [Loffredo].
Preclinical research is an important part of the development of treatments, however results may be very different in clinical trials. Preclinical results are not used in this paper.
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, and 11 show forest plots for a random effects meta-analysis of all studies with pooled effects, mortality results, ventilation, ICU admission, hospitalization, recovery, cases, and peer reviewed studies.
0 0.5 1 1.5+ ALL STUDIES MORTALITY VENTILATION ICU ADMISSION HOSPITALIZATION RECOVERY CASES RANDOMIZED CONTROLLED TRIALS PEER-REVIEWED After Exclusions ALL STUDIES All Prophylaxis Early Late Famotidine for COVID-19 C19EARLY.COM/FM 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 1 1 100% 48% improvement
RR 0.52 [0.20‑1.32]
p = 0.17
Late treatment 7 12 58.3% 8% improvement
RR 0.92 [0.72‑1.16]
p = 0.48
Prophylaxis 6 9 66.7% 13% improvement
RR 0.87 [0.76‑1.00]
p = 0.048
All studies 14 22 63.6% 14% improvement
RR 0.86 [0.76‑0.98]
p = 0.019
Table 1. Results by treatment stage.
Studies Early treatment Late treatment Prophylaxis PatientsAuthors
All studies 2248% [-32‑80%]8% [-16‑28%]13% [0‑24%] 76,267 188
With exclusions 1948% [-32‑80%]6% [-24‑29%]21% [3‑36%] 75,623 154
Peer-reviewed 2148% [-32‑80%]5% [-22‑27%]13% [0‑24%] 76,247 182
Randomized Controlled TrialsRCTs 348% [-32‑80%]30% [0‑51%] 253 45
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+ Brennan (DB RCT) 48% 0.52 [0.20-1.32] no recov. 5/27 10/28 Improvement, RR [CI] Treatment Control Tau​2 = 0.00, I​2 = 0.0%, p = 0.17 Early treatment 48% 0.52 [0.20-1.32] 5/27 10/28 48% improvement Shoaibi -3% 1.03 [0.89-1.18] death 1,816 (n) 26,820 (n) Improvement, RR [CI] Treatment Control Zhou (PSM) -81% 1.81 [1.28-2.58] severe case 72/519 198/2,595 Yeramaneni -59% 1.59 [0.94-2.71] death 410 (n) 746 (n) Mura (PSM) 21% 0.79 [0.65-0.96] death 563 (n) 563 (n) Samim.. (SB RCT) 33% 0.67 [0.45-0.98] hosp. time 10 (n) 10 (n) Elhadi (ICU) 7% 0.93 [0.73-1.17] death 34/60 247/405 ICU patients Taşdemir 45% 0.55 [0.20-1.55] death 5/85 10/94 OT​1 Kuno (PSM) 0% 1.00 [0.86-1.17] death 1,593 (n) 7,972 (n) Stolow -519% 6.19 [2.10-18.3] death 137 (n) 352 (n) Wagner 70% 0.30 [0.20-0.44] death 638 (n) 819 (n) Pahwani (RCT) 11% 0.89 [0.36-2.20] death 8/89 9/89 Siraj 36% 0.64 [0.48-0.83] death 183/711 122/289 Tau​2 = 0.13, I​2 = 89.0%, p = 0.48 Late treatment 8% 0.92 [0.72-1.16] 302/6,631 586/40,754 8% improvement Freedberg (PSM) 57% 0.43 [0.21-0.86] death/int. 8/84 332/1,536 Improvement, RR [CI] Treatment Control Mather (PSM) 61% 0.39 [0.20-0.74] death 83 (n) 689 (n) Balouch 22% 0.78 [0.36-1.51] symp. case 18/80 49/227 Yeramaneni 51% 0.49 [0.16-1.52] death 351 (n) 6,807 (n) Cheung -34% 1.34 [0.24-6.06] severe case 23 (n) 929 (n) Fung 0% 1.00 [0.96-1.04] death population-based cohort Razjouyan 27% 0.73 [0.59-0.92] death 93 (n) 9,981 (n) Wallace -11% 1.11 [0.89-1.35] death 