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Melatonin for COVID-19: real-time meta analysis of 12 studies
Covid Analysis, January 14, 2022, DRAFT
https://c19melatonin.com/meta.html
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ All studies 63% 12 13,597 Improvement, Studies, Patients Relative Risk With exclusions 65% 11 13,149 Mortality 75% 5 1,730 ICU admission 7% 4 240 Hospitalization 54% 2 140 Recovery 50% 3 115 Cases 40% 2 11,672 RCTs 72% 5 349 RCT mortality 86% 2 254 Peer-reviewed 52% 11 12,649 Prophylaxis 40% 2 11,672 Early 78% 2 91 Late 68% 8 1,834 Melatonin for COVID-19 c19melatonin.com Jan 14, 2022 Favors melatonin Favors control
Statistically significant improvements are seen for mortality and recovery. 8 studies from 5 different countries show statistically significant improvements in isolation (6 for the most serious outcome).
Meta analysis using the most serious outcome reported shows 63% [42‑77%] improvement. Results are better for Randomized Controlled Trials, similar after exclusions, and similar for peer-reviewed studies.
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ All studies 63% 12 13,597 Improvement, Studies, Patients Relative Risk With exclusions 65% 11 13,149 Mortality 75% 5 1,730 ICU admission 7% 4 240 Hospitalization 54% 2 140 Recovery 50% 3 115 Cases 40% 2 11,672 RCTs 72% 5 349 RCT mortality 86% 2 254 Peer-reviewed 52% 11 12,649 Prophylaxis 40% 2 11,672 Early 78% 2 91 Late 68% 8 1,834 Melatonin for COVID-19 c19melatonin.com Jan 14, 2022 Favors melatonin Favors control
While many treatments have some level of efficacy, they do not replace vaccines and other measures to avoid infection. Only 17% of melatonin studies show zero events in the treatment arm.
Multiple treatments are typically used in combination, and other treatments may be more effective.
Elimination of COVID-19 is a race against viral evolution. No treatment, vaccine, or intervention is 100% available and effective for all variants. All practical, effective, and safe means should be used, including treatments, as supported by Pfizer [Pfizer]. 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.
Studies Early treatment Late treatment Prophylaxis PatientsAuthors
All studies 1278% [25‑94%]68% [43‑82%]40% [-11‑67%] 13,597 95
With exclusions 1178% [25‑94%]71% [38‑86%]40% [-11‑67%] 13,149 91
Peer-reviewed 1178% [25‑94%]53% [38‑64%]40% [-11‑67%] 12,649 92
Randomized Controlled TrialsRCTs 573% [-5‑93%]72% [22‑90%] 349 36
Percentage improvement with melatonin treatment
A
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ Lissoni 91% 0.09 [0.01-1.57] hosp. 0/30 5/30 CT​1 Improvement, RR [CI] Treatment Control Alizadeh (SB RCT) 73% 0.27 [0.07-1.05] no recov. 2/14 9/17 Tau​2 = 0.00, I​2 = 0.0%, p = 0.016 Early treatment 78% 0.22 [0.06-0.75] 2/44 14/47 78% improvement Ramlall 87% 0.13 [0.08-0.22] death 196 (n) 752 (n) Improvement, RR [CI] Treatment Control Darban (RCT) 33% 0.67 [0.14-3.17] progression 2/10 3/10 CT​1 Hosseini 48% 0.52 [0.36-0.77] recov. time 20 (n) 20 (n) Farnoosh (DB RCT) 81% 0.19 [0.01-3.65] ICU 0/24 2/20 Sánchez-González 54% 0.46 [0.28-0.71] death 24/224 53/224 Mousavi (RCT) 67% 0.33 [0.04-3.09] death 1/48 3/48 Hasan (RCT) 93% 0.07 [0.01-0.53] death 1/82 13/76 Bologna 50% 0.50 [0.13-1.86] death 3/40 6/40 Tau​2 = 0.33, I​2 = 68.7%, p = 0.00012 Late treatment 68% 0.32 [0.18-0.57] 31/644 80/1,190 68% improvement Jehi 58% 0.42 [0.26-0.68] cases 16/529 802/11,143 Improvement, RR [CI] Treatment Control Zhou (PSM) 21% 0.79 [0.65-0.94] cases Tau​2 = 0.17, I​2 = 83.5%, p = 0.1 Prophylaxis 40% 0.60 [0.33-1.11] 16/529 802/11,143 40% improvement All studies 63% 0.37 [0.23-0.58] 49/1,217 896/12,380 63% improvement 12 melatonin COVID-19 studies c19melatonin.com Jan 14, 2022 Tau​2 = 0.35, I​2 = 82.2%, p < 0.0001 Effect extraction pre-specified, see appendix 1 CT: study uses combined treatment Favors melatonin 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 melatonin 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.
