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Curcumin for COVID-19: real-time meta analysis of 9 studies
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Covid Analysis, December 4, 2021
https://c19curcumin.com/meta.html
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ All studies 59% 9 867 Improvement, Studies, Patients Relative Risk, 95% CI Mortality 70% 4 434 Ventilation 72% 2 266 Hospitalization 33% 4 367 Progression 94% 1 41 Recovery 40% 5 407 Viral clearance 6% 1 92 RCTs 45% 8 826 Early 71% 6 707 Late 58% 3 160 Curcumin for COVID-19 c19curcumin.com Dec 4, 2021 Favors curcumin Favors control
Meta analysis using the most serious outcome reported shows 59% [30‑76%] improvement. Results are slightly worse for Randomized Controlled Trials.
Statistically significant improvements are seen for mortality and recovery. 5 studies show statistically significant improvements in isolation (3 for the most serious outcome).
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ All studies 59% 9 867 Improvement, Studies, Patients Relative Risk, 95% CI Mortality 70% 4 434 Ventilation 72% 2 266 Hospitalization 33% 4 367 Progression 94% 1 41 Recovery 40% 5 407 Viral clearance 6% 1 92 RCTs 45% 8 826 Early 71% 6 707 Late 58% 3 160 Curcumin for COVID-19 c19curcumin.com Dec 4, 2021 Favors curcumin Favors control
While many treatments have some level of efficacy, they do not replace vaccines and other measures to avoid infection. Only 44% of curcumin studies show zero events in the treatment arm.
Multiple treatments are typically used in combination, and other treatments may be more effective. Studies typically use advanced formulations for greatly improved bioavailability.
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 the risk of COVID-19 becoming endemic; and increases mortality, morbidity, and collateral damage.
All data to reproduce this paper and sources are in the appendix.
Studies Early treatment Late treatment PatientsAuthors
All studies 971% [26‑89%]58% [-3‑83%] 867 83
Randomized Controlled TrialsRCTs 860% [12‑82%]58% [-3‑83%] 826 74
Percentage improvement with curcumin treatment
A
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ Dound (RCT) 33% 0.67 [0.54-0.82] 6 pt. scale 100 (n) 100 (n) CT​1 Improvement, RR [CI] Treatment Control Saber-Moghaddam 94% 0.06 [0.00-0.93] progression 0/21 8/20 Pawar (DB RCT) 82% 0.18 [0.04-0.79] death 2/70 11/70 Ahmadi (DB RCT) 86% 0.14 [0.01-2.65] hosp. 0/30 3/30 Sankhe (RCT) 89% 0.11 [0.01-2.03] death 0/87 4/87 CT​1 Majeed (DB RCT) 66% 0.34 [0.01-8.09] ventilation 0/45 1/47 CT​1 Tau​2 = 0.49; I​2 = 40.4% Early treatment 71% 0.29 [0.11-0.74] 2/353 27/354 71% improvement Valizadeh (DB RCT) 50% 0.50 [0.18-1.40] death 4/20 8/20 Improvement, RR [CI] Treatment Control Tahmasebi (DB RCT) 83% 0.17 [0.02-1.32] death 1/40 6/40 Hassania.. (DB RCT) -46% 1.46 [0.01-329] SpO2 imp. 20 (n) 20 (n) Tau​2 = 0.00; I​2 = 0.0% Late treatment 58% 0.42 [0.17-1.03] 5/80 14/80 58% improvement All studies 59% 0.41 [0.24-0.70] 7/433 41/434 59% improvement 9 curcumin COVID-19 studies c19curcumin.com Dec 4, 2021 1 CT: study uses combined treatmentTau​2 = 0.14; I​2 = 21.8%; Z = 3.22 Effect extraction pre-specified, see appendix Favors curcumin 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 curcumin 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
3CLpro inhibitorCurcumin inhibits SARS-CoV-2 3CLpro [Bahun, Guijarro-Real, Rehman].
RdRp inhibitorSARS-CoV-2 RNA‐dependent RNA polymerase (RdRp) inhibition [Singh].
ACE2 inhibitorCurcumin inhibits ACE2 activity. SARS-CoV-2 viral entry requires host cell surface proteins ACE2 and TMPRSS2 [Jena, Patel].
