Antiandrogens for COVID-19: real-time meta analysis of 49 studies
Abstract
Statistically significant lower risk is seen for mortality, ventilation, ICU admission, hospitalization, recovery, cases, and viral clearance. 29 studies from 23 independent teams in 12 countries show statistically significant
improvements.
Meta analysis using the most serious outcome reported shows
30% [21‑38%] lower risk. Results are similar for higher quality and peer-reviewed studies and better for Randomized Controlled Trials.
Results are robust — in exclusion sensitivity analysis 23 of 49
studies must be excluded to avoid finding statistically significant efficacy
in pooled analysis.
This analysis combines the results of several different antiandrogens. Results for individual treatments may vary.
No treatment or intervention
is 100% effective. All practical, effective, and safe means should be used
based on risk/benefit analysis.
Multiple treatments are typically used
in combination, and other treatments
may be more effective.
Highlights
Antiandrogens reduce
risk for COVID-19 with very high confidence for mortality, ventilation, hospitalization, recovery, viral clearance, and in pooled analysis, high confidence for ICU admission and cases, and very low confidence for progression.
Combined results of several different antiandrogens.
7th treatment shown effective with ≥3 clinical studies in
September 2020, now with p = 0.000000056 from 49 studies.
We show outcome specific analyses and combined evidence from all studies, incorporating treatment delay, a primary
confounding factor for COVID-19.
Real-time updates and corrections,
transparent analysis with all results in the same format, consistent protocol
for 69
treatments.
Figure 1.
A. Random effects
meta-analysis. This plot shows pooled effects,
see the specific outcome analyses for individual outcomes.
Analysis validating pooled outcomes for
COVID-19 can be found below.
Effect extraction is pre-specified, using the most serious outcome reported.
For details see the appendix.
B. Timeline of results in antiandrogen studies. The marked dates indicate the time when efficacy was known with a statistically significant improvement of ≥10% from ≥3 studies for pooled outcomes, one or more specific outcome, pooled outcomes in RCTs, and one or more specific outcome in RCTs. Efficacy based on RCTs only was delayed by 14.6 months, compared to using all studies. Efficacy based on specific outcomes was delayed by 11.6 months, compared to using pooled outcomes.
SARS-CoV-2 infection primarily begins in the upper respiratory
tract and may progress to the lower respiratory tract, other tissues, and the
nervous and cardiovascular systems, which may lead to cytokine storm,
pneumonia, ARDS, neurological issues Duloquin, Hampshire, Scardua-Silva, Sodagar, Yang,
cardiovascular complications Eberhardt, organ failure, and death.
Minimizing replication as early as possible is recommended.
SARS-CoV-2 infection and replication involves the complex interplay of 50+
host and viral proteins and other factors Note A, Malone, Murigneux, Lv, Lui, Niarakis, providing many
therapeutic targets for which many existing compounds have known activity.
Scientists have predicted that over 7,000 compounds may
reduce COVID-19 risk c19early.org, either by
directly minimizing infection or replication, by supporting immune system
function, or by minimizing secondary complications.
We analyze all significant
controlled studies of
Antiandrogens
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, studies within each treatment stage, individual outcomes, peer-reviewed studies, Randomized Controlled Trials (RCTs), and higher quality studies.
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.
An In Silico study supports the efficacy of antiandrogens Saih.
An In Vitro study supports the efficacy of antiandrogens Majidipur.
An In Vivo animal study supports the efficacy of antiandrogens Leach.
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.
Table 1 summarizes the results for all stages combined, for Randomized Controlled Trials, for peer-reviewed studies, after exclusions, and for specific outcomes.
Table 2 shows results by treatment stage.
Figure 3 plots individual results by treatment stage.
Figure 4, 5, 6, 7, 8, 9, 10, 11, 12, and 13
show forest plots for 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.
| Improvement | Studies | Patients | Authors | |
|---|---|---|---|---|
| All studies | 30% [21‑38%] **** | 49 | 120,172 | 533 |
| After exclusions | 32% [22‑40%] **** | 45 | 118,761 | 511 |
| Peer-reviewed studiesPeer-reviewed | 28% [18‑37%] **** | 43 | 118,669 | 483 |
| Randomized Controlled TrialsRCTs | 58% [36‑72%] **** | 17 | 2,902 | 216 |
| Mortality | 37% [21‑50%] **** | 32 | 112,973 | 366 |
| VentilationVent. | 47% [23‑64%] ** | 14 | 28,211 | 174 |
| ICU admissionICU | 36% [5‑57%] * | 11 | 8,017 | 104 |
| HospitalizationHosp. | 32% [11‑48%] ** | 16 | 9,228 | 222 |
| Recovery | 42% [27‑55%] **** | 11 | 2,063 | 130 |
| Cases | 8% [1‑14%] * | 12 | 105,457 | 100 |
| Viral | 49% [27‑65%] *** | 5 | 1,329 | 49 |
| RCT mortality | 62% [44‑75%] **** | 13 | 2,590 | 157 |
| RCT hospitalizationRCT hosp. | 32% [3‑53%] * | 8 | 2,304 | 131 |
| Early treatment | Late treatment | Prophylaxis | |
|---|---|---|---|
| All studies | 44% [31‑55%] **** | 63% [45‑75%] **** | 7% [-3‑16%] |
| After exclusions | 39% [29‑48%] **** | 63% [45‑75%] **** | 11% [2‑18%] * |
| Peer-reviewed studiesPeer-reviewed | 40% [31‑49%] **** | 61% [40‑75%] **** | 8% [-2‑17%] |
| Randomized Controlled TrialsRCTs | 64% [26‑82%] ** | 57% [29‑73%] *** | |
| Mortality | 39% [29‑48%] **** | 63% [43‑75%] **** | 7% [-12‑22%] |
| VentilationVent. | 95% [60‑99%] ** | 44% [23‑59%] *** | 46% [-12‑74%] |
| ICU admissionICU | 40% [22‑55%] *** | 31% [-88‑75%] | |
| HospitalizationHosp. | 81% [46‑93%] ** | 21% [-10‑43%] | 21% [-23‑50%] |
| Recovery | 68% [41‑83%] *** | 38% [21‑52%] *** | |
| Cases | 8% [1‑14%] * |
||
| Viral | 58% [2‑82%] * | 37% [21‑50%] **** | |
| RCT mortality | 71% [-75‑95%] | 61% [39‑75%] **** | |
| RCT hospitalizationRCT hosp. | 81% [46‑93%] ** | 10% [-20‑33%] |
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Figure 3. Scatter plot showing the most serious outcome in all studies, and for studies within each stage. Diamonds shows the results of random effects meta-analysis.
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Figure 4. Random effects meta-analysis for all studies.
This plot shows pooled effects,
see the specific outcome analyses for individual outcomes.
Analysis validating pooled outcomes for
COVID-19 can be found below.
Effect extraction is pre-specified, using the most serious outcome reported.
For details see the appendix.
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Figure 5. Random effects meta-analysis for mortality results.
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Figure 6. Random effects meta-analysis for ventilation.
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Figure 7. Random effects meta-analysis for ICU admission.
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Figure 8. Random effects meta-analysis for hospitalization.
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Figure 9. Random effects meta-analysis for progression.
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Figure 10. Random effects meta-analysis for recovery.
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Figure 11. Random effects meta-analysis for cases.
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Figure 12. Random effects meta-analysis for viral clearance.
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Figure 13. Random effects meta-analysis for peer reviewed studies.
Effect extraction is pre-specified, using the most serious outcome reported,
see the appendix for details.
Analysis validating pooled outcomes for
COVID-19 can be found below.
Zeraatkar et al. analyze 356 COVID-19 trials, finding no significant
evidence that preprint results are inconsistent with peer-reviewed studies.
They also show extremely long peer-review delays, with a median of 6 months to
journal publication. A six month delay was equivalent to around 1.5 million
deaths during the first two years of the pandemic. Authors recommend using
preprint evidence, with appropriate checks for potential falsified data, which
provides higher certainty much earlier. Davidson et al. also showed no
important difference between meta analysis results of preprints and
peer-reviewed publications for COVID-19, based on 37 meta analyses including
114 trials.
Figure 14 shows a comparison of results for RCTs and non-RCT studies.
Random effects meta analysis of RCTs shows
58% improvement,
compared to 18% for other studies.
Figure 15, 16, and 17
show forest plots for random effects meta-analysis of
all Randomized Controlled Trials, RCT mortality results, and RCT hospitalization results.
RCT results are included in Table 1 and Table 2.
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Figure 14. Results for RCTs and non-RCT studies.
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Figure 15. Random effects meta-analysis for all Randomized Controlled Trials.
This plot shows pooled effects,
see the specific outcome analyses for individual outcomes.
Analysis validating pooled outcomes for
COVID-19 can be found below.
Effect extraction is pre-specified, using the most serious outcome reported.
For details see the appendix.
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Figure 16. Random effects meta-analysis for RCT mortality results.
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Figure 17. Random effects meta-analysis for RCT hospitalization results.
RCTs help to make study groups more similar and can provide a higher level of
evidence, however they are subject to many biases Jadad, and
analysis of double-blind RCTs has identified extreme levels of bias
Gøtzsche.
