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Introduction
Results
Exclusions
Randomized Controlled Trials..
Heterogeneity
Discussion
Conclusion
Study Notes 
Appendix 1. Methods and Study..
Supplementary Data
References

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Mortality
ICU admission
Hospitalization
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COVID-19 cases
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Quercetin for COVID-19: real-time meta analysis of 8 studies
Covid Analysis, January 18, 2022, DRAFT
https://c19quercetin.com/meta.html
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ All studies 74% 8 1,229 Improvement, Studies, Patients Relative Risk With exclusions 68% 7 1,116 Mortality 59% 4 683 ICU admission 75% 4 683 Hospitalization 68% 2 194 Recovery 34% 3 689 Cases 93% 3 346 Viral clearance 74% 1 42 RCTs 70% 7 1,116 RCT mortality 59% 4 683 Peer-reviewed 68% 7 1,116 Exc. combined 68% 5 574 Prophylaxis 93% 3 346 Early 79% 2 194 Late 31% 3 689 Quercetin for COVID-19 c19quercetin.com Jan 18, 2022 Favors quercetin Favors control
Statistically significant improvements are seen for ICU admission, hospitalization, recovery, cases, and viral clearance. 8 studies from 7 independent teams in 6 different countries show statistically significant improvements in isolation (3 for the most serious outcome).
Meta analysis using the most serious outcome reported shows 74% [36‑90%] improvement. Results are similar for Randomized Controlled Trials, similar after exclusions, similar for peer-reviewed studies, and similar after excluding studies using combined treatment. Early treatment is more effective than late treatment.
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ All studies 74% 8 1,229 Improvement, Studies, Patients Relative Risk With exclusions 68% 7 1,116 Mortality 59% 4 683 ICU admission 75% 4 683 Hospitalization 68% 2 194 Recovery 34% 3 689 Cases 93% 3 346 Viral clearance 74% 1 42 RCTs 70% 7 1,116 RCT mortality 59% 4 683 Peer-reviewed 68% 7 1,116 Exc. combined 68% 5 574 Prophylaxis 93% 3 346 Early 79% 2 194 Late 31% 3 689 Quercetin for COVID-19 c19quercetin.com Jan 18, 2022 Favors quercetin Favors control
3 studies use combined treatments. When excluding those studies, the pooled improvement is 68% [12‑89%] compared to 74% [36‑90%].
Currently there is limited data, with only 48 control events for the most serious outcome in trials to date.
Studies may use specific formulations for improved bioavailability.
While many treatments have some level of efficacy, they do not replace vaccines and other measures to avoid infection. Only 50% of quercetin 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 879% [-82‑98%]31% [-42‑67%]93% [73‑98%] 1,229 87
With exclusions 779% [-82‑98%]31% [-42‑67%]94% [64‑99%] 1,116 80
Peer-reviewed 779% [-82‑98%]31% [-42‑67%]94% [64‑99%] 1,116 80
Randomized Controlled TrialsRCTs 779% [-82‑98%]31% [-42‑67%]92% [66‑98%] 1,116 82
Percentage improvement with quercetin treatment
A
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ Di Pierro (RCT) 86% 0.14 [0.01-2.72] death 0/76 3/76 Improvement, RR [CI] Treatment Control Di Pierro (RCT) 67% 0.33 [0.01-7.74] death 0/21 1/21 Tau​2 = 0.00, I​2 = 0.0%, p = 0.16 Early treatment 79% 0.21 [0.02-1.82] 0/97 4/97 79% improvement Onal (RCT) -29% 1.29 [0.16-10.5] death 1/49 6/380 CT​1 Improvement, RR [CI] Treatment Control Zupanets (RCT) 29% 0.71 [0.32-1.58] no recov. 9/99 13/101 Shohan (RCT) 86% 0.14 [0.01-2.65] death 0/30 3/30 Tau​2 = 0.00, I​2 = 0.0%, p = 0.32 Late treatment 31% 0.69 [0.33-1.42] 10/178 22/511 31% improvement Arslan (RCT) 92% 0.08 [0.01-0.79] cases 1/71 9/42 CT​1 Improvement, RR [CI] Treatment Control Margolin 94% 0.06 [0.00-0.93] cases 0/53 9/60 CT​1 Rondanelli (DB RCT) 93% 0.07 [0.01-0.91] symp. case 1/60 4/60 Tau​2 = 0.00, I​2 = 0.0%, p < 0.0001 Prophylaxis 93% 0.07 [0.02-0.27] 2/184 22/162 93% improvement All studies 74% 0.26 [0.10-0.64] 12/459 48/770 74% improvement 8 quercetin COVID-19 studies c19quercetin.com Jan 18, 2022 Tau​2 = 0.56, I​2 = 34.6%, p = 0.0038 Effect extraction pre-specified, see appendix 1 CT: study uses combined treatment Favors quercetin 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 quercetin 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.