TMPRSS2 downregulationCurcumin downregulates transmembrane serine protease 2 (TMPRSS2). SARS-CoV-2 viral entry requires host cell surface proteins ACE2 and TMPRSS2 [Goc].
Cathepsin L inhibitorCurcumin inhibits cathepsin L activity. Cathepsin L plays a key role in viral entry [Goc].
Anti‑inflammatoryCurcumin shows anti-inflammatory action [Daily, Derosa, Gupta, Marín-Palma, Rattis, Sahebkar].
Inhibition in Vero E6 cells demonstratedIn Vitro research shows curcumin inhibits SARS-CoV-2 in Vero E6 cells [Bormann, Marín-Palma].
Inhibition in Calu-3 cells demonstratedIn Vitro research shows curcumin inhibits SARS-CoV-2 in Calu-3 cells [Bormann].
Table 1. Curcumin mechanisms of action. Submit Updates.
Results
Figure 3, 4, 5, 6, 7, 8, and 9 show forest plots for a random effects meta-analysis of all studies with pooled effects, mortality results, ventilation, hospitalization, progression, recovery, and viral clearance. 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 6 6 100% 71% improvement
RR 0.29 [0.11‑0.74]
p = 0.0094
Late treatment 2 3 66.7% 58% improvement
RR 0.42 [0.17‑1.03]
p = 0.059
All studies 8 9 88.9% 59% improvement
RR 0.41 [0.24‑0.70]
p = 0.0013
Table 2. Results by treatment stage.
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ Dound (RCT) 33% 0.67 [0.54-0.82] 6 pt. scale 100 (n) 100 (n) CT​1 Improvement, RR [CI] Treatment Control Saber-Moghaddam 94% 0.06 [0.00-0.93] progression 0/21 8/20 Pawar (DB RCT) 82% 0.18 [0.04-0.79] death 2/70 11/70 Ahmadi (DB RCT) 86% 0.14 [0.01-2.65] hosp. 0/30 3/30 Sankhe (RCT) 89% 0.11 [0.01-2.03] death 0/87 4/87 CT​1 Majeed (DB RCT) 66% 0.34 [0.01-8.09] ventilation 0/45 1/47 CT​1 Tau​2 = 0.49; I​2 = 40.4% Early treatment 71% 0.29 [0.11-0.74] 2/353 27/354 71% improvement Valizadeh (DB RCT) 50% 0.50 [0.18-1.40] death 4/20 8/20 Improvement, RR [CI] Treatment Control Tahmasebi (DB RCT) 83% 0.17 [0.02-1.32] death 1/40 6/40 Hassania.. (DB RCT) -46% 1.46 [0.01-329] SpO2 imp. 20 (n) 20 (n) Tau​2 = 0.00; I​2 = 0.0% Late treatment 58% 0.42 [0.17-1.03] 5/80 14/80 58% improvement All studies 59% 0.41 [0.24-0.70] 7/433 41/434 59% improvement 9 curcumin COVID-19 studies c19curcumin.com Dec 4, 2021 1 CT: study uses combined treatmentTau​2 = 0.14; I​2 = 21.8%; Z = 3.22 Effect extraction pre-specified, see appendix Favors curcumin 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+ Pawar (DB RCT) 82% 0.18 [0.04-0.79] 2/70 11/70 Improvement, RR [CI] Treatment Control Sankhe (RCT) 89% 0.11 [0.01-2.03] 0/87 4/87 CT​1 Tau​2 = 0.00; I​2 = 0.0% Early treatment 84% 0.16 [0.04-0.61] 2/157 15/157 84% improvement Valizadeh (DB RCT) 50% 0.50 [0.18-1.40] 4/20 8/20 Improvement, RR [CI] Treatment Control Tahmasebi (DB RCT) 83% 0.17 [0.02-1.32] 1/40 6/40 Tau​2 = 0.00; I​2 = 0.0% Late treatment 60% 0.40 [0.16-1.01] 5/60 14/60 60% improvement All studies 70% 0.30 [0.14-0.64] 7/217 29/217 70% improvement 4 curcumin COVID-19 mortality results c19curcumin.com Dec 4, 2021 1 CT: study uses combined treatmentTau​2 = 0.00; I​2 = 0.0%; Z = 3.14 Favors curcumin 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+ Sankhe (RCT) 75% 0.25 [0.03-2.19] 1/87 4/87 CT​1 Improvement, RR [CI] Treatment Control Majeed (DB RCT) 66% 0.34 [0.01-8.09] 0/45 1/47 CT​1 Tau​2 = 0.00; I​2 = 0.0% Early treatment 72% 0.28 [0.05-1.65] 1/132 5/134 72% improvement All studies 72% 0.28 [0.05-1.65] 1/132 5/134 72% improvement 2 curcumin COVID-19 mechanical ventilation results c19curcumin.com Dec 4, 2021 1 CT: study uses combined treatmentTau​2 = 0.00; I​2 = 0.0%; Z = 1.41 Favors curcumin Favors control
Figure 5. Random effects meta-analysis for ventilation.