For COVID-19, the overhead may delay treatment, dramatically compromising
efficacy; they may encourage monotherapy for simplicity at the cost of
efficacy which may rely on combined or synergistic effects; the participants
that sign up may not reflect real world usage or the population that benefits
most in terms of age, comorbidities, severity of illness, or other factors;
standard of care may be compromised and unable to evolve quickly based on
emerging research for new diseases; errors may be made in randomization and
medication delivery; and investigators may have hidden agendas or vested
interests influencing design, operation, analysis, reporting, and the
potential for fraud. All of these biases have been observed with COVID-19
RCTs. There is no guarantee that a specific RCT provides a higher level of
evidence.
RCTs are expensive and many RCTs are funded
by pharmaceutical companies or interests closely aligned with pharmaceutical
companies. For COVID-19, this creates an incentive to show efficacy for
patented commercial products, and an incentive to show a lack of efficacy for
inexpensive treatments. The bias is expected to be significant, for example
Als-Nielsen et al. analyzed 370 RCTs from Cochrane reviews, showing that
trials funded by for-profit organizations were 5 times more likely to
recommend the experimental drug compared with those funded by nonprofit
organizations. For COVID-19, some major philanthropic organizations are
largely funded by investments with extreme conflicts of interest for and
against specific COVID-19 interventions.
High quality RCTs for novel acute diseases are more challenging, with
increased ethical issues due to the urgency of treatment, increased risk due
to enrollment delays, and more difficult design with a rapidly evolving
evidence base. For COVID-19, the most common site of initial infection is the
upper respiratory tract. Immediate treatment is likely to be most successful
and may prevent or slow progression to other parts of the body. For a
non-prophylaxis RCT, it makes sense to provide treatment in advance and
instruct patients to use it immediately on symptoms, just as some governments
have done by providing medication kits in advance. Unfortunately, no RCTs have
been done in this way. Every treatment RCT to date involves delayed treatment.
Among the 69 treatments we have analyzed,
63% of RCTs involve very late treatment 5+ days after
onset. No non-prophylaxis COVID-19 RCTs match the potential real-world use of
early treatments. They may more accurately represent results for treatments
that require visiting a medical facility, e.g., those requiring intravenous
administration.
Evidence shows that non-RCT studies can also
provide reliable results. Concato et al. found that well-designed
observational studies do not systematically overestimate the magnitude of the
effects of treatment compared to RCTs. Anglemyer et al. summarized reviews
comparing RCTs to observational studies and found little evidence for
significant differences in effect estimates. Lee et al. showed 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 may
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.
Currently, 44 of the treatments we analyze show statistically significant efficacy or harm, defined as ≥10% decreased risk or >0% increased risk from ≥3 studies. Of these, 28 have been confirmed in RCTs, with a mean delay of 7.0 months. When considering only low cost treatments, 23 have been confirmed with a delay of 8.4 months. For the 16 unconfirmed treatments, 3 have zero RCTs to date. The point estimates for the remaining 13 are all consistent with the overall results (benefit or harm), with 10 showing >20%. The only treatments showing >10% efficacy for all studies, but <10% for RCTs are sotrovimab and aspirin.
We need to
evaluate each trial on its own merits. RCTs for a given medication and disease
may be more reliable, however they may also be less reliable. For off-patent
medications, very high conflict of interest trials may be more likely to be
RCTs, and more likely to be large trials that dominate meta analyses.
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 can be easily influenced by potential bias, may ignore
or underemphasize serious issues not captured in the checklists, and may
overemphasize issues unlikely to alter outcomes in specific cases (for example
certain specifics of randomization with a very large effect size and
well-matched baseline characteristics).
The studies excluded are as below.
Figure 18 shows a forest plot for random
effects meta-analysis of all studies after exclusions.
Cadegiani, potential randomization failure.
Cadegiani (B), significant unadjusted differences between groups.
Holt, unadjusted results with no group details.
Jiménez-Alcaide, excessive unadjusted differences between groups. Excluded results: case.
Kazan, excessive unadjusted differences between groups.
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Figure 18. Random effects meta-analysis for all studies after exclusions.
This plot shows pooled effects,
see the specific outcome analyses for individual outcomes.
Analysis validating pooled outcomes for
COVID-19 can be found below.
Effect extraction is pre-specified, using the most serious outcome reported.
For details see the appendix.
Heterogeneity in COVID-19 studies arises from many factors including:
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.
Baloxavir studies for influenza also show that treatment delay is critical
— Ikematsu et al. report an 86% reduction in cases for post-exposure
prophylaxis, Hayden et al. show a 33 hour reduction in the time to
alleviation of symptoms for treatment within 24 hours and a reduction of 13
hours for treatment within 24-48 hours, and Kumar et al. report only 2.5
hours improvement for inpatient treatment.
| Treatment delay | Result |
| Post-exposure prophylaxis | 86% fewer cases Ikematsu |
| <24 hours | -33 hours symptoms Hayden |
| 24-48 hours | -13 hours symptoms Hayden |
| Inpatients | -2.5 hours to improvement Kumar |
Figure 19 shows a mixed-effects meta-regression for efficacy
as a function of treatment delay in COVID-19 studies from 69 treatments, showing
that efficacy declines rapidly with treatment delay. Early treatment is
critical for COVID-19.
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Figure 19. Early treatment is more effective. Meta-regression showing efficacy as a function of treatment delay in COVID-19 studies from 69 treatments.
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, for example as in
López-Medina et al.
Efficacy may
depend critically on the distribution of SARS-CoV-2 variants encountered by
patients. Risk varies significantly across variants Korves, 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 degree to which
TMPRSS2 contributes to viral entry can differ across variants
Peacock, Willett.
Effectiveness may depend strongly on the dosage and treatment regimen.
The use
of other treatments may significantly affect outcomes, including supplements,
other medications, or other interventions such as prone positioning.
Treatments may be synergistic Alsaidi, Andreani, De Forni, Fiaschi, Jeffreys, Jitobaom, Jitobaom (B), Ostrov, Said, Thairu, Wan, therefore
efficacy may depend strongly on combined treatments.
The
quality of medications may vary significantly between manufacturers and
production batches, which may significantly affect efficacy and safety.
Williams et al. analyze ivermectin from 11 different sources, showing
highly variable antiparasitic efficacy across different manufacturers.
Xu et al. analyze a treatment from two different manufacturers, showing 9
different impurities, with significantly different concentrations for each
manufacturer.
Across all
studies there is a strong association between different outcomes, for example
improved recovery is strongly associated with lower mortality. However,
efficacy may differ depending on the effect measured, for example a treatment
may be more effective against secondary complications and have minimal effect
on viral clearance.
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 early treatment is very effective.
All meta analyses combine heterogeneous studies, varying in population,
variants, and potentially all factors above, and therefore may obscure
efficacy by including studies where treatment is less effective. Generally, we
expect the estimated effect size from meta analysis to be less than that for
the optimal case.
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.
While we present results for all studies, we also present treatment time and
individual outcome analyses, which may be more informative for specific use
cases.
For COVID-19, delay in clinical results translates into
additional death and morbidity, as well as additional economic and societal
damage. Combining the results of studies reporting different outcomes is
required.
There may be no mortality in a trial with low-risk patients,
however a reduction in severity or improved viral clearance may translate
into lower mortality in a high-risk population.
Different studies may report lower severity, improved recovery, and lower mortality,
and the significance may be very high when combining the results.
"The studies reported different outcomes"
is not a good reason for disregarding results.
We present both specific outcome and pooled analyses.
In order to combine the results of studies reporting different outcomes we use
the most serious outcome reported in each study, based on the thesis that
improvement in the most serious outcome provides comparable measures of
efficacy for a treatment. A critical advantage of this approach is
simplicity and transparency.
There are many other ways to combine evidence for different outcomes, along
with additional evidence such as dose-response relationships, however these
increase complexity.
Another way to view pooled analysis is that we are using more of
the available information. Logically we should, and do, use additional
information. For example dose-response and
treatment delay-response relationships provide significant additional evidence
of efficacy that is considered when reviewing the evidence for a
treatment.
Trials with high-risk patients may be restricted due to ethics for treatments
that are known or expected to be effective, and they increase difficulty for
recruiting. Using less severe outcomes as a proxy for more serious outcomes
allows faster collection of evidence.
For many COVID-19 treatments, a reduction in mortality logically
follows from a reduction in hospitalization, which follows from a reduction in
symptomatic cases, which follows from a reduction in PCR positivity. We can
directly test this for COVID-19.
Analysis of the the association between different outcomes across studies from
all 69
treatments we cover confirms the validity of pooled outcome analysis for COVID-19.
Figure 20 shows that lower hospitalization is very strongly associated
with lower mortality (p < 0.000000000001).
Similarly, Figure 21 shows that improved recovery is very strongly associated
with lower mortality (p < 0.000000000001).
Considering the extremes, Singh et al. show an association between viral clearance and
hospitalization or death, with p = 0.003 after excluding one large
outlier from a mutagenic treatment, and based on 44 RCTs including 52,384
patients.
Figure 22 shows that improved viral clearance is strongly associated
with fewer serious outcomes. The association is very similar to
Singh et al., with higher confidence due to the larger number of
studies. As with Singh et al., the confidence increases
when excluding the outlier treatment, from p = 0.0000031 to p = 0.0000000067.
