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Quercetin for COVID-19: real-time meta analysis of 9 studies
Covid Analysis, May 27, 2022, DRAFT
https://c19quercetin.com/meta.html
0 0.5 1 1.5+ All studies 63% 9 1,279 Improvement, Studies, Patients Relative Risk Mortality 59% 4 683 ICU admission 75% 4 683 Hospitalization 68% 2 194 Recovery 34% 4 739 Cases 93% 3 346 Viral clearance 61% 2 92 RCTs 57% 8 1,166 RCT mortality 59% 4 683 Peer-reviewed 53% 8 1,166 Exc. combined 68% 5 574 Prophylaxis 93% 3 346 Early 38% 3 244 Late 31% 3 689 Quercetin for COVID-19 c19quercetin.com May 2022 Favorsquercetin Favorscontrol after exclusions
Statistically significant improvements are seen for ICU admission, hospitalization, recovery, cases, and viral clearance. 9 studies from 8 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 63% [27‑81%] improvement. Results are similar for Randomized Controlled Trials, similar after exclusions, similar for peer-reviewed studies, and similar after excluding studies using combined treatment.
0 0.5 1 1.5+ All studies 63% 9 1,279 Improvement, Studies, Patients Relative Risk Mortality 59% 4 683 ICU admission 75% 4 683 Hospitalization 68% 2 194 Recovery 34% 4 739 Cases 93% 3 346 Viral clearance 61% 2 92 RCTs 57% 8 1,166 RCT mortality 59% 4 683 Peer-reviewed 53% 8 1,166 Exc. combined 68% 5 574 Prophylaxis 93% 3 346 Early 38% 3 244 Late 31% 3 689 Quercetin for COVID-19 c19quercetin.com May 2022 Favorsquercetin Favorscontrol after exclusions
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 44% of quercetin studies show zero events in the treatment arm. Multiple treatments are typically used in combination, and other treatments may be more effective.
No treatment, vaccine, or intervention is 100% available and effective for all variants. All practical, effective, and safe means should be used. Denying the efficacy of treatments increases mortality, morbidity, collateral damage, and endemic risk.
All data to reproduce this paper and sources are in the appendix.
Highlights
Quercetin reduces risk for COVID-19 with very high confidence for hospitalization, recovery, cases, viral clearance, and in pooled analysis, high confidence for ICU admission, and very low confidence for mortality.
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+ 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 Khan (RCT) 33% 0.67 [0.37-1.19] no recov. 10/25 15/25 CT​1 Tau​2 = 0.00, I​2 = 0.0%, p = 0.09 Early treatment 38% 0.62 [0.35-1.08] 10/122 19/122 38% 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 63% 0.37 [0.19-0.73] 22/484 63/795 63% improvement 9 quercetin COVID-19 studies c19quercetin.com May 2022 Tau​2 = 0.31, I​2 = 35.3%, p = 0.0042 Effect extraction pre-specified(most serious outcome, 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.
Preclinical Research
3 In Silico studies support the efficacy of quercetin [Kandeil, Sekiou, Şimşek].
5 In Vitro studies support the efficacy of quercetin [Bahun, Goc, Kandeil, Munafò, Singh].
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, 11, and 12 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.
0 0.5 1 1.5+ ALL STUDIES MORTALITY ICU ADMISSION HOSPITALIZATION RECOVERY CASES VIRAL CLEARANCE RANDOMIZED CONTROLLED TRIALS RCT MORTALITY PEER-REVIEWED EXC. COMBINED After Exclusions ALL STUDIES All Prophylaxis Early Late Quercetin for COVID-19 C19QUERCETIN.COM MAY 2022
Figure 3. Overview of results.
Treatment timeNumber of studies reporting positive effects Total number of studiesPercentage of studies reporting positive effects Random effects meta-analysis results
Early treatment 3 3 100% 38% improvement
RR 0.62 [0.35‑1.08]
p = 0.09
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 8 9 88.9% 63% improvement
RR 0.37 [0.19‑0.73]
p = 0.0042
Table 1. Results by treatment stage.