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ Saber-Moghaddam 45% 0.55 [0.39-0.79] hosp. time 21 (n) 20 (n) Improvement, RR [CI] Treatment Control Ahmadi (DB RCT) 86% 0.14 [0.01-2.65] hosp. 0/30 3/30 Sankhe (RCT) 10% 0.90 [0.71-1.15] hosp. time 87 (n) 87 (n) CT​1 Majeed (DB RCT) 80% 0.20 [0.01-4.13] hosp. 0/45 2/47 CT​1 Tau​2 = 0.09; I​2 = 57.4% Early treatment 33% 0.67 [0.42-1.06] 0/183 5/184 33% improvement All studies 33% 0.67 [0.42-1.06] 0/183 5/184 33% improvement 4 curcumin COVID-19 hospitalization results c19curcumin.com Dec 4, 2021 1 CT: study uses combined treatmentTau​2 = 0.09; I​2 = 57.4%; Z = 1.70 Favors curcumin 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+ Saber-Moghaddam 94% 0.06 [0.00-0.93] 0/21 8/20 Improvement, RR [CI] Treatment Control Tau​2 = 0.00; I​2 = 0.0% Early treatment 94% 0.06 [0.00-0.93] 0/21 8/20 94% improvement All studies 94% 0.06 [0.00-0.93] 0/21 8/20 94% improvement 1 curcumin COVID-19 progression result c19curcumin.com Dec 4, 2021 Tau​2 = 0.00; I​2 = 0.0%; Z = 2.01 Favors curcumin 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+ Saber-Moghaddam 38% 0.62 [0.39-0.96] no recov. 11/21 17/20 Improvement, RR [CI] Treatment Control Ahmadi (DB RCT) 21% 0.79 [0.48-1.31] recov. time 30 (n) 30 (n) Sankhe (RCT) 46% 0.54 [0.35-0.76] no recov. 29/87 60/87 CT​1 Majeed (DB RCT) 43% 0.57 [0.39-0.84] no recov. 45 (n) 47 (n) CT​1 Tau​2 = 0.00; I​2 = 0.0% Early treatment 40% 0.60 [0.49-0.73] 40/183 77/184 40% improvement Hassania.. (DB RCT) -46% 1.46 [0.01-329] SpO2 imp. 20 (n) 20 (n) Improvement, RR [CI] Treatment Control Tau​2 = 0.00; I​2 = 0.0% Late treatment -46% 1.46 [0.01-329] 0/20 0/20 -46% improvement All studies 40% 0.60 [0.49-0.73] 40/203 77/204 40% improvement 5 curcumin COVID-19 recovery results c19curcumin.com Dec 4, 2021 1 CT: study uses combined treatmentTau​2 = 0.00; I​2 = 0.0%; Z = 5.05 Favors curcumin 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+ Majeed (DB RCT) 6% 0.94 [0.80-1.10] viral time 45 (n) 47 (n) CT​1 Improvement, RR [CI] Treatment Control Tau​2 = 0.00; I​2 = 0.0% Early treatment 6% 0.94 [0.80-1.10] 0/45 0/47 6% improvement All studies 6% 0.94 [0.80-1.10] 0/45 0/47 6% improvement 1 curcumin COVID-19 viral clearance result c19curcumin.com Dec 4, 2021 1 CT: study uses combined treatmentTau​2 = 0.00; I​2 = 0.0%; Z = 0.74 Favors curcumin Favors control
Figure 9. Random effects meta-analysis for viral clearance.