Mechanisms of Action
CD147SARS-CoV-2 may enter host cells via the cluster of differentiation 147 (CD147) transmembrane protein. Melatonin inhibits the CD147 signalling pathway [Behl, Su, Wang].
Heme oxygenaseCOVID-19 risk may be related to low intracellular heme oxygenase (HO-1). Melatonin increases HO-1 and HO-1 has cytoprotective and anti-inflammatory properties [Anderson, Anderson (B), Hooper, Hooper (B), Shi].
Inhibiting brain infectionMelatonin has been shown to inhibit SARS-CoV-2 brain infection in a K18-hACE2 mouse model via allosteric binding to ACE2. [Cecon].
Limiting type I and III interferonsIn a K18-hACE2 mouse model, melatonin improved survival which may be associated with limiting lung production of type I and type III interferons [Cecon (B)].
MucormycosisMelatonin deficiency may increase the risk of mucormycosis by providing favorable conditions for growth [Sen].
Cytokine levelsMelatonin may lower pro-inflammatory cytokine levels [Zhang].
Immune regulationMelatonin has immune regulatory properties, enhancing the proliferation and maturation of natural killing cells, T and B lymphocytes, granulocytes, and monocytes [Miller, Zhang].
Sleep improvementMelatonin improves the quality of sleep which may be beneficial for COVID-19 [Lewis, Zhang].
Anti‑inflammatoryMelatonin shows anti-inflammatory effects [Zhang].
Anti‑oxidationMelatonin shows anti-oxidative effects which may be beneficial for COVID-19 [Gitto, Gitto (B), Reiter, Wu, Zhang].
Table 1. Melatonin mechanisms of action. Submit updates.
Results
Figure 3, 4, 5, 6, 7, 8, 9, and 10 show forest plots for a random effects meta-analysis of all studies with pooled effects, mortality results, ICU admission, hospitalization, progression, recovery, cases, and peer reviewed studies. Table 2 summarizes the results by treatment stage.
Treatment timeNumber of studies reporting positive effects Total number of studiesPercentage of studies reporting positive effects Random effects meta-analysis results
Early treatment 2 2 100% 78% improvement
RR 0.22 [0.06‑0.75]
p = 0.016
Late treatment 8 8 100% 68% improvement
RR 0.32 [0.18‑0.57]
p = 0.00012
Prophylaxis 2 2 100% 40% improvement
RR 0.60 [0.33‑1.11]
p = 0.1
All studies 12 12 100% 63% improvement
RR 0.37 [0.23‑0.58]
p < 0.0001
Table 2. Results by treatment stage.
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ Lissoni 91% 0.09 [0.01-1.57] hosp. 0/30 5/30 CT​1 Improvement, RR [CI] Treatment Control Alizadeh (SB RCT) 73% 0.27 [0.07-1.05] no recov. 2/14 9/17 Tau​2 = 0.00, I​2 = 0.0%, p = 0.016 Early treatment 78% 0.22 [0.06-0.75] 2/44 14/47 78% improvement Ramlall 87% 0.13 [0.08-0.22] death 196 (n) 752 (n) Improvement, RR [CI] Treatment Control Darban (RCT) 33% 0.67 [0.14-3.17] progression 2/10 3/10 CT​1 Hosseini 48% 0.52 [0.36-0.77] recov. time 20 (n) 20 (n) Farnoosh (DB RCT) 81% 0.19 [0.01-3.65] ICU 0/24 2/20 Sánchez-González 54% 0.46 [0.28-0.71] death 24/224 53/224 Mousavi (RCT) 67% 0.33 [0.04-3.09] death 1/48 3/48 Hasan (RCT) 93% 0.07 [0.01-0.53] death 1/82 13/76 Bologna 50% 0.50 [0.13-1.86] death 3/40 6/40 Tau​2 = 0.33, I​2 = 68.7%, p = 0.00012 Late treatment 68% 0.32 [0.18-0.57] 31/644 