98/423 1,436/7,521 MacFadden 7% 0.93 [0.84-1.03] cases n/a n/a Tau​2 = 0.02, I​2 = 70.2%, p = 0.048 Prophylaxis 13% 0.87 [0.76-1.00] 124/1,137 1,817/27,690 13% improvement All studies 14% 0.86 [0.76-0.98] 431/7,795 2,413/68,472 14% improvement 22 famotidine COVID-19 studies c19early.com/fm May 2022 Tau​2 = 0.05, I​2 = 84.0%, p = 0.019 Effect extraction pre-specified(most serious outcome, see appendix) 1 OT: comparison with other treatment Favors famotidine 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+ Shoaibi -3% 1.03 [0.89-1.18] 1,816 (n) 26,820 (n) Improvement, RR [CI] Treatment Control Yeramaneni -59% 1.59 [0.94-2.71] 410 (n) 746 (n) Mura (PSM) 21% 0.79 [0.65-0.96] 563 (n) 563 (n) Elhadi (ICU) 7% 0.93 [0.73-1.17] 34/60 247/405 ICU patients Taşdemir 45% 0.55 [0.20-1.55] 5/85 10/94 OT​1 Kuno (PSM) 0% 1.00 [0.86-1.17] 1,593 (n) 7,972 (n) Stolow -519% 6.19 [2.10-18.3] 137 (n) 352 (n) Wagner 70% 0.30 [0.20-0.44] 638 (n) 819 (n) Pahwani (RCT) 11% 0.89 [0.36-2.20] 8/89 9/89 Siraj 36% 0.64 [0.48-0.83] 183/711 122/289 Tau​2 = 0.10, I​2 = 86.8%, p = 0.23 Late treatment 14% 0.86 [0.68-1.10] 230/6,102 388/38,149 14% improvement Mather (PSM) 61% 0.39 [0.20-0.74] 83 (n) 689 (n) Improvement, RR [CI] Treatment Control Yeramaneni 51% 0.49 [0.16-1.52] 351 (n) 6,807 (n) Fung 0% 1.00 [0.96-1.04] population-based cohort Razjouyan 27% 0.73 [0.59-0.92] 93 (n) 9,981 (n) Wallace -11% 1.11 [0.89-1.35] 98/423 1,436/7,521 Tau​2 = 0.04, I​2 = 78.4%, p = 0.16 Prophylaxis 15% 0.85 [0.68-1.06] 98/950 1,436/24,998 15% improvement All studies 16% 0.84 [0.73-0.98] 328/7,052 1,824/63,147 16% improvement 15 famotidine COVID-19 mortality results c19early.com/fm May 2022 Tau​2 = 0.05, I​2 = 85.2%, p = 0.026 1 OT: comparison with other treatment Favors famotidine 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+ Pahwani (RCT) 12% 0.88 [0.53-1.45] 21/89 24/89 Improvement, RR [CI] Treatment Control Tau​2 = 0.00, I​2 = 0.0%, p = 0.62 Late treatment 12% 0.88 [0.53-1.45] 21/89 24/89 12% improvement All studies 12% 0.88 [0.53-1.45] 21/89 24/89 12% improvement 1 famotidine COVID-19 mechanical ventilation result c19early.com/fm May 2022 Tau​2 = 0.00, I​2 = 0.0%, p = 0.62 Favors famotidine Favors control
Figure 6. Random effects meta-analysis for ventilation.
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ Taşdemir 37% 0.63 [0.28-1.43] 8/85 14/94 OT​1 Improvement, RR [CI] Treatment Control Stolow -2390% 24.90 [3.70-168] 137 (n) 352 (n) Pahwani (RCT) 10% 0.90 [0.51-1.58] 18/89 20/89 Tau​2 = 1.10, I​2 = 83.7%, p = 0.45 Late treatment -70% 1.70 [0.44-6.51] 26/311 34/535 -70% improvement All studies -70% 1.70 [0.44-6.51] 26/311 34/535 -70% improvement 3 famotidine COVID-19 ICU results c19early.com/fm May 2022 Tau​2 = 1.10, I​2 = 83.7%, p = 0.45 1 OT: comparison with other treatment Favors famotidine Favors control
Figure 7. Random effects meta-analysis for ICU admission.