Studies Early treatment Late treatment Prophylaxis PatientsAuthors
All studies 938% [-8‑65%]31% [-42‑67%]93% [73‑98%] 1,279 94
With exclusions 838% [-8‑65%]31% [-42‑67%]94% [64‑99%] 1,166 87
Peer-reviewed 838% [-8‑65%]31% [-42‑67%]94% [64‑99%] 1,166 87
Randomized Controlled TrialsRCTs 838% [-8‑65%]31% [-42‑67%]92% [66‑98%] 1,166 89
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+ 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 Khan (RCT) 33% 0.67 [0.37-1.19] no recov. 10/25 15/25 CT​1 Tau​2 = 0.00, I​2 = 0.0%, p = 0.09 Early treatment 38% 0.62 [0.35-1.08] 10/122 19/122 38% 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 63% 0.37 [0.19-0.73] 22/484 63/795 63% improvement 9 quercetin COVID-19 studies c19quercetin.com May 2022 Tau​2 = 0.31, I​2 = 35.3%, p = 0.0042 Effect extraction pre-specified(most serious outcome, see appendix) 1 CT: study uses combined treatment Favors quercetin 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+ 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 May 2022 Tau​2 = 0.00, I​2 = 0.0%, p = 0.19 1 CT: study uses combined treatment Favors quercetin 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+ 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 May 2022 Tau​2 = 0.29, I​2 = 16.2%, p = 0.029 1 CT: study uses combined treatment Favors quercetin Favors control
Figure 6. Random effects meta-analysis for ICU admission.
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ 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 May 2022 Tau​2 = 0.00, I​2 = 0.0%, p = 0.0035 Favors quercetin Favors control
Figure 7. Random effects meta-analysis for hospitalization.
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ Khan (RCT) 33% 0.67 [0.37-1.19] no recov. 10/25 15/25 CT​1 Improvement, RR [CI] Treatment Control Tau​2 = 0.00, I​2 = 0.0%, p = 0.17 Early treatment 33% 0.67 [0.37-1.19] 10/25 15/25 33% improvement 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 [0.50-0.88] 20/203 63/536 34% improvement 4 quercetin COVID-19 recovery results c19quercetin.com May 2022 Tau​2 = 0.00, I​2 = 0.0%, p = 0.005 1 CT: study uses combined treatment Favors quercetin 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+ 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 May 2022 Tau​2 = 0.00, I​2 = 0.0%, p < 0.0001 1 CT: study uses combined treatment Favors quercetin 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+ Di Pierro (RCT) 74% 0.26 [0.12-0.57] viral+ 5/21 19/21 Improvement, RR [CI] Treatment Control Khan (RCT) 50% 0.50 [0.30-0.84] viral+ 10/25 20/25 CT​1 Tau​2 = 0.09, I​2 = 44.8%, p = 0.0026 Early treatment 61% 0.39 [0.21-0.72] 15/46 39/46 61% improvement All studies 61% 0.39 [0.21-0.72] 15/46 39/46 61% improvement 2 quercetin COVID-19 viral clearance results c19quercetin.com May 2022 Tau​2 = 0.09, I​2 = 44.8%, p = 0.0026 1 CT: study uses combined treatment Favors quercetin Favors control
Figure 10. 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 Khan (RCT) 33% 0.67 [0.37-1.19] no recov. 10/25 15/25 CT​1 Tau​2 = 0.00, I​2 = 0.0%, p = 0.09 Early treatment 38% 0.62 [0.35-1.08] 10/122 19/122 38% 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 53% 0.47 [0.25-0.87] 21/413 54/753 53% improvement 8 quercetin COVID-19 peer reviewed trials c19quercetin.com May 2022 Tau​2 = 0.17, I​2 = 23.4%, p = 0.016 Effect extraction pre-specified(most serious outcome, see appendix) 1 CT: study uses combined treatment Favors quercetin 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.
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 May 2022 Tau​2 = 0.35, I​2 = 23.4%, p = 0.027 Effect extraction pre-specified(most serious outcome, see appendix) Favors quercetin Favors control
Figure 12. 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 13 shows a forest plot for random effects meta-analysis of all studies after exclusions.
[Arslan], paper no longer available at the source, and the 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 Khan (RCT) 33% 0.67 [0.37-1.19] no recov. 10/25 15/25 CT​1 Tau​2 = 0.00, I​2 = 0.0%, p = 0.09 Early treatment 38% 0.62 [0.35-1.08] 10/122 19/122 38% 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 53% 0.47 [0.25-0.87] 21/413 54/753 53% improvement 8 quercetin COVID-19 studies after exclusions c19quercetin.com May 2022 Tau​2 = 0.17, I​2 = 23.4%, p = 0.016 Effect extraction pre-specified(most serious outcome, see appendix) 1 CT: study uses combined treatment Favors quercetin Favors control
Figure 13. Random effects meta-analysis for all studies after exclusions. This plot shows pooled effects, discussion can be found in the heterogeneity section, and results for specific outcomes can be found in the individual outcome analyses. Effect extraction is pre-specified, using the most serious outcome reported. For details of effect extraction see the appendix.
