•Statistically significant improvements are seen for mortality, ventilation, ICU admission, and hospitalization. 28 studies from 27 independent teams in 10 different countries show statistically significant
improvements in isolation (24 for the most serious outcome).
•Results are robust — in exclusion sensitivity analysis 29 of 48
studies must be excluded to avoid finding statistically significant efficacy
in pooled analysis.
•Most studies analyze existing use with diabetic patients. Many
results are subject to confounding by indication — metformin is
typically used early in the progression of type 2 diabetes. Prophylaxis
results typically include continuing use after infection and
hospitalization, and greater benefit is seen for more serious outcomes.
The beneficial effect of metformin may be more related to later stages of
COVID-19. The TOGETHER RCT shows
27% lower mortality. While not statistically significant, p = 0.53, this
is consistent with the mortality results from all studies,
33% [28‑39%].
•No treatment, vaccine, or
intervention is 100% effective and available. All practical, effective, and
safe means should be used based on risk/benefit analysis.
Multiple treatments are typically used
in combination, and other treatments
are more effective.
None of the metformin studies show zero events with treatment.
•All data to reproduce this paper and
sources are in the appendix.
Other meta analyses for metformin can be found in
[Hariyanto, Kow, Lukito, Yang], showing significant improvements for mortality and progression.
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
metformin
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 metformin [Parthasarathy].
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, 12, and 13
show forest plots for a random effects meta-analysis of
all studies with pooled effects, mortality results, ventilation, ICU admission, hospitalization, progression, recovery, cases, 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.