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Figure 20. Lower hospitalization is associated with lower mortality, supporting pooled outcome analysis.
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Figure 21. Improved recovery is associated with lower mortality, supporting pooled outcome analysis.
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Figure 20. Improved viral clearance is associated with fewer serious outcomes, supporting pooled outcome analysis.
Currently, 44 of the treatments we analyze show statistically significant efficacy or harm, defined as ≥10% decreased risk or >0% increased risk from ≥3 studies. 88% of these have been confirmed with one or more specific outcomes, with a mean delay of 4.7 months. When restricting to RCTs only, 54% of treatments showing statistically significant efficacy/harm with pooled effects have been confirmed with one or more specific outcomes, with a mean delay of 5.5 months.
Figure 23 shows when treatments were found effective during the
pandemic. Pooled outcomes often resulted in earlier detection of efficacy.
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Figure 23. The time when studies showed that
treatments were effective, defined as statistically significant improvement of
≥10% from ≥3 studies.
Pooled results typically show efficacy earlier than specific
outcome results. Results from all studies often shows efficacy much earlier
than when restricting to RCTs.
Results reflect conditions as used in trials to date, these depend on the
population treated, treatment delay, and treatment regimen.
Pooled analysis could hide efficacy, for example a treatment that is
beneficial for late stage patients but has no effect on viral clearance may
show no efficacy if most studies only examine viral clearance. In practice, it
is rare for a non-antiviral treatment to report viral clearance and to not
report clinical outcomes; and in practice other sources of heterogeneity such
as difference in treatment delay is more likely to hide efficacy.
Analysis validates the use of pooled effects and shows significantly faster
detection of efficacy on average.
However, as with all meta analyses, it is important to review the different
studies included. We also present individual outcome analyses, which may be
more informative for specific use cases.
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, twitter.com.
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.
Figure 24 shows a scatter plot of
results for prospective and retrospective studies.
46% of retrospective studies
report a statistically significant positive effect for
one or more outcomes, compared to
76% of prospective studies, consistent with a bias toward publishing negative results.
The median effect size for
retrospective studies is 21% improvement,
compared to 72% for prospective
studies, suggesting a potential bias towards publishing results showing lower efficacy.
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Figure 24. Prospective vs. retrospective studies.
The diamonds show the results of random effects meta-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 25 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 25. Example funnel plot analysis for simulated perfect trials.
Summary statistics from
meta analysis necessarily lose information. As with all meta analyses, studies
are heterogeneous, with differences
in treatment delay, treatment regimen, patient demographics, variants,
conflicts of interest, standard of care, and other factors. We provide analyses for specific
outcomes and by treatment delay, and we aim to identify key characteristics in
the forest plots and summaries. Results should be viewed in the context of
study characteristics.
Some analyses classify treatment based on early or late
administration, as done here, while others distinguish between mild, moderate,
and severe cases. 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.
Details of treatment delay per patient is often not available.
For example, a study may treat 90% of patients relatively early, but the
events driving the outcome may come from 10% of patients treated very late.
Our 5 day cutoff for early treatment may be too conservative, 5 days may be too late in many cases.
Comparison across treatments is confounded by differences in
the studies performed, for example dose, variants, and conflicts of interest.
Trials with conflicts of interest may use designs better suited to the
preferred outcome.
In some cases, the most serious outcome has very few events,
resulting in lower confidence results being used in pooled analysis, however
the method is simpler and more transparent. This is less critical as the
number of studies increases. Restriction to outcomes with sufficient power may
be beneficial in pooled analysis and improve accuracy when there are few
studies, however we maintain our pre-specified method to avoid any
retrospective changes.
Studies show that combinations of treatments can be highly
synergistic and may result in many times greater efficacy than individual
treatments alone Alsaidi, Andreani, De Forni, Fiaschi, Jeffreys, Jitobaom, Jitobaom (B), Ostrov, Said, Thairu, Wan.
Therefore standard of care may be critical and benefits may diminish or
disappear if standard of care does not include certain treatments.
This real-time analysis is constantly updated based on
submissions. Accuracy benefits from widespread review and submission of
updates and corrections from reviewers. Less popular treatments may receive
fewer reviews.
No treatment or intervention is 100% available and
effective for all current and future variants. Efficacy may vary significantly
with different variants and within different populations. All treatments have
potential side effects. Propensity to experience side effects may be predicted
in advance by qualified physicians. We do not provide medical advice. Before
taking any medication, consult a qualified physician who can compare all
options, provide personalized advice, and provide details of risks and
benefits based on individual medical history and situations.
1 of the 49
studies compare against other treatments, which may reduce the effect
seen.
4 of 49 studies
combine treatments. The results of
antiandrogens
alone may differ.
2 of 17 RCTs use combined treatment.
Other meta analyses show significant improvements with antiandrogens for mortality Cheema, Kotani, hospitalization Cheema, recovery Cheema, and progression Kotani.
Mauvais-Jarvis et al. present a review covering antiandrogen for COVID-19.
SARS-CoV-2 infection and replication involves a complex interplay of 50+ host
and viral proteins and other factors Lui, Lv, Malone, Murigneux, Niarakis,
providing many therapeutic targets.
Over 7,000 compounds have been predicted to reduce COVID-19
risk c19early.org, either by directly
minimizing infection or replication, by supporting immune system function, or
by minimizing secondary complications.
Figure 26 shows an overview of the results for antiandrogens
in the context of multiple COVID-19 treatments, and Figure 27 shows a plot
of efficacy vs. cost for COVID-19 treatments.
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Figure 26.
Scatter plot showing results within the context of multiple COVID-19 treatments.
Diamonds shows the results of random effects meta-analysis.
0.6% of 7,000+ proposed treatments show efficacy
c19early.org (B).
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Figure 27. Efficacy vs. cost for COVID-19 treatments.
Antiandrogens are
an effective treatment for COVID-19.
Statistically significant lower risk is seen for mortality, ventilation, ICU admission, hospitalization, recovery, cases, and viral clearance. 29 studies from 23 independent teams in 12 countries show statistically significant
improvements.
Meta analysis using the most serious outcome reported shows
30% [21‑38%] lower risk. Results are similar for higher quality and peer-reviewed studies and better for Randomized Controlled Trials.
Results are robust — in exclusion sensitivity analysis 23 of 49
studies must be excluded to avoid finding statistically significant efficacy
in pooled analysis.
This analysis combines the results of several different antiandrogens. Results for individual treatments may vary.
Abbasi:
RCT including 51 spironolactone patients and 87 control patients in Iran, showing improved recovery with spironolactone, sitagliptin, and the combination of both.
Barnette:
RCT with 98 hospitalized moderate/severe patients treated with sabizabulin and 52 control patients, showing lower mortality with treatment. Sabizabulin 9mg for up to 21 days. For more discussion see twitter.com (B), twitter.com (C), twitter.com (D).
Bennani:
Retrospective 118 prostate cancer patients, 4 on androgren deprivation therapy, not showing significant differences (as expected with only 4 patients in the treatment group).
Cadegiani (C):
RCT 177 women in Brazil, 75 treated with proxalutamide, showing significantly lower hospitalization with treatment.
Cadegiani:
RCT 130 outpatients in Brazil, 54 treated with dutasteride, showing faster recovery with treatment. All patients received nitazoxanide. There were no hospitalizations, mechanical ventilation, or deaths. Some percentages for viral clearance in Table 3 do not match the group sizes, and a third-party analysis suggests possible randomization failure. 34110420.2.0000.0008.
Cadegiani (B):
Prospective study of 270 female COVID-19 patients in Brazil, 75 with hyperandrogenism, of which 8 were on spironolactone. Results suggest that HA patients may be at increased risk, and that spironolactone use may reduce the risk compared to both other HA patients and non-HA patients. SOC included other treatments and there was no mortality or hospitalization.
Cadegiani (D):
RCT 778 hospitalized patients in Brazil, 423 treated with proxalutamide, showing significantly lower mortality and improved recovery with treatment. NCT04728802 and NCT05126628. Authors note that cases in this trial were predominantly the P.1 Gamma variant, for which proxalutamide may be more effective compared to other variants.
Cousins:
PSM retrospective 898,303 hospitalized COVID-19 patients in the USA, 16,324 on spironolactone, showing lower mortality and ventilation with spironolactone use.
Cousins (B):
PSM retrospective 64,349 COVID-19 patients in the USA, showing spironolactone associated with lower ICU admission.
Authors also present In Vitro research showing dose-dependent inhibition in a human lung epithelial cell line.
Authors also present In Vitro research showing dose-dependent inhibition in a human lung epithelial cell line.
Davarpanah:
Prospective study of 206 outpatients in Iran, 103 treated with spironolactone and sitagliptin, showing lower hospitalization and faster recovery with treatment. spironolactone 100mg and sitagliptin 100mg daily.
Davidsson:
Retrospective 655 prostate cancer patients in Sweden, showing no significant difference in seropositivity with ADT.
Duarte:
Retrospective 199 prostate cancer patients hospitalized with COVID-19 in Brazil, showing no significant difference in mortality with active ADT.
Ersoy:
Retrospective 30 COVID-19 ARDS ICU patients and 30 control patients, showing lower mortality with treatment.