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ Samim.. (SB RCT) 33% 0.67 [0.45-0.98] hosp. time 10 (n) 10 (n) Improvement, RR [CI] Treatment Control Taşdemir 18% 0.82 [0.72-0.93] hosp. time 85 (n) 94 (n) OT​1 Pahwani (RCT) 17% 0.83 [0.79-0.89] hosp. time 89 (n) 89 (n) Tau​2 = 0.00, I​2 = 0.0%, p < 0.0001 Late treatment 17% 0.83 [0.78-0.88] 0/184 0/193 17% improvement Fung 6% 0.94 [0.91-0.97] hosp. population-based cohort Improvement, RR [CI] Treatment Control Tau​2 = 0.00, I​2 = 0.0%, p = 0.00016 Prophylaxis 6% 0.94 [0.91-0.97] 6% improvement All studies 14% 0.86 [0.78-0.95] 0/184 0/193 14% improvement 4 famotidine COVID-19 hospitalization results c19early.com/fm May 2022 Tau​2 = 0.01, I​2 = 81.7%, p = 0.0027 1 OT: comparison with other treatment Favors famotidine Favors control
Figure 8. Random effects meta-analysis for hospitalization.
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ Brennan (DB RCT) 48% 0.52 [0.20-1.32] no recov. 5/27 10/28 Improvement, RR [CI] Treatment Control Tau​2 = 0.00, I​2 = 0.0%, p = 0.17 Early treatment 48% 0.52 [0.20-1.32] 5/27 10/28 48% improvement Samim.. (SB RCT) 0% 1.00 [0.42-2.40] no recov. 5/10 5/10 Improvement, RR [CI] Treatment Control Taşdemir 20% 0.80 [0.65-0.99] recov. time 85 (n) 94 (n) OT​1 Pahwani (RCT) 10% 0.90 [0.85-0.96] recov. time 89 (n) 89 (n) Tau​2 = 0.00, I​2 = 0.0%, p = 0.00023 Late treatment 10% 0.90 [0.85-0.95] 5/184 5/193 10% improvement Balouch 37% 0.63 [0.26-1.54] recov. time 80 (n) 227 (n) Improvement, RR [CI] Treatment Control Tau​2 = 0.00, I​2 = 0.0%, p = 0.32 Prophylaxis 37% 0.63 [0.26-1.54] 0/80 0/227 37% improvement All studies 11% 0.89 [0.84-0.95] 10/291 15/448 11% improvement 5 famotidine COVID-19 recovery results c19early.com/fm May 2022 Tau​2 = 0.00, I​2 = 0.0%, p = 0.00013 1 OT: comparison with other treatment Favors famotidine 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+ Balouch 22% 0.78 [0.36-1.51] symp. case 18/80 49/227 Improvement, RR [CI] Treatment Control Fung -12% 1.12 [1.10-1.15] cases population-based cohort MacFadden 7% 0.93 [0.84-1.03] cases n/a n/a Tau​2 = 0.02, I​2 = 86.0%, p = 0.98 Prophylaxis 0% 1.00 [0.84-1.19] 18/80 49/227 0% improvement All studies 0% 1.00 [0.84-1.19] 18/80 49/227 0% improvement 3 famotidine COVID-19 case results c19early.com/fm May 2022 Tau​2 = 0.02, I​2 = 86.0%, p = 0.98 Favors famotidine 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+ Brennan (DB RCT) 48% 0.52 [0.20-1.32] no recov. 5/27 10/28 Improvement, RR [CI] Treatment Control Tau​2 = 0.00, I​2 = 0.0%, p = 0.17 Early treatment 48% 0.52 [0.20-1.32] 5/27 10/28 48% improvement Shoaibi -3% 1.03 [0.89-1.18] death 1,816 (n) 26,820 (n) Improvement, RR [CI] Treatment Control Zhou (PSM) -81% 1.81 [1.28-2.58] severe case 72/519 198/2,595 Yeramaneni -59% 1.59 [0.94-2.71] death 410 (n) 746 (n) Mura (PSM) 21% 0.79 [0.65-0.96] death 563 (n) 563 (n) Elhadi (ICU) 7% 0.93 [0.73-1.17] death 34/60 247/405 ICU patients Taşdemir 45% 0.55 [0.20-1.55] death 5/85 10/94 OT​1 Kuno (PSM) 0% 1.00 [0.86-1.17] death 1,593 (n) 7,972 (n) Stolow -519% 6.19 [2.10-18.3] death 137 (n) 352 (n) Wagner 70% 0.30 [0.20-0.44] death 638 (n) 819 (n) Pahwani (RCT) 11% 0.89 [0.36-2.20] death 8/89 9/89 Siraj 36% 0.64 [0.48-0.83] death 183/711 122/289 Tau​2 = 0.14, I​2 = 89.7%, p = 0.68 Late treatment 5% 0.95 [0.73-1.22] 302/6,621 586/40,744 5% improvement Freedberg (PSM) 57% 0.43 [0.21-0.86] death/int. 8/84 