Results
Figure 3, 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, ICU admission, hospitalization, recovery, cases, viral clearance, peer reviewed studies, and all studies excluding combined treatment studies. Table 1 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% 79% improvement
RR 0.21 [0.02‑1.82]
p = 0.16
Late treatment 2 3 66.7% 31% improvement
RR 0.69 [0.33‑1.42]
p = 0.32
Prophylaxis 3 3 100% 93% improvement
RR 0.07 [0.02‑0.27]
p < 0.0001
All studies 7 8 87.5% 74% improvement
RR 0.26 [0.10‑0.64]
p = 0.0038
Table 1. Results by treatment stage.
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ Di Pierro (RCT) 86% 0.14 [0.01-2.72] death 0/76 3/76 Improvement, RR [CI] Treatment Control Di Pierro (RCT) 67% 0.33 [0.01-7.74] death 0/21 1/21 Tau​2 = 0.00, I​2 = 0.0%, p = 0.16 Early treatment 79% 0.21 [0.02-1.82] 0/97 4/97 79% improvement Onal (RCT) -29% 1.29 [0.16-10.5] death 1/49 6/380 CT​1 Improvement, RR [CI] Treatment Control Zupanets (RCT) 29% 0.71 [0.32-1.58] no recov. 9/99 13/101 Shohan (RCT) 86% 0.14 [0.01-2.65] death 0/30 3/30 Tau​2 = 0.00, I​2 = 0.0%, p = 0.32 Late treatment 31% 0.69 [0.33-1.42] 10/178 22/511 31% improvement Arslan (RCT) 92% 0.08 [0.01-0.79] cases 1/71 9/42 CT​1 Improvement, RR [CI] Treatment Control Margolin 94% 0.06 [0.00-0.93] cases 0/53 9/60 CT​1 Rondanelli (DB RCT) 93% 0.07 [0.01-0.91] symp. case 1/60 4/60 Tau​2 = 0.00, I​2 = 0.0%, p < 0.0001 Prophylaxis 93% 0.07 [0.02-0.27] 2/184 22/162 93% improvement All studies 74% 0.26 [0.10-0.64] 12/459 48/770 74% improvement 8 quercetin COVID-19 studies c19quercetin.com Jan 18, 2022 Tau​2 = 0.56, I​2 = 34.6%, p = 0.0038 Effect extraction pre-specified, see appendix 1 CT: study uses combined treatment Favors quercetin 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+ Di Pierro (RCT) 86% 0.14 [0.01-2.72] 0/76 3/76 Improvement, RR [CI] Treatment Control Di Pierro (RCT) 67% 0.33 [0.01-7.74] 0/21 1/21 Tau​2 = 0.00, I​2 = 0.0%, p = 0.16 Early treatment 79% 0.21 [0.02-1.82] 0/97 4/97 79% improvement Onal (RCT) -29% 1.29 [0.16-10.5] 1/49 6/380 CT​1 Improvement, RR [CI] Treatment Control Shohan (RCT) 86% 0.14 [0.01-2.65] 0/30 3/30 Tau​2 = 0.74, I​2 = 30.6%, p = 0.59 Late treatment 45% 0.55 [0.07-4.50] 1/79 9/410 45% improvement All studies 59% 0.41 [0.11-1.55] 1/176 13/507 59% improvement 4 quercetin COVID-19 mortality results c19quercetin.com Jan 18, 2022 Tau​2 = 0.00, I​2 = 0.0%, p = 0.19 1 CT: study uses combined treatment Favors quercetin 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+ Di Pierro (RCT) 94% 0.06 [0.00-1.00] 0/76 8/76 Improvement, RR [CI] Treatment Control Di Pierro (RCT) 67% 0.33 [0.01-7.74] 0/21 1/21 Tau​2 = 0.00, I​2 = 0.0%, p = 0.055 Early treatment 87% 0.13 [0.02-1.05] 0/97 9/97 87% improvement Onal (RCT) 94% 0.06 [0.00-0.98] 0/49 14/380 CT​1 Improvement, RR [CI] Treatment Control Shohan (RCT) 40% 0.60 [0.16-2.29] 3/30 5/30 Tau​2 = 1.41, I​2 = 52.9%, p = 0.23 Late treatment 73% 0.27 [0.03-2.31] 3/79 19/410 73% improvement All studies 75% 0.25 [0.07-0.87] 3/176 28/507 75% improvement 4 quercetin COVID-19 ICU results c19quercetin.com Jan 18, 2022 Tau​2 = 0.29, I​2 = 16.2%, p = 0.029 1 CT: study uses combined treatment Favors quercetin 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+ Di Pierro (RCT) 68% 0.32 [0.14-0.70] hosp. 7/76 22/76 Improvement, RR [CI] Treatment Control Di Pierro (RCT) 67% 0.33 [0.01-7.74] hosp. 0/21 1/21 Tau​2 = 0.00, I​2 = 0.0%, p = 0.0035 Early treatment 68% 0.32 [0.15-0.69] 7/97 23/97 68% improvement All studies 68% 0.32 [0.15-0.69] 7/97 23/97 68% improvement 2 quercetin COVID-19 hospitalization results c19quercetin.com Jan 18, 2022 Tau​2 = 0.00, I​2 = 0.0%, p = 0.0035 Favors quercetin 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+ Onal (RCT) 78% 0.22 [0.03-1.58] no disch. 1/49 35/380 CT​1 Improvement, RR [CI] Treatment Control Zupanets (RCT) 29% 0.71 [0.32-1.58] no recov. 9/99 13/101 Shohan (RCT) 32% 0.68 [0.47-0.98] recov. time 30 (n) 30 (n) Tau​2 = 0.00, I​2 = 0.0%, p = 0.014 Late treatment 34% 0.66 [0.47-0.92] 10/178 48/511 34% improvement All studies 34% 0.66 [0.47-0.92] 10/178 48/511 34% improvement 3 quercetin COVID-19 recovery results c19quercetin.com Jan 18, 2022 Tau​2 = 0.00, I​2 = 0.0%, p = 0.014 1 CT: study uses combined treatment Favors quercetin Favors control
Figure 7. Random effects meta-analysis for recovery.
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ Arslan (RCT) 92% 0.08 [0.01-0.79] cases 1/71 9/42 CT​1 Improvement, RR [CI] Treatment Control Margolin 94% 0.06 [0.00-0.93] cases 0/53 9/60 CT​1 Rondanelli (DB RCT) 93% 0.07 [0.01-0.91] symp. case 1/60 4/60 Tau​2 = 0.00, I​2 = 0.0%, p < 0.0001 Prophylaxis 93% 0.07 [0.02-0.27] 2/184 22/162 93% improvement All studies 93% 0.07 [0.02-0.27] 2/184 22/162 93% improvement 3 quercetin COVID-19 case results c19quercetin.com Jan 18, 2022 Tau​2 = 0.00, I​2 = 0.0%, p < 0.0001 1 CT: study uses combined treatment Favors quercetin Favors control
Figure 8. Random effects meta-analysis for cases.