Randomized Controlled Trials (RCTs)
Figure 10 and 11 show forest plots for a random effects meta-analysis of all Randomized Controlled Trials and RCT mortality results. Table 3 summarizes the results.
RCTs have a bias against finding an effect for interventions that are widely available — patients that believe they need the intervention are more likely to decline participation and take the intervention. This is illustrated with the extreme example of an RCT showing no significant differences for use of a parachute when jumping from a plane [Yeh]. RCTs for curcumin are more likely to enroll low-risk participants that do not need treatment to recover, making the results less applicable to clinical practice. This bias is likely to be greater for widely known treatments. Note that this bias does not apply to the typical pharmaceutical trial of a new drug that is otherwise unavailable.
Evidence shows that non-RCT trials can also provide reliable results. [Concato] find that well-designed observational studies do not systematically overestimate the magnitude of the effects of treatment compared to RCTs. [Anglemyer] summarized reviews comparing RCTs to observational studies and found little evidence for significant differences in effect estimates. [Lee] shows that only 14% of the guidelines of the Infectious Diseases Society of America were based on RCTs. Evaluation of studies relies on an understanding of the study and potential biases. Limitations in an RCT can outweigh the benefits, for example excessive dosages, excessive treatment delays, or Internet survey bias could have a greater effect on results. Ethical issues may also prevent running RCTs for known effective treatments. For more on issues with RCTs see [Deaton, Nichol].
Figure 12. Randomized Controlled Trials. The distribution of results for RCTs and other studies.
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ Dound (RCT) 33% 0.67 [0.54-0.82] 6 pt. scale 100 (n) 100 (n) CT​1 Improvement, RR [CI] Treatment Control Pawar (DB RCT) 82% 0.18 [0.04-0.79] death 2/70 11/70 Ahmadi (DB RCT) 86% 0.14 [0.01-2.65] hosp. 0/30 3/30 Sankhe (RCT) 89% 0.11 [0.01-2.03] death 0/87 4/87 CT​1 Majeed (DB RCT) 66% 0.34 [0.01-8.09] ventilation 0/45 1/47 CT​1 Tau​2 = 0.26; I​2 = 27.7% Early treatment 60% 0.40 [0.18-0.88] 2/332 19/334 60% improvement Valizadeh (DB RCT) 50% 0.50 [0.18-1.40] death 4/20 8/20 Improvement, RR [CI] Treatment Control Tahmasebi (DB RCT) 83% 0.17 [0.02-1.32] death 1/40 6/40 Hassania.. (DB RCT) -46% 1.46 [0.01-329] SpO2 imp. 20 (n) 20 (n) Tau​2 = 0.00; I​2 = 0.0% Late treatment 58% 0.42 [0.17-1.03] 5/80 14/80 58% improvement All studies 45% 0.55 [0.39-0.78] 7/412 33/414 45% improvement 8 curcumin COVID-19 Randomized Controlled Trials c19curcumin.com Dec 4, 2021 1 CT: study uses combined treatmentTau​2 = 0.03; I​2 = 5.7%; Z = 3.37 Effect extraction pre-specified, see appendix Favors curcumin Favors control
Figure 10. 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+ Pawar (DB RCT) 82% 0.18 [0.04-0.79] 2/70 11/70 Improvement, RR [CI] Treatment Control Sankhe (RCT) 89% 0.11 [0.01-2.03] 0/87 4/87 CT​1 Tau​2 = 0.00; I​2 = 0.0% Early treatment 84% 0.16 [0.04-0.61] 2/157 15/157 84% improvement Valizadeh (DB RCT) 50% 0.50 [0.18-1.40] 4/20 8/20 Improvement, RR [CI] Treatment Control Tahmasebi (DB RCT) 83% 0.17 [0.02-1.32] 1/40 6/40 Tau​2 = 0.00; I​2 = 0.0% Late treatment 60% 0.40 [0.16-1.01] 5/60 14/60 60% improvement All studies 70% 0.30 [0.14-0.64] 7/217 29/217 70% improvement 4 curcumin COVID-19 RCT mortality results c19curcumin.com Dec 4, 2021 1 CT: study uses combined treatmentTau​2 = 0.00; I​2 = 0.0%; Z = 3.14 Favors curcumin Favors control
Figure 11. 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 7 8 87.5% 45% improvement
RR 0.55 [0.39‑0.78]
p = 0.0008
RCT mortality results 4 4 100% 70% improvement
RR 0.30 [0.14‑0.64]
p = 0.0018
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 13 shows an example where efficacy declines as a function of treatment delay.