Gedeborg:
Case control study with 474 patients that died of COVID-19 in Sweden, showing higher risk with ADT, without statistical significance.
Ghandehari:
RCT 42 hospitalized patients in the USA, showing improved recovery and lower progression with progesterone treatment.
Gomaa:
RCT with 50 hospitalized COVID+ patients in Egypt, 25 treated with glycyrrhizin and boswellic acid, showing improved recovery with treatment. Glycyrrhizin 60mg and boswellic acid 200mg bid for 2 weeks. NCT04487964.
Gordon:
Phase 2 RCT of sabizabulin showing lower mortality with treatment. For more discussion see twitter.com (E).
Goren:
Prospective study of 77 men hospitalized with COVID-19, 12 taking antiandrogens (9 dutasteride, 2 finasteride, 1 spironolactone), showing lower ICU admission with treatment (statistically significant with age-matched controls only when excluding the spironolactone patient). NCT04368897.
Holt:
Retrospective 689 hospitalized COVID-19 patients in Denmark, showing higher risk of ICU/death with spironolactone use in unadjusted results subject to confounding by indication.
Hsieh:
Prospective study of 260 hospitalized patients in Taiwan, 117 treated with herbal formula Jing Si Herbal Tea which includes antiandrogen glycyrrhiza glabra, showing improved recovery with treatment, with statistical significance for SpO2, Ct score, CRP, and Brixia score.
Hunt:
Retrospective 26,508 consecutive COVID+ veterans in the USA, showing lower mortality with multiple treatments including anti-androgens. Treatment was defined as drugs administered ≥50% of the time within 2 weeks post-COVID+, and may be a continuation of prophylactic treatment in some cases, and may be early or late treatment in other cases. Further reduction in mortality was seen with combinations of treatments.
Ianhez:
Retrospective survey of 41,529 participants, including 571 on antiandrogen therapy, showing no significant association between antiandrogen use and COVID-19 incidence, hospitalization, or ICU admission/mechanical ventilation.
Israel:
Case control study examining medication usage with a healthcare database in Israel, showing lower risk of hospitalization with dutasteride.
Jeon:
Retrospective 6,462 liver cirrhosis patients in South Korea, with 67 COVID+ cases, showing significantly lower cases with spironolactone treatment. Death and ICU results per group are not provided.
Jiménez-Alcaide:
Retrospective 1,349 prostate cancer patients in Spain, 156 on ADT, showing no significant differences in COVID-19 outcomes with treatment.
Kazan:
Retrospective 365 prostate cancer patients in Turkey, 138 treated with ADT, showing no significant differences with treatment.
Kintor:
RCT 733 outpatients, 99% in the USA, showing lower hospitalization/death, and significantly reduced viral load with proxalutamide treatment. The viral clearance result is from Ma et al..
Klein:
Retrospective 1,779 prostate cancer patients, showing no significant differences in COVID-19 outcomes with ADT.
Koskinen:
Retrospective 352 prostate cancer patients in Finland, showing no significant differences in COVID-19 with ADT.
Kotfis:
RCT with 24 patients treated with potassium canrenoate and 25 placebo patients in Poland, showing no significant differences.
Kwon:
Retrospective 5,211 prostate cancer patients, 799 on ADT, showing no significant differences in COVID-19 outcomes with treatment.
Lazzeri:
Retrospective case-control study in Italy with 943 male COVID-19 patients, 45 on chronic 5ARI treatment (finasteride/dutasteride). There was significantly fewer COVID-19 patients >55 on 5ARI treatment compared to age-matched controls (5.57 vs. 8.14%, p=0.0083). The difference was greater for men aged >65 (7.14 vs. 12.31%, p=0.0001). There was no significant difference for ICU admission or death.
Lee (B):
Retrospective 3,057 androgen deprivation therapy patients in the USA, and 36,096 control patients with cancer, showing lower risk of cases and severity with ADT.
Lyon:
Retrospective 944 5ARI users in the USA and 944 matched controls, showing lower risk of COVID-19 cases with treatment.
MacFadden:
Retrospective 26,121 cases and 2,369,020 controls ≥65yo in Canada, showing lower cases with chronic use of spironolactone.
Mareev:
Prospective 103 PCR+ patients in Russia, 33 treated with bromexhine+spironolactone, showing lower PCR+ at day 10 or hospitalization >10 days with treatment. Bromhexine 8mg 4 times daily, spironolactone 25-50 mg/day for 10 days.
McCoy:
RCT 268 male patients in Brazil, 134 treated with proxalutamide, showing significantly lower hospitalization and mechanical ventilation. NCT04446429.
This paper was censored without details or author response, and the editors have ignored the authors, see twitter.com (F).
This paper was censored without details or author response, and the editors have ignored the authors, see twitter.com (F).
Montopoli:
Retrospective 5,273 prostate cancer patients on androgen-deprivation therapy (ADT), and 37,161 not on ADT, showing lower risk of cases with treatment.
Nicastri:
RCT 68 patients in Italy showing improved viral clearance with raloxifene.
Nickols:
Early terminated RCT with 62 very late stage (79% on oxygen) degarelix patients and 34 placebo patients, showing no significant differences with treatment.
For discussion of many issues with this study see twitter.com (G).
For discussion of many issues with this study see twitter.com (G).
Patel:
Retrospective 58 prostate cancer patients in the USA, showing lower risk of hospitalization with ADT.
Schmidt:
Retrospective 1,106 prostate cancer patients, showing no significant differences in COVID-19 outcomes with ADT.
Shah:
Retrospective 465 prostate cancer patients, showing no significant difference in COVID-19 outcomes with ADT.
Shaw:
PSM retrospective 144 alopecia patients in the USA, showing no significant difference in COVID-19 cases with anti-androgen use. The supplemental appendix is not available.
Vicenzi:
Retrospective 69 consecutive hospitalized COVID-19 patients in Italy, 30 patients receiving canrenone, and 39 treated with vasodilator agents or renin–angiotensin–aldosterone system (RAAS) inhibitors, showing lower mortality with canrenone.
Wadhwa:
RCT 120 hospitalized patients in India, 74 treated with spironolactone and dexamethasone, and 46 with dexamethasone, showing lower progression with treatment. Spironolactone 50mg once daily day 1, 25mg once daily until day 21.
Welén (B):
Retrospective 7,894 COVID+ prostate cancer patients, analyzing patients on antiandrogen treatment, ADT, and ADT + abiraterone acetate or enzalutamide, showing mixed results and higher mortality for ADT + abiraterone acetate or enzalutamide.
This paper also includes a small RCT which is listed separately, and an In Vitro HBEC study showing no significant differences (p = 0.084). The supplementary data is not currently available. NCT04475601.
For discussion of issues with this study see sciencedirect.com, sciencedirect.com (B), sciencedirect.com (C), sciencedirect.com (D).
This paper also includes a small RCT which is listed separately, and an In Vitro HBEC study showing no significant differences (p = 0.084). The supplementary data is not currently available. NCT04475601.
For discussion of issues with this study see sciencedirect.com, sciencedirect.com (B), sciencedirect.com (C), sciencedirect.com (D).
Welén:
Very small late stage RCT with 10 control patients and 29 enzalutamide patients, showing mixed results. Discharge and hospitalization time favored the control group, while viral load reduction was better with treatment on days 4&6 (day 4 ΔCt −5.6 p = 0.084), and the only death occurred in the control group. 27% of enzalutamide patients had diabetes compared to 0% of the control group. This paper also includes a retrospective study which is listed separately, and an In Vitro HBEC study showing no significant differences (p = 0.084). The supplementary data is not currently available. NCT04475601.
For discussion of issues with this study see sciencedirect.com, sciencedirect.com (B), sciencedirect.com (C), sciencedirect.com (D).
For discussion of issues with this study see sciencedirect.com, sciencedirect.com (B), sciencedirect.com (C), sciencedirect.com (D).
Zarehoseinzade:
RCT 80 hospitalized COVID-19 patients in Iran, 40 treated with finasteride, showing no significant differences other than improved oxygen saturation on the 5th day with treatment. There was significantly more patients with diabetes in the control group. 5mg finasteride for 7 days. IRCT20200505047318N1.
We perform ongoing searches of PubMed, medRxiv, Europe PMC,
ClinicalTrials.gov, The Cochrane Library, Google Scholar, Research
Square, ScienceDirect, Oxford University Press, the reference lists of other
studies and meta-analyses, and submissions to the site c19early.org.
Search terms are antiandrogen and COVID-19 or SARS-CoV-2. Automated searches are performed twice daily, with all matches reviewed for inclusion.
All studies regarding the use of antiandrogen 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 have preference. Mortality alone is preferred over combined outcomes.
Outcomes with zero events in both arms are not used, the next most serious
outcome with one or more events is used. 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 outcomes are considered more important than viral test 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 little or
no room for an effective treatment to do better, however faster recovery is
valuable.
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 compute the relative risk when
possible, or convert 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 propensity score matching and multivariable regression has preference
over propensity score matching or weighting, which has preference over
multivariable regression. Adjusted results have preference over unadjusted
results for a more serious outcome when the adjustments significantly alter
results. 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
(3.12.3) with
scipy (1.13.0), pythonmeta (1.26), numpy (1.26.4), statsmodels (0.14.2), and plotly (5.21.0).