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ Di Pierro (RCT) 74% 0.26 [0.12-0.57] viral+ 5/21 19/21 Improvement, RR [CI] Treatment Control Tau​2 = 0.00, I​2 = 0.0%, p = 0.00081 Early treatment 74% 0.26 [0.12-0.57] 5/21 19/21 74% improvement All studies 74% 0.26 [0.12-0.57] 5/21 19/21 74% improvement 1 quercetin COVID-19 viral clearance result c19quercetin.com Jan 18, 2022 Tau​2 = 0.00, I​2 = 0.0%, p = 0.00081 Favors quercetin Favors control
Figure 9. Random effects meta-analysis for viral clearance.
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ Di Pierro (RCT) 86% 0.14 [0.01-2.72] death 0/76 3/76 Improvement, RR [CI] Treatment Control Di Pierro (RCT) 67% 0.33 [0.01-7.74] death 0/21 1/21 Tau​2 = 0.00, I​2 = 0.0%, p = 0.16 Early treatment 79% 0.21 [0.02-1.82] 0/97 4/97 79% improvement Onal (RCT) -29% 1.29 [0.16-10.5] death 1/49 6/380 CT​1 Improvement, RR [CI] Treatment Control Zupanets (RCT) 29% 0.71 [0.32-1.58] no recov. 9/99 13/101 Shohan (RCT) 86% 0.14 [0.01-2.65] death 0/30 3/30 Tau​2 = 0.00, I​2 = 0.0%, p = 0.32 Late treatment 31% 0.69 [0.33-1.42] 10/178 22/511 31% improvement Margolin 94% 0.06 [0.00-0.93] cases 0/53 9/60 CT​1 Improvement, RR [CI] Treatment Control Rondanelli (DB RCT) 93% 0.07 [0.01-0.91] symp. case 1/60 4/60 Tau​2 = 0.00, I​2 = 0.0%, p = 0.0018 Prophylaxis 94% 0.06 [0.01-0.36] 1/113 13/120 94% improvement All studies 68% 0.32 [0.13-0.82] 11/388 39/728 68% improvement 7 quercetin COVID-19 peer reviewed trials c19quercetin.com Jan 18, 2022 Tau​2 = 0.43, I​2 = 27.7%, p = 0.017 Effect extraction pre-specified, see appendix 1 CT: study uses combined treatment Favors quercetin 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.
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ Di Pierro (RCT) 86% 0.14 [0.01-2.72] death 0/76 3/76 Improvement, RR [CI] Treatment Control Di Pierro (RCT) 67% 0.33 [0.01-7.74] death 0/21 1/21 Tau​2 = 0.00, I​2 = 0.0%, p = 0.16 Early treatment 79% 0.21 [0.02-1.82] 0/97 4/97 79% improvement Zupanets (RCT) 29% 0.71 [0.32-1.58] no recov. 9/99 13/101 Improvement, RR [CI] Treatment Control Shohan (RCT) 86% 0.14 [0.01-2.65] death 0/30 3/30 Tau​2 = 0.08, I​2 = 6.5%, p = 0.29 Late treatment 40% 0.60 [0.24-1.53] 9/129 16/131 40% improvement Rondanelli (DB RCT) 93% 0.07 [0.01-0.91] symp. case 1/60 4/60 Improvement, RR [CI] Treatment Control Tau​2 = 0.00, I​2 = 0.0%, p = 0.016 Prophylaxis 93% 0.07 [0.01-0.91] 1/60 4/60 93% improvement All studies 68% 0.32 [0.11-0.88] 10/286 24/288 68% improvement 5 quercetin COVID-19 studies excluding combined treatment c19quercetin.com Jan 18, 2022 Tau​2 = 0.35, I​2 = 23.4%, p = 0.027 Effect extraction pre-specified, see appendix Favors quercetin Favors control
Figure 11. Random effects meta-analysis for all studies excluding combined treatment 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 12 shows a forest plot for random effects meta-analysis of all studies after exclusions.