Randomized Controlled Trials (RCTs)
Figure 14 shows the distribution of results for Randomized Controlled Trials and other studies, and a chronological history of results. Figure 15 and 16 show forest plots for a random effects meta-analysis of all Randomized Controlled Trials and RCT mortality results. Table 3 summarizes the results.
Figure 14. The distribution of results for Randomized Controlled Trials and other studies, and a chronological history of results.
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ 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 Khan (RCT) 33% 0.67 [0.37-1.19] no recov. 10/25 15/25 CT​1 Tau​2 = 0.00, I​2 = 0.0%, p = 0.09 Early treatment 38% 0.62 [0.35-1.08] 10/122 19/122 38% 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 57% 0.43 [0.23-0.82] 22/431 54/735 57% improvement 8 quercetin COVID-19 Randomized Controlled Trials c19quercetin.com May 2022 Tau​2 = 0.22, I​2 = 29.5%, p = 0.01 Effect extraction pre-specified(most serious outcome, see appendix) 1 CT: study uses combined treatment Favors quercetin Favors control
Figure 15. Random effects meta-analysis for all Randomized Controlled Trials. This plot shows pooled effects, discussion can be found in the heterogeneity section, and results for specific outcomes can be found in the individual outcome analyses. Effect extraction is pre-specified, using the most serious outcome reported. For details of effect extraction see the appendix.
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ 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 May 2022 Tau​2 = 0.00, I​2 = 0.0%, p = 0.19 1 CT: study uses combined treatment Favors quercetin Favors control
Figure 16. Random effects meta-analysis for RCT mortality results.
Treatment timeNumber of studies reporting positive effects Total number of studiesPercentage of studies reporting positive effects Random effects meta-analysis results
Randomized Controlled Trials 7 8 87.5% 57% improvement
RR 0.43 [0.23‑0.82]
p = 0.01
RCT mortality results 3 4 75.0% 59% improvement
RR 0.41 [0.11‑1.55]
p = 0.19
Table 3. Randomized Controlled Trial results.
Heterogeneity
Heterogeneity in COVID-19 studies arises from many factors including:
Treatment delay.
The time between infection or the onset of symptoms and treatment may critically affect how well a treatment works. For example an antiviral may be very effective when used early but may not be effective in late stage disease, and may even be harmful. Oseltamivir, for example, is generally only considered effective for influenza when used within 0-36 or 0-48 hours [McLean, Treanor]. Figure 17 shows a mixed-effects meta-regression for efficacy as a function of treatment delay in COVID-19 studies from 42 treatments, showing that efficacy declines rapidly with treatment delay. Early treatment is critical for COVID-19.
Figure 17. Meta-regression showing efficacy as a function of treatment delay in COVID-19 studies from 42 treatments. Early treatment is critical.
Patient demographics.
Details of the patient population including age and comorbidities may critically affect how well a treatment works. For example, many COVID-19 studies with relatively young low-comorbidity patients show all patients recovering quickly with or without treatment. In such cases, there is little room for an effective treatment to improve results (as in [López-Medina]).
Effect measured.
Efficacy may differ significantly depending on the effect measured, for example a treatment may be very effective at reducing mortality, but less effective at minimizing cases or hospitalization. Or a treatment may have no effect on viral clearance while still being effective at reducing mortality.
Variants.
There are many different variants of SARS-CoV-2 and efficacy may depend critically on the distribution of variants encountered by the patients in a study. For example, the Gamma variant shows significantly different characteristics [Faria, Karita, Nonaka, Zavascki]. Different mechanisms of action may be more or less effective depending on variants, for example the viral entry process for the omicron variant has moved towards TMPRSS2-independent fusion, suggesting that TMPRSS2 inhibitors may be less effective [Peacock, Willett].
Regimen.
Effectiveness may depend strongly on the dosage and treatment regimen.
Treatments.
The use of other treatments may significantly affect outcomes, including anything from supplements, other medications, or other kinds of treatment such as prone positioning.
The distribution of studies will alter the outcome of a meta analysis. Consider a simplified example where everything is equal except for the treatment delay, and effectiveness decreases to zero or below with increasing delay. If there are many studies using very late treatment, the outcome may be negative, even though the treatment may be very effective when used earlier.