332/1,536 Improvement, RR [CI] Treatment Control Mather (PSM) 61% 0.39 [0.20-0.74] death 83 (n) 689 (n) Balouch 22% 0.78 [0.36-1.51] symp. case 18/80 49/227 Yeramaneni 51% 0.49 [0.16-1.52] death 351 (n) 6,807 (n) Cheung -34% 1.34 [0.24-6.06] severe case 23 (n) 929 (n) Fung 0% 1.00 [0.96-1.04] death population-based cohort Razjouyan 27% 0.73 [0.59-0.92] death 93 (n) 9,981 (n) Wallace -11% 1.11 [0.89-1.35] death 98/423 1,436/7,521 MacFadden 7% 0.93 [0.84-1.03] cases n/a n/a Tau​2 = 0.02, I​2 = 70.2%, p = 0.048 Prophylaxis 13% 0.87 [0.76-1.00] 124/1,137 1,817/27,690 13% improvement All studies 13% 0.87 [0.77-0.99] 431/7,785 2,413/68,462 13% improvement 21 famotidine COVID-19 peer reviewed trials c19early.com/fm May 2022 Tau​2 = 0.05, I​2 = 84.3%, p = 0.036 Effect extraction pre-specified(most serious outcome, see appendix) 1 OT: comparison with other treatment Favors famotidine Favors control
Figure 11. 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 12 shows a forest plot for random effects meta-analysis of all studies after exclusions.
[Elhadi], unadjusted results with no group details.
[Fung], not fully adjusting for the different baseline risk of systemic autoimmune patients.
[Taşdemir], excessive unadjusted differences between groups.
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ Brennan (DB RCT) 48% 0.52 [0.20-1.32] no recov. 5/27 10/28 Improvement, RR [CI] Treatment Control Tau​2 = 0.00, I​2 = 0.0%, p = 0.17 Early treatment 48% 0.52 [0.20-1.32] 5/27 10/28 48% improvement Shoaibi -3% 1.03 [0.89-1.18] death 1,816 (n) 26,820 (n) Improvement, RR [CI] Treatment Control Zhou (PSM) -81% 1.81 [1.28-2.58] severe case 72/519 198/2,595 Yeramaneni -59% 1.59 [0.94-2.71] death 410 (n) 746 (n) Mura (PSM) 21% 0.79 [0.65-0.96] death 563 (n) 563 (n) Samim.. (SB RCT) 33% 0.67 [0.45-0.98] hosp. time 10 (n) 10 (n) Kuno (PSM) 0% 1.00 [0.86-1.17] death 1,593 (n) 7,972 (n) Stolow -519% 6.19 [2.10-18.3] death 137 (n) 352 (n) Wagner 70% 0.30 [0.20-0.44] death 638 (n) 819 (n) Pahwani (RCT) 11% 0.89 [0.36-2.20] death 8/89 9/89 Siraj 36% 0.64 [0.48-0.83] death 183/711 122/289 Tau​2 = 0.15, I​2 = 90.9%, p = 0.67 Late treatment 6% 0.94 [0.71-1.24] 263/6,486 329/40,255 6% improvement Freedberg (PSM) 57% 0.43 [0.21-0.86] death/int. 8/84 332/1,536 Improvement, RR [CI] Treatment Control Mather (PSM) 61% 0.39 [0.20-0.74] death 83 (n) 689 (n) Balouch 22% 0.78 [0.36-1.51] symp. case 18/80 49/227 Yeramaneni 51% 0.49 [0.16-1.52] death 351 (n) 6,807 (n) Cheung -34% 1.34 [0.24-6.06] severe case 23 (n) 929 (n) Razjouyan 27% 0.73 [0.59-0.92] death 93 (n) 9,981 (n) Wallace -11% 1.11 [0.89-1.35] death 98/423 1,436/7,521 MacFadden 7% 0.93 [0.84-1.03] cases n/a n/a Tau​2 = 0.04, I​2 = 68.2%, p = 0.026 Prophylaxis 21% 0.79 [0.64-0.97] 124/1,137 1,817/27,690 21% improvement All studies 16% 0.84 [0.71-1.00] 392/7,650 2,156/67,973 16% improvement 19 famotidine COVID-19 studies after exclusions c19early.com/fm May 2022 Tau​2 = 0.09, I​2 = 85.3%, p = 0.046 Effect extraction pre-specified(most serious outcome, see appendix) Favors famotidine Favors control
Figure 12. 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 13 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 33% improvement, compared to 7% for other studies. Figure 14 and 15 show forest plots for a random effects meta-analysis of all Randomized Controlled Trials and RCT mortality results. Table 3 summarizes the results.