80/1,190 68% improvement Jehi 58% 0.42 [0.26-0.68] cases 16/529 802/11,143 Improvement, RR [CI] Treatment Control Zhou (PSM) 21% 0.79 [0.65-0.94] cases Tau​2 = 0.17, I​2 = 83.5%, p = 0.1 Prophylaxis 40% 0.60 [0.33-1.11] 16/529 802/11,143 40% improvement All studies 63% 0.37 [0.23-0.58] 49/1,217 896/12,380 63% improvement 12 melatonin COVID-19 studies c19melatonin.com Jan 14, 2022 Tau​2 = 0.35, I​2 = 82.2%, p < 0.0001 Effect extraction pre-specified, see appendix 1 CT: study uses combined treatment Favors melatonin Favors control
Figure 3. 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+ Ramlall 87% 0.13 [0.08-0.22] 196 (n) 752 (n) Improvement, RR [CI] Treatment Control Sánchez-González 54% 0.46 [0.28-0.71] 24/224 53/224 Mousavi (RCT) 67% 0.33 [0.04-3.09] 1/48 3/48 Hasan (RCT) 93% 0.07 [0.01-0.53] 1/82 13/76 Bologna 50% 0.50 [0.13-1.86] 3/40 6/40 Tau​2 = 0.51, I​2 = 73.5%, p = 0.001 Late treatment 75% 0.25 [0.11-0.57] 29/590 75/1,140 75% improvement All studies 75% 0.25 [0.11-0.57] 29/590 75/1,140 75% improvement 5 melatonin COVID-19 mortality results c19melatonin.com Jan 14, 2022 Tau​2 = 0.51, I​2 = 73.5%, p = 0.001 Favors melatonin Favors control
Figure 4. Random effects meta-analysis for mortality results.
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ Darban (RCT) 6% 0.94 [0.84-1.06] 10 (n) 10 (n) CT​1 Improvement, RR [CI] Treatment Control Farnoosh (DB RCT) 81% 0.19 [0.01-3.65] 0/24 2/20 Mousavi (RCT) 40% 0.60 [0.24-1.52] 6/48 10/48 Bologna 50% 0.50 [0.13-1.86] 3/40 6/40 Tau​2 = 0.00, I​2 = 0.0%, p = 0.2 Late treatment 7% 0.93 [0.83-1.04] 9/122 18/118 7% improvement All studies 7% 0.93 [0.83-1.04] 9/122 18/118 7% improvement 4 melatonin COVID-19 ICU results c19melatonin.com Jan 14, 2022 Tau​2 = 0.00, I​2 = 0.0%, p = 0.2 1 CT: study uses combined treatment Favors melatonin Favors control
Figure 5. Random effects meta-analysis for ICU admission.
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ Lissoni 91% 0.09 [0.01-1.57] hosp. 0/30 5/30 CT​1 Improvement, RR [CI] Treatment Control Tau​2 = 0.00, I​2 = 0.0%, p = 0.099 Early treatment 91% 0.09 [0.01-1.57] 0/30 5/30 91% improvement Bologna 9% 0.91 [0.83-1.00] hosp. time 40 (n) 40 (n) Improvement, RR [CI] Treatment Control Tau​2 = 0.00, I​2 = 0.0%, p = 0.054 Late treatment 9% 0.91 [0.83-1.00] 0/40 0/40 9% improvement All studies 54% 0.46 [0.06-3.62] 0/70 5/70 54% improvement 2 melatonin COVID-19 hospitalization results c19melatonin.com Jan 14, 2022 Tau​2 = 1.60, I​2 = 60.2%, p = 0.47 1 CT: study uses combined treatment Favors melatonin Favors control
Figure 6. Random effects meta-analysis for hospitalization.
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ Darban (RCT) 33% 0.67 [0.14-3.17] 2/10 3/10 CT​1 Improvement, RR [CI] Treatment Control Tau​2 = 0.00, I​2 = 0.0%, p = 0.62 Late treatment 33% 0.67 [0.14-3.17] 2/10 3/10 33% improvement All studies 33% 0.67 [0.14-3.17] 2/10 3/10 33% improvement 1 melatonin COVID-19 progression result c19melatonin.com Jan 14, 2022 Tau​2 = 0.00, I​2 = 0.0%, p = 0.62 1 CT: study uses combined treatment Favors melatonin Favors control
Figure 7. Random effects meta-analysis for progression.