[Arslan], paper no longer available at the source, and contact does not reply to queries.
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ Di Pierro (RCT) 86% 0.14 [0.01-2.72] death 0/76 3/76 Improvement, RR [CI] Treatment Control Di Pierro (RCT) 67% 0.33 [0.01-7.74] death 0/21 1/21 Tau​2 = 0.00, I​2 = 0.0%, p = 0.16 Early treatment 79% 0.21 [0.02-1.82] 0/97 4/97 79% improvement Onal (RCT) -29% 1.29 [0.16-10.5] death 1/49 6/380 CT​1 Improvement, RR [CI] Treatment Control Zupanets (RCT) 29% 0.71 [0.32-1.58] no recov. 9/99 13/101 Shohan (RCT) 86% 0.14 [0.01-2.65] death 0/30 3/30 Tau​2 = 0.00, I​2 = 0.0%, p = 0.32 Late treatment 31% 0.69 [0.33-1.42] 10/178 22/511 31% improvement Margolin 94% 0.06 [0.00-0.93] cases 0/53 9/60 CT​1 Improvement, RR [CI] Treatment Control Rondanelli (DB RCT) 93% 0.07 [0.01-0.91] symp. case 1/60 4/60 Tau​2 = 0.00, I​2 = 0.0%, p = 0.0018 Prophylaxis 94% 0.06 [0.01-0.36] 1/113 13/120 94% improvement All studies 68% 0.32 [0.13-0.82] 11/388 39/728 68% improvement 7 quercetin COVID-19 studies after exclusions c19quercetin.com Jan 18, 2022 Tau​2 = 0.43, I​2 = 27.7%, p = 0.017 Effect extraction pre-specified, see appendix 1 CT: study uses combined treatment Favors quercetin 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. Figure 14 and 15 show forest plots for a random effects meta-analysis of all Randomized Controlled Trials and RCT mortality results. Table 2 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+ Di Pierro (RCT) 86% 0.14 [0.01-2.72] death 0/76 3/76 Improvement, RR [CI] Treatment Control Di Pierro (RCT) 67% 0.33 [0.01-7.74] death 0/21 1/21 Tau​2 = 0.00, I​2 = 0.0%, p = 0.16 Early treatment 79% 0.21 [0.02-1.82] 0/97 4/97 79% improvement Onal (RCT) -29% 1.29 [0.16-10.5] death 1/49 6/380 CT​1 Improvement, RR [CI] Treatment Control Zupanets (RCT) 29% 0.71 [0.32-1.58] no recov. 9/99 13/101 Shohan (RCT) 86% 0.14 [0.01-2.65] death 0/30 3/30 Tau​2 = 0.00, I​2 = 0.0%, p = 0.32 Late treatment 31% 0.69 [0.33-1.42] 10/178 22/511 31% improvement Arslan (RCT) 92% 0.08 [0.01-0.79] cases 1/71 9/42 CT​1 Improvement, RR [CI] Treatment Control Rondanelli (DB RCT) 93% 0.07 [0.01-0.91] symp. case 1/60 4/60 Tau​2 = 0.00, I​2 = 0.0%, p = 0.00073 Prophylaxis 92% 0.08 [0.02-0.34] 2/131 13/102 92% improvement All studies 70% 0.30 [0.12-0.76] 12/406 39/710 70% improvement 7 quercetin COVID-19 Randomized Controlled Trials c19quercetin.com Jan 18, 2022 Tau​2 = 0.47, I​2 = 32.0%, p = 0.011 Effect extraction pre-specified, see appendix 1 CT: study uses combined treatment Favors quercetin 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+ Di Pierro (RCT) 86% 0.14 [0.01-2.72] 0/76 3/76 Improvement, RR [CI] Treatment Control Di Pierro (RCT) 67% 0.33 [0.01-7.74] 0/21 1/21 Tau​2 = 0.00, I​2 = 0.0%, p = 0.16 Early treatment 79% 0.21 [0.02-1.82] 0/97 4/97 79% improvement Onal (RCT) -29% 1.29 [0.16-10.5] 1/49 6/380 CT​1 Improvement, RR [CI] Treatment Control Shohan (RCT) 86% 0.14 [0.01-2.65] 0/30 3/30 Tau​2 = 0.74, I​2 = 30.6%, p = 0.59 Late treatment 45% 0.55 [0.07-4.50] 1/79 9/410 45% improvement All studies 59% 0.41 [0.11-1.55] 1/176 13/507 59% improvement 4 quercetin COVID-19 RCT mortality results c19quercetin.com Jan 18, 2022 Tau​2 = 0.00, I​2 = 0.0%, p = 0.19 1 CT: study uses combined treatment Favors quercetin Favors control
Figure 15. 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 6 7 85.7% 70% improvement
RR 0.30 [0.12‑0.76]
p = 0.011
RCT mortality results 3 4 75.0% 59% improvement
RR 0.41 [0.11‑1.55]
p = 0.19
Table 2. 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 16 shows an example where efficacy declines as a function of treatment delay.