Figure 13. 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+ Brennan (DB RCT) 48% 0.52 [0.20-1.32] no recov. 5/27 10/28 Improvement, RR [CI] Treatment Control Tau​2 = 0.00, I​2 = 0.0%, p = 0.17 Early treatment 48% 0.52 [0.20-1.32] 5/27 10/28 48% improvement Samim.. (SB RCT) 33% 0.67 [0.45-0.98] hosp. time 10 (n) 10 (n) Improvement, RR [CI] Treatment Control Pahwani (RCT) 11% 0.89 [0.36-2.20] death 8/89 9/89 Tau​2 = 0.00, I​2 = 0.0%, p = 0.047 Late treatment 30% 0.70 [0.49-1.00] 8/99 9/99 30% improvement All studies 33% 0.67 [0.48-0.94] 13/126 19/127 33% improvement 3 famotidine COVID-19 Randomized Controlled Trials c19early.com/fm May 2022 Tau​2 = 0.00, I​2 = 0.0%, p = 0.019 Effect extraction pre-specified(most serious outcome, see appendix) Favors famotidine Favors control
Figure 14. 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+ Pahwani (RCT) 11% 0.89 [0.36-2.20] 8/89 9/89 Improvement, RR [CI] Treatment Control Tau​2 = 0.00, I​2 = 0.0%, p = 0.81 Late treatment 11% 0.89 [0.36-2.20] 8/89 9/89 11% improvement All studies 11% 0.89 [0.36-2.20] 8/89 9/89 11% improvement 1 famotidine COVID-19 RCT mortality result c19early.com/fm May 2022 Tau​2 = 0.00, I​2 = 0.0%, p = 0.81 Favors famotidine Favors control
Figure 15. 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 3 3 100% 33% improvement
RR 0.67 [0.48‑0.94]
p = 0.019
RCT mortality results 1 1 100% 11% improvement
RR 0.89 [0.36‑2.20]
p = 0.81
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 16 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 16. 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, however evidence suggests that there may be a negative bias for inexpensive treatments for COVID-19. Both negative and positive results are very important for COVID-19, media in many countries prioritizes negative results for inexpensive treatments (inverting the typical incentive for scientists that value media recognition), and there are many reports of difficulty publishing positive results [Boulware, Meeus, Meneguesso]. For famotidine, 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.
44% of retrospective studies report a statistically significant positive effect for one or more outcomes, compared to 75% of prospective studies, consistent with a bias toward publishing negative results. The median effect size for retrospective studies is 14% improvement, compared to 22% for prospective studies, suggesting a potential bias towards publishing results showing lower efficacy. Figure 17 shows a scatter plot of results for prospective and retrospective studies.
Figure 17. 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 18 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 18. Example funnel plot analysis for simulated perfect trials.
Conflicts of interest.
Pharmaceutical drug trials often have conflicts of interest whereby sponsors or trial staff have a financial interest in the outcome being positive. Famotidine for COVID-19 lacks this because it is off-patent, has multiple manufacturers, and is very low cost. In contrast, most COVID-19 famotidine trials have been run by physicians on the front lines with the primary goal of finding the best methods to save human lives and minimize the collateral damage caused by COVID-19. While pharmaceutical companies are careful to run trials under optimal conditions (for example, restricting patients to those most likely to benefit, only including patients that can be treated soon after onset when necessary, and ensuring accurate dosing), not all famotidine trials represent the optimal conditions for efficacy.
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.
Notes.
1 of the 22 studies compare against other treatments, which may reduce the effect seen.
Conclusion
Statistically significant improvements are seen for mortality, hospitalization, and recovery. 11 studies from 11 independent teams in 5 different countries show statistically significant improvements in isolation (7 for the most serious outcome). Meta analysis using the most serious outcome reported shows 14% [2‑24%] improvement. Results are better for Randomized Controlled Trials, similar after exclusions, and similar for peer-reviewed studies. Early treatment is more effective than late treatment. In exclusion sensitivity analysis, statistical significance is lost after excluding only one of 22 studies in pooled analysis.
Study Notes
0 0.5 1 1.5 2+ Symptomatic case 22% Improvement