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ Alizadeh (SB RCT) 73% 0.27 [0.07-1.05] no recov. 2/14 9/17 Improvement, RR [CI] Treatment Control Tau​2 = 0.00, I​2 = 0.0%, p = 0.058 Early treatment 73% 0.27 [0.07-1.05] 2/14 9/17 73% improvement Hosseini 48% 0.52 [0.36-0.77] recov. time 20 (n) 20 (n) Improvement, RR [CI] Treatment Control Farnoosh (DB RCT) 49% 0.51 [0.32-0.81] recov. time 24 (n) 20 (n) Tau​2 = 0.00, I​2 = 0.0%, p < 0.0001 Late treatment 48% 0.52 [0.39-0.70] 0/44 0/40 48% improvement All studies 50% 0.50 [0.38-0.67] 2/58 9/57 50% improvement 3 melatonin COVID-19 recovery results c19melatonin.com Jan 14, 2022 Tau​2 = 0.00, I​2 = 0.0%, p < 0.0001 Favors melatonin Favors control
Figure 8. Random effects meta-analysis for recovery.
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ Jehi 58% 0.42 [0.26-0.68] 16/529 802/11,143 Improvement, RR [CI] Treatment Control Zhou (PSM) 21% 0.79 [0.65-0.94] Tau​2 = 0.17, I​2 = 83.5%, p = 0.1 Prophylaxis 40% 0.60 [0.33-1.11] 16/529 802/11,143 40% improvement All studies 40% 0.60 [0.33-1.11] 16/529 802/11,143 40% improvement 2 melatonin COVID-19 case results c19melatonin.com Jan 14, 2022 Tau​2 = 0.17, I​2 = 83.5%, p = 0.1 Favors melatonin Favors control
Figure 9. Random effects meta-analysis for cases.
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ Lissoni 91% 0.09 [0.01-1.57] hosp. 0/30 5/30 CT​1 Improvement, RR [CI] Treatment Control Alizadeh (SB RCT) 73% 0.27 [0.07-1.05] no recov. 2/14 9/17 Tau​2 = 0.00, I​2 = 0.0%, p = 0.016 Early treatment 78% 0.22 [0.06-0.75] 2/44 14/47 78% improvement Darban (RCT) 33% 0.67 [0.14-3.17] progression 2/10 3/10 CT​1 Improvement, RR [CI] Treatment Control Hosseini 48% 0.52 [0.36-0.77] recov. time 20 (n) 20 (n) Farnoosh (DB RCT) 81% 0.19 [0.01-3.65] ICU 0/24 2/20 Sánchez-González 54% 0.46 [0.28-0.71] death 24/224 53/224 Mousavi (RCT) 67% 0.33 [0.04-3.09] death 1/48 3/48 Hasan (RCT) 93% 0.07 [0.01-0.53] death 1/82 13/76 Bologna 50% 0.50 [0.13-1.86] death 3/40 6/40 Tau​2 = 0.00, I​2 = 0.0%, p < 0.0001 Late treatment 53% 0.47 [0.36-0.62] 31/448 80/438 53% improvement Jehi 58% 0.42 [0.26-0.68] cases 16/529 802/11,143 Improvement, RR [CI] Treatment Control Zhou (PSM) 21% 0.79 [0.65-0.94] cases Tau​2 = 0.17, I​2 = 83.5%, p = 0.1 Prophylaxis 40% 0.60 [0.33-1.11] 16/529 802/11,143 40% improvement All studies 52% 0.48 [0.34-0.68] 49/1,021 896/11,628 52% improvement 11 melatonin COVID-19 peer reviewed trials c19melatonin.com Jan 14, 2022 Tau​2 = 0.12, I​2 = 58.6%, p < 0.0001 Effect extraction pre-specified, see appendix 1 CT: study uses combined treatment Favors melatonin Favors control
Figure 10. Random effects meta-analysis for peer reviewed studies. 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 11 shows a forest plot for random effects meta-analysis of all studies after exclusions.
[Sánchez-González], immortal time bias may significantly affect results.