Figure 16. 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 quercetin, 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 94% improvement, compared to 86% for prospective studies, consistent with a positive publication bias. 100% of retrospective studies report a statistically significant positive effect for one or more outcomes, compared to 100% of prospective studies, showing no difference. Figure 17 shows a scatter plot of results for prospective and retrospective studies.
Figure 17. 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. Quercetin for COVID-19 lacks this because it is an inexpensive and widely available supplement. In contrast, most COVID-19 quercetin 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 quercetin 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.
3 of 8 studies combine treatments. The results of quercetin alone may differ. 2 of 7 RCTs use combined treatment.
Conclusion
Quercetin is an effective treatment for COVID-19. Statistically significant improvements are seen for ICU admission, hospitalization, recovery, cases, and viral clearance. 8 studies from 7 independent teams in 6 different countries show statistically significant improvements in isolation (3 for the most serious outcome). Meta analysis using the most serious outcome reported shows 74% [36‑90%] improvement. Results are similar for Randomized Controlled Trials, similar after exclusions, similar for peer-reviewed studies, and similar after excluding studies using combined treatment. Early treatment is more effective than late treatment.
3 studies use combined treatments. When excluding those studies, the pooled improvement is 68% [12‑89%] compared to 74% [36‑90%].
Currently there is limited data, with only 48 control events for the most serious outcome in trials to date.
Studies may use specific formulations for improved bioavailability.
Study Notes
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ Case 92% Improvement Relative Risk c19quercetin.com/arslan.html Favors quercetin Favors control
[Arslan] Small prophylaxis RCT with 113 patients showing fewer cases with quercetin + vitamin C + bromelain prophylaxis. NCT04377789. Note that this paper disappeared from SSRN without explanation.
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ Mortality 67% Improvement Relative Risk ICU admission 67% Hospitalization 67% Virological cure 74% Virological cure (b) 89% c19quercetin.com/dipierro2.html Favors quercetin Favors control
[Di Pierro] RCT 42 outpatients in Pakistan, 21 treated with quercetin phytosome, showing faster viral clearance and lower symptom severity with treatment.
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ Mortality 86% Improvement Relative Risk ICU admission 94% Hospitalization 68% c19quercetin.com/dipierro.html Favors quercetin Favors control
[Di Pierro (B)] RCT 152 outpatients in Pakistan, 76 treated with quercetin phytosome, showing lower mortality, ICU admission, and hospitalization with treatment.
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ Case 94% Improvement Relative Risk COVID-19 or flu-like i.. 81% c19quercetin.com/margolinq.html Favors quercetin Favors control
[Margolin] Retrospective 113 outpatients, 53 (patient choice) treated with zinc, quercetin, vitamin C/D/E, l-lysine, and quina, showing lower cases with treatment. Results are subject to selection bias and limited information on the groups is provided. See [journals.sagepub.com].