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.
Results are presented with 95% confidence intervals. Heterogeneity among studies was
assessed using the I2 statistic.
Mixed-effects meta-regression results are computed with R (4.1.2) using the metafor
(3.0-2) and rms (6.2-0) packages, and using the most serious sufficiently powered outcome.
For all statistical tests, a p-value less than 0.05 was considered statistically significant.
Grobid 0.8.0 is used to parse PDF documents.
We have classified studies as early treatment if most patients
are not already at a severe stage at the time of treatment (for example based
on oxygen status or lung involvement), 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.
We received no funding, this research is done in our spare
time. We have no affiliations with any pharmaceutical companies or political
parties.
A summary of study results is below. Please submit
updates and corrections at https://c19early.org/aameta.html.
Effect extraction follows pre-specified rules as detailed above
and gives priority to more serious outcomes.
For pooled analyses, the first (most serious) outcome is used, which may
differ from the effect a paper focuses on.
Other outcomes are used in outcome specific analyses.
| Cadegiani (C), 7/10/2021, Double Blind Randomized Controlled Trial, Brazil, preprint, 7 authors, study period 4 January, 2021 - 28 February, 2021. | risk of death, 63.4% lower, RR 0.37, p = 1.00, treatment 0 of 75 (0.0%), control 1 of 102 (1.0%), NNT 102, relative risk is not 0 because of continuity correction due to zero events (with reciprocal of the contrasting arm). |
| risk of mechanical ventilation, 89.7% lower, RR 0.10, p = 0.07, treatment 0 of 75 (0.0%), control 5 of 102 (4.9%), NNT 20, relative risk is not 0 because of continuity correction due to zero events (with reciprocal of the contrasting arm). | |
| risk of hospitalization, 85.7% lower, RR 0.14, p < 0.001, treatment 2 of 75 (2.7%), control 19 of 102 (18.6%), NNT 6.3. | |
| Cadegiani, 2/1/2021, Double Blind Randomized Controlled Trial, Brazil, peer-reviewed, 4 authors, excluded in exclusion analyses: potential randomization failure. | risk of no recovery, 62.0% lower, RR 0.38, p = 0.009, treatment 7 of 44 (15.9%), control 18 of 43 (41.9%), NNT 3.9. |
| recovery time, 43.6% lower, relative time 0.56, p < 0.001, treatment 44, control 43, all symptoms. | |
| recovery time, 40.2% lower, relative time 0.60, p < 0.001, treatment 44, control 43, all symptoms except loss of smell or taste. | |
| Cadegiani (B), 10/6/2020, prospective, Brazil, preprint, 4 authors, average treatment delay 3.0 days, excluded in exclusion analyses: significant unadjusted differences between groups. | recovery time, 76.7% lower, relative time 0.23, p = 0.006, treatment 8, control 262, excluding anosmia. |
| recovery time, 82.8% lower, relative time 0.17, p = 0.002, treatment 8, control 262, including anosmia. | |
| time to viral-, 37.9% lower, relative time 0.62, p = 0.02, treatment 8, control 262. | |
| Hunt, 6/29/2022, retrospective, USA, peer-reviewed, 8 authors, study period 1 March, 2020 - 10 September, 2020. | risk of death, 39.0% lower, RR 0.61, p < 0.001, treatment 167 of 1,788 (9.3%), control 1,445 of 24,720 (5.8%), adjusted per study, day 30. |
| Kintor, 4/5/2022, Double Blind Randomized Controlled Trial, placebo-controlled, USA, preprint, 1 author, study period 5 March, 2021 - 1 April, 2022, trial NCT04870606 (history). | risk of death, 66.7% lower, RR 0.33, p = 1.00, treatment 0 of 365 (0.0%), control 1 of 365 (0.3%), NNT 365, relative risk is not 0 because of continuity correction due to zero events (with reciprocal of the contrasting arm), 1+ days of treatment, group sizes approximated. |
| risk of hospitalization, 50.0% lower, RR 0.50, p = 0.38, treatment 4 of 365 (1.1%), control 8 of 365 (2.2%), NNT 91, 1+ days of treatment, group sizes approximated. | |
| risk of death, 66.6% lower, RR 0.33, p = 1.00, treatment 0 of 360 (0.0%), control 1 of 361 (0.3%), NNT 361, relative risk is not 0 because of continuity correction due to zero events (with reciprocal of the contrasting arm), >1 day of treatment, group sizes approximated. | |
| risk of hospitalization, 71.3% lower, RR 0.29, p = 0.18, treatment 2 of 360 (0.6%), control 7 of 361 (1.9%), NNT 72, >1 day of treatment, group sizes approximated. | |
| risk of death, 66.6% lower, RR 0.33, p = 1.00, treatment 0 of 346 (0.0%), control 1 of 347 (0.3%), NNT 347, relative risk is not 0 because of continuity correction due to zero events (with reciprocal of the contrasting arm), >7 days of treatment, group sizes approximated. | |
| risk of hospitalization, 92.3% lower, RR 0.08, p = 0.03, treatment 0 of 346 (0.0%), control 6 of 347 (1.7%), NNT 58, relative risk is not 0 because of continuity correction due to zero events (with reciprocal of the contrasting arm), >7 days of treatment, group sizes approximated. | |
| risk of no viral clearance, 73.9% lower, RR 0.26, p < 0.001, treatment 365, control 365, group sizes approximated, day 7. | |
| McCoy, 12/30/2020, Double Blind Randomized Controlled Trial, Brazil, peer-reviewed, 15 authors, study period 15 June, 2020 - 28 July, 2020, trial NCT04446429 (history). | risk of death, 80.0% lower, RR 0.20, p = 0.50, treatment 0 of 134 (0.0%), control 2 of 134 (1.5%), NNT 67, relative risk is not 0 because of continuity correction due to zero events (with reciprocal of the contrasting arm). |
| risk of mechanical ventilation, 97.1% lower, RR 0.03, p < 0.001, treatment 0 of 134 (0.0%), control 17 of 134 (12.7%), NNT 7.9, relative risk is not 0 because of continuity correction due to zero events (with reciprocal of the contrasting arm). | |
| risk of hospitalization, 91.0% lower, RR 0.09, p < 0.001, treatment 3 of 134 (2.2%), control 35 of 134 (26.1%), NNT 4.2. |
Effect extraction follows pre-specified rules as detailed above
and gives priority to more serious outcomes.
For pooled analyses, the first (most serious) outcome is used, which may
differ from the effect a paper focuses on.
Other outcomes are used in outcome specific analyses.