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ Lissoni 91% 0.09 [0.01-1.57] hosp. 0/30 5/30 CT​1 Improvement, RR [CI] Treatment Control Alizadeh (SB RCT) 73% 0.27 [0.07-1.05] no recov. 2/14 9/17 Tau​2 = 0.00, I​2 = 0.0%, p = 0.016 Early treatment 78% 0.22 [0.06-0.75] 2/44 14/47 78% improvement Ramlall 87% 0.13 [0.08-0.22] death 196 (n) 752 (n) Improvement, RR [CI] Treatment Control Darban (RCT) 33% 0.67 [0.14-3.17] progression 2/10 3/10 CT​1 Hosseini 48% 0.52 [0.36-0.77] recov. time 20 (n) 20 (n) Farnoosh (DB RCT) 81% 0.19 [0.01-3.65] ICU 0/24 2/20 Mousavi (RCT) 67% 0.33 [0.04-3.09] death 1/48 3/48 Hasan (RCT) 93% 0.07 [0.01-0.53] death 1/82 13/76 Bologna 50% 0.50 [0.13-1.86] death 3/40 6/40 Tau​2 = 0.56, I​2 = 71.3%, p = 0.0016 Late treatment 71% 0.29 [0.14-0.62] 7/420 27/966 71% improvement Jehi 58% 0.42 [0.26-0.68] cases 16/529 802/11,143 Improvement, RR [CI] Treatment Control Zhou (PSM) 21% 0.79 [0.65-0.94] cases Tau​2 = 0.17, I​2 = 83.5%, p = 0.1 Prophylaxis 40% 0.60 [0.33-1.11] 16/529 802/11,143 40% improvement All studies 65% 0.35 [0.21-0.60] 25/993 843/12,156 65% improvement 11 melatonin COVID-19 studies after exclusions c19melatonin.com Jan 14, 2022 Tau​2 = 0.43, I​2 = 83.0%, p = 0.00012 Effect extraction pre-specified, see appendix 1 CT: study uses combined treatment Favors melatonin Favors control
Figure 11. 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 12 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 73% improvement, compared to 54% for other studies. Figure 13 and 14 show forest plots for a random effects meta-analysis of all Randomized Controlled Trials and RCT mortality results. Table 3 summarizes the results.
Figure 12. 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+ Alizadeh (SB RCT) 73% 0.27 [0.07-1.05] no recov. 2/14 9/17 Improvement, RR [CI] Treatment Control Tau​2 = 0.00, I​2 = 0.0%, p = 0.058 Early treatment 73% 0.27 [0.07-1.05] 2/14 9/17 73% improvement Darban (RCT) 33% 0.67 [0.14-3.17] progression 2/10 3/10 CT​1 Improvement, RR [CI] Treatment Control Farnoosh (DB RCT) 81% 0.19 [0.01-3.65] ICU 0/24 2/20 Mousavi (RCT) 67% 0.33 [0.04-3.09] death 1/48 3/48 Hasan (RCT) 93% 0.07 [0.01-0.53] death 1/82 13/76 Tau​2 = 0.02, I​2 = 2.1%, p = 0.015 Late treatment 72% 0.28 [0.10-0.78] 4/164 21/154 72% improvement All studies 72% 0.28 [0.12-0.63] 6/178 30/171 72% improvement 5 melatonin COVID-19 Randomized Controlled Trials c19melatonin.com Jan 14, 2022 Tau​2 = 0.00, I​2 = 0.0%, p = 0.002 Effect extraction pre-specified, see appendix 1 CT: study uses combined treatment Favors melatonin Favors control
Figure 13. 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+ Mousavi (RCT) 67% 0.33 [0.04-3.09] 1/48 3/48 Improvement, RR [CI] Treatment Control Hasan (RCT) 93% 0.07 [0.01-0.53] 1/82 13/76 Tau​2 = 0.02, I​2 = 1.5%, p = 0.011 Late treatment 86% 0.14 [0.03-0.64] 2/130 16/124 86% improvement All studies 86% 0.14 [0.03-0.64] 2/130 16/124 86% improvement 2 melatonin COVID-19 RCT mortality results c19melatonin.com Jan 14, 2022 Tau​2 = 0.02, I​2 = 1.5%, p = 0.011 Favors melatonin Favors control
Figure 14. Random effects meta-analysis for RCT mortality results. Effect extraction is pre-specified, using the most serious outcome reported, see the appendix for details.
Treatment timeNumber of studies reporting positive effects Total number of studiesPercentage of studies reporting positive effects Random effects meta-analysis results
Randomized Controlled Trials 5 5 100% 72% improvement
RR 0.28 [0.12‑0.63]
p = 0.002
RCT mortality results 2 2 100% 86% improvement
RR 0.14 [0.03‑0.64]
p = 0.011
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]. Other medications might be beneficial for late stage complications, while early use may not be effective or may even be harmful. Figure 15 shows an example where efficacy declines as a function of treatment delay.
Figure 15. Effectiveness may depend critically on treatment delay.