In general, by combining heterogeneous studies, as all meta analyses do, we run the risk of obscuring an effect by including studies where the treatment is less effective, not effective, or harmful.
When including studies where a treatment is less effective we expect the estimated effect size to be lower than that for the optimal case. We do not a priori expect that pooling all studies will create a positive result for an effective treatment. Looking at all studies is valuable for providing an overview of all research, important to avoid cherry-picking, and informative when a positive result is found despite combining less-optimal situations. However, the resulting estimate does not apply to specific cases such as early treatment in high-risk populations.
Discussion
Publication bias.
Publishing is often biased towards positive results, 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.
100% of retrospective studies report a statistically significant positive effect for one or more outcomes, compared to 100% of prospective studies, showing no difference. The median effect size for retrospective studies is 94% improvement, compared to 76% for prospective studies, suggesting a potential bias towards publishing results showing higher efficacy. Figure 18 shows a scatter plot of results for prospective and retrospective studies.
Figure 18. Prospective vs. retrospective studies.
Funnel plot analysis.
Funnel plots have traditionally been used for analyzing publication bias. This is invalid for COVID-19 acute treatment trials — the underlying assumptions are invalid, which we can demonstrate with a simple example. Consider a set of hypothetical perfect trials with no bias. Figure 19 plot A shows a funnel plot for a simulation of 80 perfect trials, with random group sizes, and each patient's outcome randomly sampled (10% control event probability, and a 30% effect size for treatment). Analysis shows no asymmetry (p > 0.05). In plot B, we add a single typical variation in COVID-19 treatment trials — treatment delay. Consider that efficacy varies from 90% for treatment within 24 hours, reducing to 10% when treatment is delayed 3 days. In plot B, each trial's treatment delay is randomly selected. Analysis now shows highly significant asymmetry, p < 0.0001, with six variants of Egger's test all showing p < 0.05 [Egger, Harbord, Macaskill, Moreno, Peters, Rothstein, Rücker, Stanley]. Note that these tests fail even though treatment delay is uniformly distributed. In reality treatment delay is more complex — each trial has a different distribution of delays across patients, and the distribution across trials may be biased (e.g., late treatment trials may be more common). Similarly, many other variations in trials may produce asymmetry, including dose, administration, duration of treatment, differences in SOC, comorbidities, age, variants, and bias in design, implementation, analysis, and reporting.
Figure 19. Example funnel plot analysis for simulated perfect trials.
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.
4 of 9 studies combine treatments. The results of quercetin alone may differ. 3 of 8 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. 9 studies from 8 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 63% [27‑81%] improvement. Results are similar for Randomized Controlled Trials, similar after exclusions, similar for peer-reviewed studies, and similar after excluding studies using combined treatment.
Studies may use specific formulations for improved bioavailability.
Study Notes
0 0.5 1 1.5 2+ Case 92% Improvement Relative Risk c19quercetin.com Arslan et al. NCT04377789 Quercetin RCT Prophylaxis 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 0.5 1 1.5 2+ Mortality 67% Improvement Relative Risk ICU admission 67% Hospitalization 67% Viral clearance 74% Viral clearance (b) 89% c19quercetin.com Di Pierro et al. NCT04861298 Quercetin RCT EARLY TREATMENT 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 0.5 1 1.5 2+ Mortality 86% Improvement Relative Risk ICU admission 94% Hospitalization 68% c19quercetin.com Di Pierro et al. NCT04578158 Quercetin RCT EARLY TREATMENT 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 0.5 1 1.5 2+ Recovery 33% Improvement Relative Risk CRP reduction 39% Viral clearance 50% c19quercetin.com Khan et al. Quercetin for COVID-19 RCT EARLY TREATMENT Favors quercetin Favors control
[Khan] RCT 50 COVID+ outpatients in Pakistan, 25 treated with curcumin, quercetin, and vitamin D, showing significantly faster viral clearance, significantly improved CRP, and faster resolution of acute symptoms (p=0.154). Only the abstract is currently available. 168mg curcumin, 260mg quercetin and 360IU cholecalciferol.
0 0.5 1 1.5 2+ Case 94% Improvement Relative Risk COVID-19 or flu-like.. 81% c19quercetin.com Margolin et al. Quercetin for COVID-19 Prophylaxis 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 0.5 1 1.5 2+ Mortality -29% Improvement Relative Risk ICU admission 94% Discharge 78% c19quercetin.com Onal et al. NCT04377789 Quercetin RCT LATE TREATMENT 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 et al. NCT05037240 Quercetin RCT Prophylaxis 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.