| Abbasi, 2/7/2022, Single Blind Randomized Controlled Trial, Iran, peer-reviewed, 11 authors, study period December 2020 - April 2021. | risk of death, 55.1% lower, RR 0.45, p = 0.10, treatment 5 of 51 (9.8%), control 19 of 87 (21.8%), NNT 8.3, day 5. |
| risk of mechanical ventilation, 33.7% lower, RR 0.66, p = 0.36, treatment 7 of 51 (13.7%), control 18 of 87 (20.7%), NNT 14, day 5. | |
| risk of ICU admission, 18.8% lower, RR 0.81, p = 0.67, treatment 10 of 51 (19.6%), control 21 of 87 (24.1%), NNT 22, day 5. | |
| risk of no recovery, 47.3% lower, RR 0.53, p < 0.001, treatment mean 1.64 (±0.81) n=51, control mean 3.11 (±2.45) n=87, relative clinical score, day 5. | |
| Barnette, 7/6/2022, Double Blind Randomized Controlled Trial, placebo-controlled, multiple countries, peer-reviewed, 12 authors, study period 18 May, 2021 - 31 January, 2022. | risk of death, 55.2% lower, RR 0.45, p = 0.002, treatment 19 of 94 (20.2%), control 23 of 51 (45.1%), NNT 4.0. |
| ventilation time, 49.5% lower, relative time 0.51, p = 0.001, treatment 98, control 52. | |
| ICU time, 43.5% lower, relative time 0.56, p = 0.001, treatment 98, control 52. | |
| hospitalization time, 26.0% lower, relative time 0.74, p = 0.03, treatment 98, control 52. | |
| Cadegiani (D), 12/25/2021, Double Blind Randomized Controlled Trial, Brazil, peer-reviewed, 15 authors, study period 1 February, 2021 - 15 April, 2021, trial NCT04728802 (history). | risk of death, 78.0% lower, RR 0.22, p < 0.001, treatment 45 of 423 (10.6%), control 171 of 355 (48.2%), NNT 2.7, adjusted per study, 28 days, Cox proportional hazards. |
| risk of death, 79.0% lower, RR 0.21, p < 0.001, treatment 34 of 423 (8.0%), control 138 of 355 (38.9%), NNT 3.2, adjusted per study, 14 days, Cox proportional hazards. | |
| recovery rate, RR 0.55, p < 0.001, treatment 423, control 355, adjusted per study, inverted to make RR<1 favor treatment, 28 days, Cox proportional hazards. | |
| recovery rate, RR 0.45, p < 0.001, treatment 423, control 355, adjusted per study, inverted to make RR<1 favor treatment, 14 days, Cox proportional hazards, primary outcome. | |
| hospitalization time, 33.3% lower, relative time 0.67, p < 0.001, treatment 423, control 355. | |
| Davarpanah, 1/21/2022, prospective, Iran, preprint, 9 authors, study period July 2021 - September 2021, average treatment delay 5.74 days, this trial uses multiple treatments in the treatment arm (combined with sitagliptin) - results of individual treatments may vary. | risk of hospitalization, 78.3% lower, RR 0.22, p < 0.001, treatment 6 of 103 (5.8%), control 23 of 103 (22.3%), NNT 6.1, odds ratio converted to relative risk. |
| recovery time, 64.4% lower, relative time 0.36, p < 0.001, treatment 103, control 103. | |
| Ersoy, 10/13/2021, retrospective, Turkey, peer-reviewed, 7 authors. | risk of death, 46.2% lower, RR 0.54, p = 0.002, treatment 14 of 30 (46.7%), control 26 of 30 (86.7%), NNT 2.5. |
| Ghandehari, 7/31/2021, Randomized Controlled Trial, USA, peer-reviewed, mean age 55.3, 14 authors, study period April 2020 - August 2020, trial NCT04365127 (history). | risk of death, 22.2% higher, RR 1.22, p = 1.00, treatment 1 of 18 (5.6%), control 1 of 22 (4.5%), day 15. |
| risk of mechanical ventilation, 84.5% lower, RR 0.15, p = 0.24, treatment 0 of 18 (0.0%), control 3 of 22 (13.6%), NNT 7.3, relative risk is not 0 because of continuity correction due to zero events (with reciprocal of the contrasting arm), peak value day 7 and 15. | |
| risk of progression, 75.6% lower, RR 0.24, p = 0.20, treatment 1 of 18 (5.6%), control 5 of 22 (22.7%), NNT 5.8, day 15. | |
| risk of progression, 38.9% lower, RR 0.61, p = 0.48, treatment 3 of 18 (16.7%), control 6 of 22 (27.3%), NNT 9.4, day 7. | |
| Gomaa, 3/1/2022, Double Blind Randomized Controlled Trial, placebo-controlled, Egypt, peer-reviewed, median age 60.0, 5 authors, study period June 2021 - November 2021, average treatment delay 6.0 days, this trial uses multiple treatments in the treatment arm (combined with boswellic acid) - results of individual treatments may vary, trial NCT04487964 (history). | risk of death, 90.9% lower, RR 0.09, p = 0.05, treatment 0 of 25 (0.0%), control 5 of 25 (20.0%), NNT 5.0, relative risk is not 0 because of continuity correction due to zero events (with reciprocal of the contrasting arm), day 14. |
| risk of mechanical ventilation, 90.9% lower, RR 0.09, p = 0.05, treatment 0 of 25 (0.0%), control 5 of 25 (20.0%), NNT 5.0, relative risk is not 0 because of continuity correction due to zero events (with reciprocal of the contrasting arm), day 14. | |
| recovery time, 44.0% lower, relative time 0.56, p < 0.001, treatment 25, control 25. | |
| risk of no recovery, 33.3% lower, RR 0.67, p < 0.001, treatment 25, control 25, relative clinical status, day 14. | |
| Gordon, 4/25/2022, Double Blind Randomized Controlled Trial, placebo-controlled, USA, peer-reviewed, 1 author. | risk of death, 82.0% lower, RR 0.18, p = 0.04, ITT. |
| ventilation time, 76.5% lower, relative time 0.24, p = 0.14. | |
| ICU time, 72.9% lower, relative time 0.27, p = 0.03. | |
| Goren, 9/25/2020, prospective, Brazil, peer-reviewed, 15 authors, trial NCT04368897 (history). | risk of ICU admission, 81.0% lower, RR 0.19, p = 0.08, treatment 1 of 12 (8.3%), control 17 of 36 (47.2%), NNT 2.6, adjusted per study, age-matched controls. |
| risk of ICU admission, 86.0% lower, RR 0.14, p = 0.04, treatment 1 of 12 (8.3%), control 38 of 65 (58.5%), NNT 2.0, adjusted per study, all controls. | |
| risk of death, 50.0% higher, RR 1.50, p = 1.00, treatment 1 of 12 (8.3%), control 2 of 36 (5.6%), age-matched controls. | |
| risk of death, 35.4% higher, RR 1.35, p = 0.58, treatment 1 of 12 (8.3%), control 4 of 65 (6.2%), all controls. | |
| Hsieh, 3/14/2022, prospective, Taiwan, peer-reviewed, 7 authors, study period 1 May, 2021 - 31 August, 2021, this trial uses multiple treatments in the treatment arm (combined with multi-herbal formula) - results of individual treatments may vary. | risk of death, 87.9% lower, RR 0.12, p = 0.13, treatment 0 of 117 (0.0%), control 4 of 143 (2.8%), NNT 36, relative risk is not 0 because of continuity correction due to zero events (with reciprocal of the contrasting arm). |
| risk of mechanical ventilation, 51.1% lower, RR 0.49, p = 0.46, treatment 2 of 117 (1.7%), control 5 of 143 (3.5%), NNT 56. | |
| risk of ICU admission, 30.2% lower, RR 0.70, p = 0.76, treatment 4 of 117 (3.4%), control 7 of 143 (4.9%), NNT 68. | |
| risk of no recovery, 87.9% lower, RR 0.12, p = 0.13, treatment 0 of 117 (0.0%), control 4 of 143 (2.8%), NNT 36, relative risk is not 0 because of continuity correction due to zero events (with reciprocal of the contrasting arm). | |
| relative increase in Ct score, 36.1% better, RR 0.64, p < 0.001, treatment mean 8.14 (±4.9) n=117, control mean 5.2 (±6.99) n=143. | |
| Kotfis, 2/5/2022, Randomized Controlled Trial, placebo-controlled, Poland, peer-reviewed, 10 authors, study period December 2020 - August 2021, trial NCT04912011 (history). | risk of death, 16.7% lower, RR 0.83, p = 1.00, treatment 4 of 24 (16.7%), control 5 of 25 (20.0%), NNT 30. |
| risk of ICU admission, 10.7% lower, RR 0.89, p = 1.00, treatment 6 of 24 (25.0%), control 7 of 25 (28.0%), NNT 33. | |
| relative TFS score, 30.4% better, RR 0.70, p = 0.51, treatment 24, control 25. | |
| Mareev, 12/3/2020, Randomized Controlled Trial, Russia, peer-reviewed, 20 authors, this trial uses multiple treatments in the treatment arm (combined with bromhexine) - results of individual treatments may vary, trial NCT04424134 (history). | relative SHOKS-COVID score, 11.3% better, RR 0.89, p = 0.47, treatment mean 2.12 (±1.39) n=33, control mean 2.39 (±1.59) n=33. |
| risk of PCR+ on day 10 or hospitalization >10 days, 38.8% lower, RR 0.61, p = 0.02, treatment 14 of 24 (58.3%), control 20 of 21 (95.2%), NNT 2.7, odds ratio converted to relative risk. | |
| hospitalization time, 8.2% lower, relative time 0.92, p = 0.35, treatment 33, control 33. | |
| risk of no viral clearance, 87.4% lower, RR 0.13, p = 0.08, treatment 0 of 17 (0.0%), control 3 of 13 (23.1%), NNT 4.3, relative risk is not 0 because of continuity correction due to zero events (with reciprocal of the contrasting arm), day 10. | |