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 melatonin, 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.
The median effect size for retrospective studies is 54% improvement, compared to 73% for prospective studies, consistent with a negative publication bias. 100% of retrospective studies report a statistically significant positive effect for one or more outcomes, compared to 43% of prospective studies, consistent with a bias toward publishing positive results. Figure 16 shows a scatter plot of results for prospective and retrospective studies.
Figure 16. Prospective vs. retrospective studies.
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. Melatonin for COVID-19 lacks this because it is off-patent, has multiple manufacturers, and is very low cost. In contrast, most COVID-19 melatonin 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 melatonin 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.
2 of 12 studies combine treatments. The results of melatonin alone may differ. 1 of 5 RCTs use combined treatment.
Conclusion
Melatonin is an effective treatment for COVID-19. Statistically significant improvements are seen for mortality and recovery. 8 studies from 5 different countries show statistically significant improvements in isolation (6 for the most serious outcome). Meta analysis using the most serious outcome reported shows 63% [42‑77%] improvement. Results are better for Randomized Controlled Trials, similar after exclusions, and similar for peer-reviewed studies.
Study Notes
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ Recovery 73% Improvement Relative Risk c19melatonin.com/alizadeh.html Favors melatonin Favors control
[Alizadeh] Small RCT 31 mild/moderate COVID-19 outpatients in Iran, 14 treated with melatonin, showing improved recovery with treatment.
0 0.5 1 1.5 2+ Mortality 50% Improvement Relative Risk ICU admission 50% Hospitalization time 9% Sub-intensive hospitali.. 39% NIV time 58% High flow oxygen time 8% Sleep time 18% Delirium 33% c19melatonin.com/bologna.html Favors melatonin Favors control
[Bologna] Retrospective 40 hospitalized patients in Italy treated with melatonin and 40 control patients, showing improved sleep, reduced delirium, shorter hospitalization and oxygen times, and reduced ICU admission and mortality (not statistically significant).
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ Progression 33% Improvement Relative Risk ICU time 6% c19melatonin.com/darban.html Favors melatonin Favors control
[Darban] Small RCT in Iran with 20 ICU patients, 10 treated with high-dose vitamin C, melatonin, and zinc, not showing significant differences. IRCT20151228025732N52.
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ ICU admission 81% Improvement Relative Risk Recovery time 49% Hospital discharge 44% Time to discharge 43% c19melatonin.com/farnoosh.html Favors melatonin Favors control
[Farnoosh] RCT 44 hospitalized patients in Iran, 24 treated with melatonin, showing faster recovery with treatment. There was no mortality.
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ Mortality 93% Improvement Relative Risk c19melatonin.com/hasan.html Favors melatonin Favors control
[Hasan] RCT 158 severe condition patients in Iraq, 82 treated with melatonin, showing lower mortality, thrombosis, and sepsis with treatment.
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ Recovery time 48% Improvement Relative Risk c19melatonin.com/hosseini.html Favors melatonin Favors control
[Hosseini] 40 hospitalized patients in Iran, 20 treated with melatonin, showing faster recovery and attenuated inflammatory cytokines with treatment.
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ Case 58% Improvement Relative Risk Case (b) 100% c19melatonin.com/jehi.html Favors melatonin Favors control
[Jehi] Retrospective 11,672 patients tested for COVID-19, 818 that tested positive, showing significantly lower risk with melatonin use.
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ Hospitalization 91% Improvement Relative Risk c19melatonin.com/lissoni.html Favors melatonin Favors control
[Lissoni] Small study with 30 patients treated with melatonin, cannabidiol, and for 14 patients angiotensin 1-7, compared with an age/sex matched control group during the same period, showing lower hospitalization with treatment.
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ Mortality 67% Improvement Relative Risk ICU admission 40% c19melatonin.com/mousavi.html Favors melatonin Favors control
[Mousavi] RCT 96 hospitalized patients in Iran, 48 treated with melatonin, showing improved sleep quality and SpO2 with treatment. 3mg oral melatonin daily. Authors recommend studies with a higher dose. IRCT20200411047030N1.
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ Mortality 87% Improvement Relative Risk c19melatonin.com/ramlall.html Favors melatonin Favors control
[Ramlall] Retrospective 948 intubated patients, 196 treated with melatonin, showing lower mortality with treatment.