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ Mortality -29% Improvement Relative Risk ICU admission 94% Hospital discharge 78% c19quercetin.com/onal.html Favors quercetin Favors control
[Onal] RCT 447 moderate-to-severe hospitalized patients in Turkey, 52 treated with quercetin, bromelain, and vitamin C, showing no statistically significant difference in clinical outcomes. NCT04377789.
0 0.5 1 1.5 2+ Symptomatic case 93% Improvement Relative Risk c19quercetin.com/rondanelli.html Favors quercetin Favors control
[Rondanelli] RCT 120 healthcare workers, 60 treated with quercetin phytosome, showing lower risk of cases with treatment. Quercetin phytosome 250mg twice a day. NCT05037240.
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ Mortality 86% Improvement Relative Risk ICU admission 40% Days from end of inter.. 32% c19quercetin.com/shohan.html Favors quercetin Favors control
[Shohan] Small RCT with 60 severe hospitalized patients in Iran, 30 treated with quercetin, showing shorter time until discharge. All patients received remdesivir or favipiravir, and vitamin C, vitamin D, famotidine, zinc, dexamethasone, and magnesium (depending on serum levels). Quercetin 1000mg daily for 7 days. IRCT20200419047128N2.
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ Recovery 29% Improvement Relative Risk Recovery time 18% c19quercetin.com/zupanets.html Favors quercetin Favors control
[Zupanets] RCT 200 patients in Ukraine, 99 treated with IV quercetin/polyvinylirolidone followed by oral quercetin/pectin, showing improved recovery with treatment.
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 c19quercetin.com. Search terms were quercetin, 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 quercetin 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]. 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 (3.9.10) 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://c19quercetin.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.
[Di Pierro], 6/24/2021, Randomized Controlled Trial, Pakistan, South Asia, peer-reviewed, 12 authors. risk of death, 66.7% lower, RR 0.33, p = 1.00, treatment 0 of 21 (0.0%), control 1 of 21 (4.8%), NNT 21, relative risk is not 0 because of continuity correction due to zero events (with reciprocal of the contrasting arm).
risk of ICU admission, 66.7% lower, RR 0.33, p = 1.00, treatment 0 of 21 (0.0%), control 1 of 21 (4.8%), NNT 21, relative risk is not 0 because of continuity correction due to zero events (with reciprocal of the contrasting arm).
risk of hospitalization, 66.7% lower, RR 0.33, p = 1.00, treatment 0 of 21 (0.0%), control 1 of 21 (4.8%), NNT 21, relative risk is not 0 because of continuity correction due to zero events (with reciprocal of the contrasting arm).
risk of no virological cure, 73.7% lower, RR 0.26, p < 0.001, treatment 5 of 21 (23.8%), control 19 of 21 (90.5%), NNT 1.5, day 7.
risk of no virological cure, 88.9% lower, RR 0.11, p = 0.11, treatment 0 of 21 (0.0%), control 4 of 21 (19.0%), NNT 5.2, relative risk is not 0 because of continuity correction due to zero events (with reciprocal of the contrasting arm), day 14.
[Di Pierro (B)], 6/8/2021, Randomized Controlled Trial, Pakistan, South Asia, peer-reviewed, 19 authors. risk of death, 85.7% lower, RR 0.14, p = 0.25, treatment 0 of 76 (0.0%), control 3 of 76 (3.9%), NNT 25, relative risk is not 0 because of continuity correction due to zero events (with reciprocal of the contrasting arm).
risk of ICU admission, 94.1% lower, RR 0.06, p = 0.006, treatment 0 of 76 (0.0%), control 8 of 76 (10.5%), NNT 9.5, relative risk is not 0 because of continuity correction due to zero events (with reciprocal of the contrasting arm).
risk of hospitalization, 68.2% lower, RR 0.32, p = 0.003, treatment 7 of 76 (9.2%), control 22 of 76 (28.9%), NNT 5.1.
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.