| Nicastri, 6/30/2022, Double Blind Randomized Controlled Trial, placebo-controlled, Italy, peer-reviewed, 17 authors, study period October 2020 - June 2021, trial NCT05172050 (history). | risk of oxygen therapy, 51.7% lower, OR 0.48, p = 0.43, treatment 20, control 19, inverted to make OR<1 favor treatment, oxygen supplementation or mechanical ventilation, day 28, 120mg, RR approximated with OR. |
| risk of oxygen therapy, 6.5% lower, OR 0.93, p = 0.94, treatment 22, control 19, inverted to make OR<1 favor treatment, oxygen supplementation or mechanical ventilation, day 28, 60mg, RR approximated with OR. | |
| risk of oxygen therapy, 4.2% higher, OR 1.04, p = 0.96, treatment 20, control 19, inverted to make OR<1 favor treatment, oxygen supplementation or mechanical ventilation, day 14, 120mg, primary outcome, RR approximated with OR. | |
| risk of oxygen therapy, 39.8% lower, OR 0.60, p = 0.56, treatment 22, control 19, inverted to make OR<1 favor treatment, oxygen supplementation or mechanical ventilation, day 14, 60mg, primary outcome, RR approximated with OR. | |
| risk of no viral clearance, 68.8% lower, OR 0.31, p = 0.22, treatment 20, control 19, inverted to make OR<1 favor treatment, mid-recovery, day 14, 120mg, RR approximated with OR. | |
| risk of no viral clearance, 9.9% lower, OR 0.90, p = 0.91, treatment 22, control 19, inverted to make OR<1 favor treatment, mid-recovery, day 14, 60mg, RR approximated with OR. | |
| Nickols, 4/19/2022, Double Blind Randomized Controlled Trial, placebo-controlled, USA, peer-reviewed, 34 authors, study period 22 July, 2020 - 8 April, 2021, trial NCT04397718 (history) (HITCH). | risk of death, 18.3% lower, RR 0.82, p = 0.66, treatment 11 of 62 (17.7%), control 7 of 34 (20.6%), NNT 35, adjusted per study, odds ratio converted to relative risk, multivariable. |
| risk of mechanical ventilation, 18.8% higher, RR 1.19, p = 0.70, treatment 13 of 62 (21.0%), control 6 of 34 (17.6%). | |
| risk of ongoing hospitalization, mortality, or mechanical ventilation, 16.7% higher, RR 1.17, p = 0.70, treatment 15 of 62 (24.2%), control 7 of 34 (20.6%), adjusted per study, odds ratio converted to relative risk, multivariable, primary outcome. | |
| hospitalization time, 20.0% higher, relative time 1.20, p = 0.94, treatment 62, control 34. | |
| Vicenzi, 9/11/2020, retrospective, Italy, peer-reviewed, 10 authors, this trial compares with another treatment - results may be better when compared to placebo. | risk of death, 93.0% lower, HR 0.07, p < 0.001, treatment 30, control 39, adjusted per study, model 2, multivariable. |
| risk of death/intubation, 81.0% lower, HR 0.19, p = 0.002, treatment 30, control 39, adjusted per study, model 2, multivariable. | |
| Wadhwa, 7/2/2022, Randomized Controlled Trial, placebo-controlled, India, preprint, 18 authors, study period 1 February, 2021 - 30 April, 2021, trial CTRI/2021/03/031721. | risk of progression, 72.4% lower, RR 0.28, p = 0.03, treatment 4 of 74 (5.4%), control 9 of 46 (19.6%), NNT 7.1, progression to WHO >4. |
| risk of no hospital discharge, 49.5% lower, RR 0.51, p = 0.048, treatment 13 of 74 (17.6%), control 16 of 46 (34.8%), NNT 5.8. | |
| recovery time, 18.2% lower, relative time 0.82, p = 0.06, treatment 74, control 46. | |
| Welén, 12/14/2021, Randomized Controlled Trial, Sweden, peer-reviewed, 27 authors, study period 15 July, 2020 - 29 May, 2021, average treatment delay 9.5 days, trial NCT04475601 (history). | risk of death, 79.6% lower, RR 0.20, p = 0.26, treatment 0 of 29 (0.0%), control 1 of 10 (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 mechanical ventilation, 31.0% lower, RR 0.69, p = 1.00, treatment 2 of 29 (6.9%), control 1 of 10 (10.0%), NNT 32. | |
| risk of no hospital discharge, 132.6% higher, RR 2.33, p = 0.03, treatment 29, control 10, inverted to make RR<1 favor treatment, primary outcome. | |
| hospitalization time, 50.0% higher, relative time 1.50, p = 0.01, treatment 29, control 10. | |
| Zarehoseinzade, 4/30/2021, Randomized Controlled Trial, Iran, peer-reviewed, 5 authors. | risk of death, 75.0% lower, RR 0.25, p = 0.36, treatment 1 of 40 (2.5%), control 4 of 40 (10.0%), NNT 13. |
| risk of ICU admission, no change, RR 1.00, p = 1.00, treatment 1 of 40 (2.5%), control 1 of 40 (2.5%). |
Effect extraction follows pre-specified rules as detailed above
and gives priority to more serious outcomes.
For pooled analyses, the first (most serious) outcome is used, which may
differ from the effect a paper focuses on.
Other outcomes are used in outcome specific analyses.
| Bennani, 8/17/2020, retrospective, Italy, peer-reviewed, 2 authors. | risk of death, 94.9% lower, RR 0.05, p = 1.00, treatment 0 of 4 (0.0%), control 18 of 114 (15.8%), NNT 6.3, relative risk is not 0 because of continuity correction due to zero events (with reciprocal of the contrasting arm). |
| risk of ICU admission, 119.2% higher, RR 2.19, p = 0.40, treatment 1 of 4 (25.0%), control 13 of 114 (11.4%). | |
| risk of hospitalization, 25.0% lower, RR 0.75, p = 0.60, treatment 2 of 4 (50.0%), control 76 of 114 (66.7%), NNT 6.0. | |
| risk of severe case, 8.1% lower, RR 0.92, p = 1.00, treatment 1 of 4 (25.0%), control 31 of 114 (27.2%), NNT 46. | |
| Cousins, 3/2/2023, retrospective, propensity score matching, USA, peer-reviewed, 2 authors. | risk of death, 18.4% lower, RR 0.82, p = 0.004, treatment 390 of 12,504 (3.1%), control 479 of 12,504 (3.8%), NNT 140, odds ratio converted to relative risk, 90 day exposure window, propensity score matching. |
| risk of death, 11.6% lower, RR 0.88, p = 0.04, treatment 521 of 16,324 (3.2%), control 592 of 16,324 (3.6%), NNT 230, odds ratio converted to relative risk, 180 day exposure window, propensity score matching, primary outcome. | |
| risk of death, 14.5% lower, RR 0.85, p = 0.003, treatment 671 of 20,690 (3.2%), control 783 of 20,690 (3.8%), NNT 185, odds ratio converted to relative risk, 360 day exposure window, propensity score matching. | |
| risk of mechanical ventilation, 16.7% lower, RR 0.83, p < 0.001, treatment 936 of 12,504 (7.5%), control 1,118 of 12,504 (8.9%), NNT 69, odds ratio converted to relative risk, 90 day exposure window, propensity score matching. | |
| risk of mechanical ventilation, 16.7% lower, RR 0.83, p < 0.001, treatment 1,212 of 16,324 (7.4%), control 1,459 of 16,324 (8.9%), NNT 66, odds ratio converted to relative risk, 180 day exposure window, propensity score matching, primary outcome. | |
| risk of mechanical ventilation, 10.2% lower, RR 0.90, p < 0.001, treatment 1,524 of 20,690 (7.4%), control 1,701 of 20,690 (8.2%), NNT 117, odds ratio converted to relative risk, 360 day exposure window, propensity score matching. | |
| Cousins (B), 7/6/2022, retrospective, propensity score matching, USA, peer-reviewed, 10 authors. | risk of mechanical ventilation, 81.0% lower, OR 0.19, p = 0.006, treatment 731, control 731, propensity score matching, RR approximated with OR. |
| risk of ICU admission, 66.0% lower, OR 0.34, p = 0.002, treatment 731, control 731, propensity score matching, RR approximated with OR. | |
| Davidsson, 1/19/2023, retrospective, Sweden, peer-reviewed, 10 authors. | risk of IgG positive, 1.8% lower, RR 0.98, p = 0.95, treatment 30 of 224 (13.4%), control 45 of 431 (10.4%), adjusted per study, odds ratio converted to relative risk, multivariable. |
| Duarte, 11/25/2021, retrospective, Brazil, peer-reviewed, 4 authors. | risk of death, 11.2% lower, RR 0.89, p = 0.37, treatment 100 of 156 (64.1%), control 32 of 43 (74.4%), NNT 9.7, adjusted per study, odds ratio converted to relative risk. |
| Gedeborg, 12/23/2021, retrospective, Sweden, peer-reviewed, 6 authors. | risk of death, 25.0% higher, OR 1.25, p = 0.11, treatment 271 of 474 (57.2%) cases, 5,181 of 23,700 (21.9%) controls, case control OR. |
| Holt, 5/7/2020, retrospective, Denmark, peer-reviewed, median age 70.0, 4 authors, study period 1 March, 2020 - 1 April, 2020, excluded in exclusion analyses: unadjusted results with no group details. | risk of death/ICU, 129.5% higher, RR 2.29, p < 0.001, treatment 16 of 31 (51.6%), control 148 of 658 (22.5%). |
| Ianhez, 9/3/2020, retrospective, Brazil, peer-reviewed, 4 authors. | risk of ICU admission, 79.7% lower, RR 0.20, p = 0.26, treatment 1 of 17 (5.9%), control 28 of 357 (7.8%), adjusted per study, odds ratio converted to relative risk, multivariable. |
| risk of hospitalization, 65.7% lower, RR 0.34, p = 0.32, treatment 2 of 17 (11.8%), control 64 of 357 (17.9%), adjusted per study, odds ratio converted to relative risk, multivariable. | |
