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All Studies   Meta Analysis    Recent:   

Quantifying treatment effects of hydroxychloroquine and azithromycin for COVID-19: a secondary analysis of an open label non-randomized clinical trial (Gautret et al., 2020)

Apr 2020  
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HCQ for COVID-19
1st treatment shown to reduce risk in March 2020
 
*, now with p < 0.00000000001 from 411 studies, recognized in 46 countries.
No treatment is 100% effective. Protocols combine treatments. * >10% efficacy, ≥3 studies.
4,400+ studies for 79 treatments. c19hcq.org
Secondary analysis of Gautret et al. showing "modest to no impact of HCQ treatment, with more significant effects from [HCQ+AZ]".
8 meta analyses show significant improvements with hydroxychloroquine for mortality1-4, hospitalization1, recovery5, combined death/hospitalization/cases6, and cases7,8.
Currently there are 39 HCQ for COVID-19 early treatment studies, showing 76% lower mortality [61‑85%], 67% lower ventilation [-710‑99%], 31% lower ICU admission [1‑53%], and 41% lower hospitalization [28‑51%].
Lover et al., 10 Apr 2020, preprint, 1 author.
This PaperHCQAll
Quantifying treatment effects of hydroxychloroquine and azithromycin for COVID-19: a secondary analysis of an open label non-randomized clinical trial
Andrew A Lover
doi:10.1101/2020.03.22.20040949
The author stands by all analytical and statistical aspects of this preprint. However, subsequent to this analysis, further details of the original study have been released-with major uncertainties in study design, reporting, choice of endpoints, and most importantly, data integrity [1, 2] . Therefore, all results from the original study should be viewed with considerable skepticism.
References
Bik, Thoughts on the Gautret et al. paper about Hydroxychloroquine and Azithromycin treatment of COVID-19 infections
Coveney, Firthlogit: Stata module to calculate bias reduction in logistic regression
Gautret, Lagier, Parola, Van Thuan, Hoang et al., Hydroxychloroquine and Azithromycin as a treatment of COVID-19: preliminary results of an open-label non-randomized clinical trial, medRxiv
Ian R White, Horton, Carpenter, Pocock, Strategy for intention to treat analysis in randomised trials with missing outcome data, Bmj
Lorenc, Oliver, Adverse effects of public health interventions: a conceptual framework, J Epidemiol Community Health
Mcnutt, Wu, Xue, Hafner, Estimating the relative risk in cohort studies and clinical trials of common outcomes, American journal of epidemiology
Michael A Johansson, Reich, Meyers, Lipsitch, Preprints: An underutilized mechanism to accelerate outbreak science, PLoS medicine
Nakagawa, Innes, Cuthill, Effect size, confidence interval and statistical significance: a practical guide for biologists, Biological reviews
Pubpeer, Pubpeer: Hydroxychloroquine and Azithromycin as a treatment of COVID-19: preliminary results of an open-label non-randomized clinical trial
Rivers, Chretien, Riley, Pavlin, Woodward et al., Using "outbreak science" to strengthen the use of models during epidemics, Nature Communications
Royston, Parmar, Flexible parametric proportional-hazards and proportional-odds models for censored survival data, with application to prognostic modelling and estimation of treatment effects, Statistics in medicine
Sandeep, Gupta, Intention-to-treat concept: a review, Perspectives in clinical research
Tjur, Coefficients of determination in logistic regression models-a new proposal: The coefficient of discrimination, The American Statistician
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An open-label clinical trial has just concluded, suggesting improved ' 'resolution of viremia with use of two existing therapies: hydroxychloroquine (HCQ) as ' 'monotherapy, and in combination with azithromycin (HCQ-AZ). [3, 4].</jats:p><jats:p>The ' 'results of this important trial have major implications for global policy in the rapid ' 'scale-up and response to this pandemic. The authors present results with p-values for ' 'differences in proportions between the study arms, but their analysis is not able to provide ' 'effect size estimates.</jats:p><jats:p>To address this gap, more modern analytical methods ' 'including survival models, have been applied to these data, and show modest to no impact of ' 'HCQ treatment, with more significant effects from the HCQ-AZ combination, potentially ' 'suggesting a role for co-infections in COVID-19 pathogenesis.</jats:p><jats:p>The trial of ' 'Gautret and colleagues, with consideration of the effect sizes, and p-values from multiple ' 'models, does not provide sufficient evidence to support wide-scale rollout of HCQ monotherapy ' 'for the treatment of COVID-19; larger randomized studies should be considered. 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Late treatment
is less effective
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