Figure 13. 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 thousands of different variants of SARS-CoV-2 and efficacy may depend critically on the distribution of variants encountered by the patients in a study.
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 curcumin, there is currently not enough data to evaluate publication bias with high confidence.
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. Curcumin for COVID-19 lacks this because it is off-patent, has multiple manufacturers, and is very low cost. In contrast, most COVID-19 curcumin 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 curcumin 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 9 studies combine treatments. The results of curcumin alone may differ. 3 of 8 RCTs use combined treatment.
Conclusion
Curcumin is an effective treatment for COVID-19. Treatment is more effective when used early. Meta analysis using the most serious outcome reported shows 59% [30‑76%] improvement. Results are slightly worse for Randomized Controlled Trials. Statistically significant improvements are seen for mortality and recovery. 5 studies show statistically significant improvements in isolation (3 for the most serious outcome).
Study Notes
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ Hospitalization 86% Imp. Relative Risk, 95% CI Recovery time 21% Ahmadi: Oral nano-curcumin formulation efficacy in the managemen.. c19curcumin.com/ahmadi.html Favors curcumin Favors control
[Ahmadi] RCT 60 outpatients in Iran, 30 treated with nano-curcumin showing lower hospitalization and faster recovery with treatment. Submit Corrections or Updates.
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ Improvement on 6-point.. 33% Imp. Relative Risk, 95% CI Dound: A Randomized, Comparative Clinical Study to Evaluate the.. c19curcumin.com/dound.html Favors curcumin Favors control
[Dound] RCT 200 COVID-19 positive patients in India, 100 treated with Curcumin, Vitamin C, Vitamin K2-7, and L-Selenomethionine, showing faster recovery with treatment. Submit Corrections or Updates.
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ Improvement in SpO2 -46% Imp. Relative Risk, 95% CI Hassaniazad: A triple-blind, placebo-controlled, randomized clinical .. c19curcumin.com/hassaniazad.html Favors curcumin Favors control
[Hassaniazad] Small RCT with 40 low risk patients in Iran, 20 treated with nano-curcumin, showing no significant difference in outcomes with treatment. Authors note that treatment can improve peripheral blood inflammatory indices and modulate immune response by decreasing Th1 and Th17 responses, increasing T regulatory responses, further reducing IL-17 and IFN-γ, and increasing suppressive cytokines TGF-β and IL-4. Submit Corrections or Updates.
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ Mechanical ventilation 66% Imp. Relative Risk, 95% CI Hospitalization 80% Ordinal scale 43% Time to improve one un.. 30% no CI Recovery 25% Time to viral- 6% Majeed: A Randomized, Double-Blind, Placebo-Controlled Study to .. c19curcumin.com/majeed.html Favors curcumin Favors control
[Majeed] RCT 100 patients in India, 50 treated with ImmuActive (curcumin, andrographolides, resveratrol, zinc, selenium, and piperine), showing improved recovery with treatment. Submit Corrections or Updates.
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ Mortality 82% Imp. Relative Risk, 95% CI Mortality (b) 60% Mortality (c) 91% Mortality (d) 67% Pawar: Oral Curcumin With Piperine as Adjuvant Therapy for the .. c19curcumin.com/pawar.html Favors curcumin Favors control
[Pawar] RCT 140 patients, 70 treated with curcumin and piperine (for absorption), showing faster recovery, lower progression, and lower mortality with treatment. Control group partients also received probiotics. CTRI/2020/05/025482. Submit Corrections or Updates.
