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