•Statistically significant improvements are seen for progression, recovery, and viral clearance. 24 studies from 24 independent teams in 16 different countries show statistically significant
improvements in isolation (14 for the most serious outcome).
•Results are robust — in exclusion sensitivity analysis 14 of 45
studies must be excluded to avoid finding statistically significant efficacy
in pooled analysis.
•Studies to date do not show a significant benefit for mortality.
Potential risks of the mechanism of action include the creation of dangerous variants, and mutagenicity, carcinogenicity, teratogenicity, and embryotoxicity [Hadj Hassine, Waters, Zhirnov].
•While many treatments have some level
of efficacy, they do not replace vaccines and other measures to avoid
infection.
Only 7% of favipiravir
studies show zero events in the treatment arm.
Multiple treatments are typically used
in combination, and other treatments
are 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.
Other meta analyses for favipiravir can be found in
[Hung, Lan], showing significant improvements for viral clearance, improvement, and hospital discharge.
Highlights
Favipiravir reduces
risk for COVID-19 with very high confidence for progression, viral clearance, and in pooled analysis, high confidence for recovery, and very low confidence for mortality, however increased risk is seen with high confidence for ICU admission.
Potential risks include the creation of dangerous variants, carcinogenicity, and genotoxicity.
We show traditional outcome specific analyses and combined
evidence from all studies, incorporating treatment delay, a primary
confounding factor in COVID-19 studies.
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).
We analyze all significant studies
concerning the use of
favipiravir
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.
An In Vitro study supports the efficacy of favipiravir [Unal].
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.
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, ventilation, ICU admission, hospitalization, progression, recovery, viral clearance, and peer reviewed studies.
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.