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ Disease progression 94% Imp. Relative Risk, 95% CI Recovery 38% Hospitalization time 45% Saber-Moghaddam: Oral nano-curcumin formulation efficacy in management of.. c19curcumin.com/sabermoghaddam.html Favors curcumin Favors control
[Saber-Moghaddam] Small prospective nonrandomized trial with 41 patients, 21 treated with curcumin, showing lower disease progression and faster recovery with treatment. IRCT20200408046990N1. Submit Corrections or Updates.
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ Mortality 89% Imp. Relative Risk, 95% CI Mechanical ventilation 75% 2-point improvement 46% Hospitalization time 10% Sankhe: A prospective, multi center, single blind, randomized co.. c19curcumin.com/sankhe.html Favors curcumin Favors control
[Sankhe] RCT 174 patients in India, 87 treated with AyurCoro-3 (turmeric, gomutra, potassium alum, khadisakhar, bos indicus milk, ghee), showing faster recovery with treatment. EC/NEW/INST/2019/245. Submit Corrections or Updates.
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ Mortality 83% Imp. Relative Risk, 95% CI Mortality (b) 67% Mortality (c) 80% Tahmasebi: Nanocurcumin improves Treg cell responses in patients wi.. c19curcumin.com/tahmasebi.html Favors curcumin Favors control
[Tahmasebi] RCT 40 hospitalized, 40 ICU, and 40 control patients in Iran, showing lower mortality and improved regulatory T cell responses with nanocurcumin treatment (SinaCurcumin). Submit Corrections or Updates.
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ Mortality 50% Imp. Relative Risk, 95% CI Valizadeh: Nano-curcumin therapy, a promising method in modulating .. c19curcumin.com/valizadeh.html Favors curcumin Favors control
[Valizadeh] Small RCT with 40 nano-curcumin patients and 40 control patients showing lower mortality with treatment. Authors conclude that nano-curcumin may be able to modulate the increased rate of inflammatory cytokines especially IL-1β and IL-6 mRNA expression and cytokine secretion in COVID-19 patients, which may improve clinical outcomes. Submit Corrections or Updates.
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 c19curcumin.com. Search terms were curcumin, 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 curcumin 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 calculations for that study. 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 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 (0.13.1), 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. None
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://c19curcumin.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 calculations, which may differ from the effect a paper focuses on.
[Ahmadi], 6/19/2021, Double Blind Randomized Controlled Trial, Iran, Middle East, peer-reviewed, 11 authors. risk of hospitalization, 85.7% lower, RR 0.14, p = 0.24, treatment 0 of 30 (0.0%), control 3 of 30 (10.0%), relative risk is not 0 because of continuity correction due to zero events (with reciprocal of the contrasting arm).
recovery time, 20.6% lower, relative time 0.79, p = 0.37, treatment 30, control 30.
[Dound], 11/16/2020, Randomized Controlled Trial, India, South Asia, peer-reviewed, 5 authors, this trial uses multiple treatments in the treatment arm (combined with vitamin C, vitamin K2-7, and l-selenomethionine) - results of individual treatments may vary. relative improvement on 6-point scale, 33.3% lower, RR 0.67, p < 0.001, treatment 100, control 100.
[Majeed], 10/11/2021, Double Blind Randomized Controlled Trial, India, South Asia, peer-reviewed, 4 authors, this trial uses multiple treatments in the treatment arm (combined with andrographolides, resveratrol, zinc, selenium, and piperine) - results of individual treatments may vary. risk of mechanical ventilation, 66.2% lower, RR 0.34, p = 1.00, treatment 0 of 45 (0.0%), control 1 of 47 (2.1%), relative risk is not 0 because of continuity correction due to zero events (with reciprocal of the contrasting arm).
risk of hospitalization, 79.7% lower, RR 0.20, p = 0.49, treatment 0 of 45 (0.0%), control 2 of 47 (4.3%), relative risk is not 0 because of continuity correction due to zero events (with reciprocal of the contrasting arm).
relative ordinal scale, 43.0% lower, RR 0.57, p = 0.004, treatment 45, control 47, day 28.
risk of no recovery, 24.6% lower, RR 0.75, p = 0.08, treatment 26 of 45 (57.8%), control 36 of 47 (76.6%), day 28.
time to viral-, 5.8% lower, relative time 0.94, p = 0.47, treatment 45, control 47.