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ Mortality 54% Improvement Relative Risk c19melatonin.com/sanchezgonzalez.html Favors melatonin Favors control
[Sánchez-González] Retrospective 2,463 hospitalized patients in Spain, 265 treated with melatonin, showing lower mortality with treatment in PSM analysis, however these results are subject to immortal time bias. Authors excluded from the sample patients that died during the first 72 hours of admission without taking melatonin, and patients that started on melatonin in the last 7 days of their admittance, having completed 75% of their stay.
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ Case 21% Improvement Relative Risk c19melatonin.com/zhou2.html Favors melatonin Favors control
[Zhou] PSM observational study with a database of 26,779 patients in the USA, showing significantly lower risk of PCR+ with melatonin usage.
We performed ongoing searches of PubMed, medRxiv, ClinicalTrials.gov, The Cochrane Library, Google Scholar, Collabovid, Research Square, ScienceDirect, Oxford University Press, the reference lists of other studies and meta-analyses, and submissions to the site c19melatonin.com. Search terms were melatonin, filtered for papers containing the terms COVID-19, SARS-CoV-2, or coronavirus. Automated searches are performed every few hours with notification of new matches. All studies regarding the use of melatonin 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 are used. Mortality alone is preferred over combined outcomes. Outcomes with zero events in both arms were not used (the next most serious outcome is used — no studies were excluded). 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 outcome is considered more important than PCR testing 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 no room for an effective treatment to do better). 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 computed the relative risk when possible, or converted to a relative risk according to [Zhang (B)]. Reported confidence intervals and p-values were used when available, using adjusted values when provided. If multiple types of adjustments are reported including propensity score matching (PSM), the PSM results are used. 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 (3.9.9) with scipy (1.7.3), pythonmeta (1.26), numpy (1.21.4), statsmodels (0.14.0), and plotly (5.4.0).
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.
We received no funding, this research is done in our spare time. We have no affiliations with any pharmaceutical companies or political parties.
We have classified studies as early treatment if most patients are not already at a severe stage at the time of treatment, 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].
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://c19melatonin.com/meta.html.
Effect extraction follows pre-specified rules as detailed above and gives priority to more serious outcomes. Only the first (most serious) outcome is used in pooled analysis, which may differ from the effect a paper focuses on. Other outcomes are used in outcome specific analyses.
[Alizadeh], 5/29/2021, Single Blind Randomized Controlled Trial, Iran, Middle East, peer-reviewed, 6 authors. risk of no recovery, 73.0% lower, RR 0.27, p = 0.06, treatment 2 of 14 (14.3%), control 9 of 17 (52.9%), NNT 2.6, day 14. With the observed event rates, ~2 more patients per arm would result in statistical significance.
[Lissoni], 12/30/2020, prospective, Italy, Europe, peer-reviewed, 14 authors, this trial uses multiple treatments in the treatment arm (combined with cannabidiol and angiotensin 1-7) - results of individual treatments may vary. risk of hospitalization, 90.9% lower, RR 0.09, p = 0.05, treatment 0 of 30 (0.0%), control 5 of 30 (16.7%), NNT 6.0, relative risk is not 0 because of continuity correction due to zero events (with reciprocal of the contrasting arm). With the observed event rates, ~4 more patients per arm would result in statistical significance.
Effect extraction follows pre-specified rules as detailed above and gives priority to more serious outcomes. Only the first (most serious) outcome is used in pooled analysis, which may differ from the effect a paper focuses on. Other outcomes are used in outcome specific analyses.
[Bologna], 12/14/2021, retrospective, Italy, Europe, peer-reviewed, 3 authors. risk of death, 50.0% lower, RR 0.50, p = 0.48, treatment 3 of 40 (7.5%), control 6 of 40 (15.0%), NNT 13.
risk of ICU admission, 50.0% lower, RR 0.50, p = 0.48, treatment 3 of 40 (7.5%), control 6 of 40 (15.0%), NNT 13.
hospitalization time, 8.7% lower, relative time 0.91, p = 0.05, treatment mean 31.3 (±6.8) n=40, control mean 34.3 (±6.9) n=40.
relative sub-intensive hospitalization time, 38.8% better, relative time 0.61, p < 0.001, treatment mean 12.3 (±3.0) n=40, control mean 20.1 (±6.1) n=40.
relative NIV time, 58.4% better, relative time 0.42, p < 0.001, treatment mean 5.2 (±3.0) n=40, control mean 12.5 (±4.2) n=40.
relative high flow oxygen time, 7.8% better, relative time 0.92, p = 0.35, treatment mean 7.1 (±2.5) n=40, control mean 7.7 (±3.2) n=40.
relative sleep time, 18.2% better, RR 0.82, p < 0.001, treatment mean 5.5 (±0.8) n=40, control mean 4.5 (±1.2) n=40.
delirium, 33.3% lower, RR 0.67, p < 0.001, treatment mean 2.2 (±1.1) n=40, control mean 3.3 (±1.3) n=40.