| risk of case, 1.4% higher, RR 1.01, p = 0.90, treatment 17 of 571 (3.0%), control 357 of 12,161 (2.9%), unadjusted, total count not provided, estimated from percentage. | |
| Israel, 7/27/2021, retrospective, Israel, peer-reviewed, 10 authors. | risk of hospitalization, 37.7% lower, OR 0.62, p = 0.01, treatment 30 of 6,530 (0.5%) cases, 240 of 32,650 (0.7%) controls, NNT 18, case control OR. |
| Jeon, 2/23/2021, retrospective, South Korea, peer-reviewed, 3 authors. | risk of case, 77.0% lower, OR 0.23, p = 0.005, treatment 6 of 49 (12.2%) cases, 89 of 245 (36.3%) controls, NNT 6.5, case control OR, model 2, within 3 months. |
| Jiménez-Alcaide, 9/13/2021, retrospective, Spain, peer-reviewed, 9 authors. | risk of death, 33.0% lower, RR 0.67, p = 0.41, treatment 3 of 11 (27.3%), control 17 of 50 (34.0%), adjusted per study, multivariable. |
| risk of progression, 8.0% higher, RR 1.08, p = 0.77, treatment 11, control 50, adjusted per study, multivariable. | |
| risk of case, 68.2% higher, RR 1.68, p = 0.15, treatment 11 of 156 (7.1%), control 50 of 1,193 (4.2%), excluded in exclusion analyses: excessive unadjusted differences between groups. | |
| Kazan, 11/1/2021, retrospective, Turkey, peer-reviewed, 10 authors, study period August 2020 - June 2021, excluded in exclusion analyses: excessive unadjusted differences between groups. | risk of hospitalization, 229.0% higher, RR 3.29, p = 0.20, treatment 4 of 138 (2.9%), control 2 of 227 (0.9%). |
| risk of case, 28.7% lower, RR 0.71, p = 0.32, treatment 13 of 138 (9.4%), control 30 of 227 (13.2%), NNT 26. | |
| Klein, 2/1/2021, retrospective, USA, peer-reviewed, 7 authors, study period 12 March, 2020 - 10 June, 2020. | risk of death, 123.9% higher, RR 2.24, p = 0.12, treatment 6 of 304 (2.0%), control 13 of 1,475 (0.9%). |
| risk of case, 6.6% lower, RR 0.93, p = 0.80, treatment 17 of 304 (5.6%), control 85 of 1,475 (5.8%), NNT 586, adjusted per study, odds ratio converted to relative risk, multivariable. | |
| Koskinen, 6/29/2020, retrospective, Finland, peer-reviewed, 7 authors. | risk of death, 45.8% lower, RR 0.54, p = 1.00, treatment 1 of 134 (0.7%), control 3 of 218 (1.4%), NNT 159. |
| risk of death/ICU, 45.8% lower, RR 0.54, p = 1.00, treatment 1 of 134 (0.7%), control 3 of 218 (1.4%), NNT 159. | |
| risk of case, 11.3% lower, RR 0.89, p = 1.00, treatment 6 of 134 (4.5%), control 11 of 218 (5.0%), NNT 176. | |
| Kwon, 1/29/2021, retrospective, USA, peer-reviewed, 7 authors. | risk of death, 21.1% lower, RR 0.79, p = 1.00, treatment 1 of 799 (0.1%), control 7 of 4,412 (0.2%), NNT 2985. |
| risk of case, 17.6% higher, RR 1.18, p = 0.54, treatment 18 of 799 (2.3%), control 79 of 4,412 (1.8%), adjusted per study, odds ratio converted to relative risk, multivariable. | |
| Lazzeri, 9/21/2020, retrospective, Italy, preprint, 11 authors. | risk of death/ICU, 23.0% higher, OR 1.23, p = 0.33, multivariable, RR approximated with OR. |
| Lee (B), 3/7/2022, retrospective, USA, peer-reviewed, 14 authors, study period 15 February, 2020 - 15 July, 2020. | risk of severe case, 21.4% lower, RR 0.79, p = 0.03, treatment 76 of 295 (25.8%), control 727 of 2,427 (30.0%), NNT 24, adjusted per study, odds ratio converted to relative risk, propensity score weighting, multivariable. |
| risk of case, 11.3% lower, RR 0.89, p < 0.001, treatment 295 of 3,057 (9.6%), control 2,427 of 36,096 (6.7%), adjusted per study, odds ratio converted to relative risk, propensity score weighting, multivariable. | |
| Lyon, 1/31/2022, retrospective, USA, peer-reviewed, 8 authors, study period 8 March, 2020 - 15 February, 2021. | risk of death, 16.9% lower, RR 0.83, p = 0.61, treatment 15 of 944 (1.6%), control 19 of 994 (1.9%), NNT 310. |
| risk of case, 7.2% lower, RR 0.93, p = 0.04, treatment 399 of 944 (42.3%), control 446 of 994 (44.9%), NNT 38, adjusted per study, odds ratio converted to relative risk, multivariable. | |
| MacFadden, 3/29/2022, retrospective, Canada, peer-reviewed, 9 authors, study period 15 January, 2020 - 31 December, 2020. | risk of case, 7.0% lower, OR 0.93, p = 0.008, RR approximated with OR. |
| Montopoli, 5/6/2020, retrospective, Italy, peer-reviewed, 12 authors. | risk of death, 95.4% lower, RR 0.05, p = 0.15, treatment 0 of 5,273 (0.0%), control 18 of 37,161 (0.0%), NNT 2064, relative risk is not 0 because of continuity correction due to zero events (with reciprocal of the contrasting arm). |
| risk of severe case, 74.5% lower, RR 0.25, p = 0.01, treatment 1 of 5,273 (0.0%), control 31 of 37,161 (0.1%), NNT 1551, inverted to make RR<1 favor treatment, odds ratio converted to relative risk. | |
| risk of case, 75.3% lower, RR 0.25, p = 0.004, treatment 4 of 5,273 (0.1%), control 114 of 37,161 (0.3%), NNT 433, inverted to make RR<1 favor treatment, odds ratio converted to relative risk. | |
| Patel, 7/9/2020, retrospective, USA, peer-reviewed, 7 authors, study period 1 March, 2020 - 4 June, 2020. | risk of death, 55.2% lower, RR 0.45, p = 0.22, treatment 4 of 22 (18.2%), control 10 of 36 (27.8%), adjusted per study, odds ratio converted to relative risk, multivariable. |
| risk of mechanical ventilation, 69.0% lower, OR 0.31, p = 0.19, treatment 22, control 36, adjusted per study, multivariable, RR approximated with OR. | |
| risk of hospitalization, 77.0% lower, OR 0.23, p = 0.02, treatment 22, control 36, adjusted per study, multivariable, RR approximated with OR. | |
| Schmidt, 11/12/2021, retrospective, USA, peer-reviewed, 42 authors, study period 17 March, 2020 - 11 February, 2021. | risk of death, 20.4% lower, RR 0.80, p = 0.41, treatment 25 of 169 (14.8%), control 44 of 308 (14.3%), adjusted per study, odds ratio converted to relative risk, propensity score matching, multivariable. |
| risk of severe case, 2.0% lower, OR 0.98, p = 0.94, treatment 169, control 308, adjusted per study, propensity score matching, multivariable, RR approximated with OR. | |
| Shah, 5/12/2022, retrospective, USA, peer-reviewed, median age 71.0, 22 authors, study period 1 March, 2020 - 31 May, 2020. | risk of death, 16.0% higher, HR 1.16, p = 0.59, treatment 148, control 317. |
| risk of mechanical ventilation, 19.0% lower, HR 0.81, p = 0.73, treatment 148, control 317. | |
| risk of severe case, 3.0% higher, HR 1.03, p = 0.91, treatment 148, control 317. | |
| risk of hospitalization, 4.0% lower, HR 0.96, p = 0.90, treatment 148, control 317. | |
| Shaw, 7/1/2021, retrospective, USA, peer-reviewed, 10 authors, study period 1 March, 2020 - 15 May, 2020. | risk of case, 6.0% lower, OR 0.94, p = 0.006, treatment 47, control 97, adjusted per study, propensity score matching, multivariable, RR approximated with OR. |
| Welén (B), 12/14/2021, retrospective, Sweden, peer-reviewed, 27 authors, trial NCT04475601 (history). | risk of death, 2.0% lower, HR 0.98, p = 0.94, treatment 21 of 358 (5.9%), control 167 of 4,980 (3.4%), adjusted per study, antiandrogen treatment. |
| risk of death, 11.0% lower, HR 0.89, p = 0.66, treatment 20 of 334 (6.0%), control 167 of 4,980 (3.4%), adjusted per study, ADT. | |
| risk of death, 151.0% higher, HR 2.51, p < 0.001, treatment 24 of 152 (15.8%), control 167 of 4,980 (3.4%), adjusted per study, ADT and abiraterone acetate or enzalutamide. | |
| risk of ICU admission, 28.0% higher, HR 1.28, p = 0.28, treatment 24 of 358 (6.7%), control 216 of 4,980 (4.3%), adjusted per study, antiandrogen treatment. | |
| risk of ICU admission, 13.0% lower, HR 0.87, p = 0.62, treatment 16 of 334 (4.8%), control 216 of 4,980 (4.3%), adjusted per study, ADT. | |
| risk of ICU admission, 21.0% lower, HR 0.79, p = 0.60, treatment 6 of 152 (3.9%), control 216 of 4,980 (4.3%), adjusted per study, ADT and abiraterone acetate or enzalutamide. | |
| risk of hospitalization, 23.0% higher, HR 1.23, p = 0.09, treatment 126 of 358 (35.2%), control 1,108 of 4,980 (22.2%), adjusted per study, antiandrogen treatment. | |
| risk of hospitalization, 24.0% higher, HR 1.24, p = 0.09, treatment 126 of 334 (37.7%), control 1,108 of 4,980 (22.2%), adjusted per study, ADT. | |
| risk of hospitalization, 40.0% higher, HR 1.40, p = 0.06, treatment 66 of 152 (43.4%), control 1,108 of 4,980 (22.2%), adjusted per study, ADT and abiraterone acetate or enzalutamide. |
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