[Onal], 1/19/2021, Randomized Controlled Trial, Turkey, Europe, peer-reviewed, 10 authors, this trial uses multiple treatments in the treatment arm (combined with bromelain and vitamin C) - results of individual treatments may vary. risk of death, 29.3% higher, RR 1.29, p = 0.57, treatment 1 of 49 (2.0%), control 6 of 380 (1.6%).
risk of ICU admission, 94.0% lower, RR 0.06, p = 0.39, treatment 0 of 49 (0.0%), control 14 of 380 (3.7%), NNT 27, relative risk is not 0 because of continuity correction due to zero events (with reciprocal of the contrasting arm).
risk of no hospital discharge, 77.8% lower, RR 0.22, p = 0.10, treatment 1 of 49 (2.0%), control 35 of 380 (9.2%), NNT 14.
[Shohan], 12/2/2021, Randomized Controlled Trial, Iran, Middle East, peer-reviewed, mean age 50.9 (treatment) 52.7 (control), 8 authors, average treatment delay 7.8 days. risk of death, 85.7% lower, RR 0.14, p = 0.24, treatment 0 of 30 (0.0%), control 3 of 30 (10.0%), NNT 10.0, relative risk is not 0 because of continuity correction due to zero events (with reciprocal of the contrasting arm).
risk of ICU admission, 40.0% lower, RR 0.60, p = 0.71, treatment 3 of 30 (10.0%), control 5 of 30 (16.7%), NNT 15.
days from end of intervention to discharge, 32.4% lower, relative time 0.68, p = 0.04, treatment 30, control 30.
[Zupanets], 9/1/2021, Randomized Controlled Trial, Ukraine, Europe, peer-reviewed, 14 authors. risk of no recovery, 29.4% lower, RR 0.71, p = 0.50, treatment 9 of 99 (9.1%), control 13 of 101 (12.9%), NNT 26.
recovery time, 18.2% lower, relative time 0.82, p = 0.03, treatment 99, control 101.
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.
[Arslan], 11/16/2020, Randomized Controlled Trial, Turkey, Europe, preprint, 7 authors, this trial uses multiple treatments in the treatment arm (combined with vitamin C and bromelain) - results of individual treatments may vary, excluded in exclusion analyses: paper no longer available at the source, and contact does not reply to queries. risk of case, 91.7% lower, RR 0.08, p = 0.03, treatment 1 of 71 (1.4%), control 9 of 42 (21.4%), NNT 5.0, adjusted per study.
[Margolin], 7/6/2021, retrospective, USA, North America, peer-reviewed, 5 authors, this trial uses multiple treatments in the treatment arm (combined with zinc, vitamin C/D/E, l-lysine, and quina) - results of individual treatments may vary. risk of case, 94.4% lower, RR 0.06, p = 0.003, treatment 0 of 53 (0.0%), control 9 of 60 (15.0%), NNT 6.7, relative risk is not 0 because of continuity correction due to zero events (with reciprocal of the contrasting arm).
risk of COVID-19 or flu-like illness, 81.1% lower, RR 0.19, p = 0.01, treatment 2 of 53 (3.8%), control 12 of 60 (20.0%), NNT 6.2.
[Rondanelli], 1/4/2022, Double Blind Randomized Controlled Trial, placebo-controlled, Italy, Europe, peer-reviewed, 12 authors. risk of symptomatic case, 92.9% lower, RR 0.07, p = 0.04, treatment 1 of 60 (1.7%), control 4 of 60 (6.7%), NNT 20, adjusted per study, Cox proportional risk.
Supplementary Data
References
Please send us corrections, updates, or comments. Vaccines and treatments are both valuable and complementary. All practical, effective, and safe means should be used. Elimination of COVID-19 is a race against viral evolution. No treatment, vaccine, or intervention is 100% available and effective for all current and future variants. Denying the efficacy of any method increases mortality, morbidity, collateral damage, and the risk of endemic status. We do not provide medical advice. Before taking any medication, consult a qualified physician who can provide personalized advice and details of risks and benefits based on your medical history and situation. WCH and FLCCC provide treatment protocols.
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