[Darban], 12/15/2020, Randomized Controlled Trial, Iran, Middle East, peer-reviewed, 8 authors, this trial uses multiple treatments in the treatment arm (combined with vitamin C and zinc) - results of individual treatments may vary. risk of progression, 33.3% lower, RR 0.67, p = 1.00, treatment 2 of 10 (20.0%), control 3 of 10 (30.0%), NNT 10.
ICU time, 6.0% lower, relative time 0.94, p = 0.30, treatment 10, control 10.
[Farnoosh], 6/23/2021, Double Blind Randomized Controlled Trial, Iran, Middle East, peer-reviewed, 12 authors, average treatment delay 7.0 days. risk of ICU admission, 81.5% lower, RR 0.19, p = 0.20, treatment 0 of 24 (0.0%), control 2 of 20 (10.0%), NNT 10.0, relative risk is not 0 because of continuity correction due to zero events (with reciprocal of the contrasting arm).
recovery time, 49.0% lower, relative time 0.51, p = 0.004, treatment 24, control 20.
risk of no hospital discharge, 44.4% lower, RR 0.56, p = 0.65, treatment 2 of 24 (8.3%), control 3 of 20 (15.0%), NNT 15.
time to discharge, 42.9% lower, relative time 0.57, p = 0.02, treatment 24, control 20.
[Hasan], 10/12/2021, Randomized Controlled Trial, Iraq, Middle East, peer-reviewed, 3 authors. risk of death, 92.9% lower, RR 0.07, p < 0.001, treatment 1 of 82 (1.2%), control 13 of 76 (17.1%), NNT 6.3.
[Hosseini], 5/17/2021, prospective, Iran, Middle East, peer-reviewed, 9 authors. recovery time, 47.6% lower, relative time 0.52, p = 0.001, treatment 20, control 20.
[Mousavi], 8/30/2021, Randomized Controlled Trial, Iran, Middle East, peer-reviewed, 7 authors. risk of death, 66.7% lower, RR 0.33, p = 0.62, treatment 1 of 48 (2.1%), control 3 of 48 (6.2%), NNT 24, day 10.
risk of ICU admission, 40.0% lower, RR 0.60, p = 0.41, treatment 6 of 48 (12.5%), control 10 of 48 (20.8%), NNT 12, day 10.
[Ramlall], 10/18/2020, retrospective, USA, North America, preprint, 3 authors. risk of death, 86.9% lower, RR 0.13, p < 0.001, treatment 196, control 752, multivariate model Cox proportional hazards.
[Sánchez-González], 7/20/2021, retrospective, Spain, Europe, peer-reviewed, 4 authors, excluded in exclusion analyses: immortal time bias may significantly affect results. risk of death, 54.4% lower, RR 0.46, p < 0.001, treatment 24 of 224 (10.7%), control 53 of 224 (23.7%), NNT 7.7, odds ratio converted to relative risk, PSM.
Effect extraction follows pre-specified rules as detailed above and gives priority to more serious outcomes. Only the first (most serious) outcome is used in pooled analysis, which may differ from the effect a paper focuses on. Other outcomes are used in outcome specific analyses.
[Jehi], 6/10/2020, retrospective, USA, North America, peer-reviewed, 8 authors. risk of case, 58.0% lower, RR 0.42, p < 0.001, treatment 16 of 529 (3.0%), control 802 of 11,143 (7.2%), NNT 24, development cohort.
risk of case, 99.7% lower, RR 0.003, p = 0.09, treatment 0 of 18 (0.0%), control 290 of 2,005 (14.5%), NNT 6.9, relative risk is not 0 because of continuity correction due to zero events (with reciprocal of the contrasting arm), Florida validation cohort.
[Zhou], 11/6/2020, retrospective, propensity score matching, USA, North America, peer-reviewed, 18 authors. risk of case, 21.1% lower, RR 0.79, p = 0.01, treatment 222 of 1,055 (21.0%), control 8,052 of 25,724 (31.3%), NNT 9.7, odds ratio converted to relative risk, PSM.
Supplementary Data
References