[Pawar], 5/28/2021, Double Blind Randomized Controlled Trial, India, South Asia, peer-reviewed, 8 authors. risk of death, 81.8% lower, RR 0.18, p = 0.02, treatment 2 of 70 (2.9%), control 11 of 70 (15.7%).
risk of death, 60.0% lower, RR 0.40, p = 0.39, treatment 2 of 15 (13.3%), control 5 of 15 (33.3%), severe group.
risk of death, 90.9% lower, RR 0.09, p = 0.05, treatment 0 of 25 (0.0%), control 5 of 25 (20.0%), relative risk is not 0 because of continuity correction due to zero events (with reciprocal of the contrasting arm), moderate group.
risk of death, 66.7% lower, RR 0.33, p = 1.00, treatment 0 of 30 (0.0%), control 1 of 30 (3.3%), relative risk is not 0 because of continuity correction due to zero events (with reciprocal of the contrasting arm), mild group.
[Saber-Moghaddam], 1/3/2021, prospective, Iran, Middle East, peer-reviewed, 9 authors. risk of disease progression, 94.3% lower, RR 0.06, p = 0.001, treatment 0 of 21 (0.0%), control 8 of 20 (40.0%), relative risk is not 0 because of continuity correction due to zero events (with reciprocal of the contrasting arm).
risk of no recovery, 38.4% lower, RR 0.62, p = 0.04, treatment 11 of 21 (52.4%), control 17 of 20 (85.0%).
hospitalization time, 44.8% lower, relative time 0.55, p < 0.001, treatment 21, control 20.
[Sankhe], 8/10/2021, Randomized Controlled Trial, India, South Asia, peer-reviewed, 8 authors, this trial uses multiple treatments in the treatment arm (combined with gomutra, potassium alum, khadisakhar, bos indicus milk, ghee) - results of individual treatments may vary. risk of death, 88.9% lower, RR 0.11, p = 0.12, treatment 0 of 87 (0.0%), control 4 of 87 (4.6%), relative risk is not 0 because of continuity correction due to zero events (with reciprocal of the contrasting arm).
risk of mechanical ventilation, 75.0% lower, RR 0.25, p = 0.37, treatment 1 of 87 (1.1%), control 4 of 87 (4.6%).
risk of no 2-point improvement, 46.5% lower, RR 0.54, p = 0.002, treatment 29 of 87 (33.3%), control 60 of 87 (69.0%), odds ratio converted to relative risk, day 7 mid-recovery.
hospitalization time, 10.0% lower, relative time 0.90, p = 0.40, treatment 87, control 87.
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 calculations, which may differ from the effect a paper focuses on.
[Hassaniazad], 9/19/2021, Double Blind Randomized Controlled Trial, Iran, Middle East, peer-reviewed, 12 authors. relative improvement in SpO2, 45.7% higher, RR 1.46, p = 0.90, treatment 20, control 20.
[Tahmasebi], 3/28/2021, Double Blind Randomized Controlled Trial, Iran, Middle East, peer-reviewed, 14 authors. risk of death, 83.3% lower, RR 0.17, p = 0.11, treatment 1 of 40 (2.5%), control 6 of 40 (15.0%).
risk of death, 66.7% lower, RR 0.33, p = 1.00, treatment 0 of 20 (0.0%), control 1 of 20 (5.0%), relative risk is not 0 because of continuity correction due to zero events (with reciprocal of the contrasting arm), non-ICU patients.
risk of death, 80.0% lower, RR 0.20, p = 0.18, treatment 1 of 20 (5.0%), control 5 of 20 (25.0%), ICU patients.
[Valizadeh], 10/20/2020, Double Blind Randomized Controlled Trial, Iran, Middle East, peer-reviewed, 12 authors. risk of death, 50.0% lower, RR 0.50, p = 0.30, treatment 4 of 20 (20.0%), control 8 of 20 (40.0%).
References
Please send us corrections, updates, or comments. Vaccines and treatments are both extremely 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 the risk of COVID-19 becoming endemic; and increases mortality, morbidity, and collateral damage. 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. Treatment protocols for physicians are available from the FLCCC.
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