Estimation of sample size in randomized controlled trials in multiple sclerosis studying annualized relapse rates: A systematic review

Author:

Poncet-Megemont Louis1,Pereira Bruno1,Rollot Fabien2,Sormani Maria Pia3ORCID,Clavelou Pierre1,Moisset Xavier1ORCID

Affiliation:

1. Université Clermont Auvergne, CHU de Clermont-Ferrand, Inserm, Neuro-Dol, Clermont-Ferrand, France

2. Université de Lyon, Université Claude Bernard Lyon 1, Lyon, France/Hospices Civils de Lyon, Hôpital Neurologique, Service de Neurologie, Sclérose en Plaques, Pathologies de la Myéline et Neuro-inflammation, Bron, France/Observatoire Français de la Sclérose en Plaques, Centre de Recherche en Neurosciences de Lyon, INSERM 1028 et CNRS UMR 5292, Lyon, France/EUGENE DEVIC EDMUS Foundation Against Multiple Sclerosis, state-approved foundation, Bron, France

3. Department of Health Sciences (DISSAL), University of Genoa and Ospedale Policlinico San Martino IRCCS, Genova, Italy

Abstract

Background: In multiple sclerosis (MS) studies, the most appropriate model for the distribution of the number of relapses was shown to be the negative binomial (NB) distribution. Objective: To determine whether the sample-size estimation (SSE) and the analysis of annualized relapse rates (ARRs) in randomized controlled trials (RCTs) were aligned and compare the SSE between normal and NB distributions. Methods: Systematic review of phase 3 and 4 RCTs for which the primary endpoint was ARR in relapsing remitting MS published since 2008 in pre-selected major medical journals. A PubMed search was performed on 30 November 2020. We checked whether the SSE and ARR analyses were congruent. We also performed standardized (fixed α/β, number of arms and overdispersion) SSEs using data collected from the studies. Results: Twenty articles (22 studies) were selected. NB distribution (or quasi-Poisson) was used for SSE in only 7/22 studies, whereas 21/22 used it for ARR analyses. SSE relying on NB regression necessitated a smaller sample size in 21/22 of our calculations. Conclusion: SSE was rarely performed using the most appropriate model. However, the use of an NB model is recommended to optimize the number of included patients and to be congruent with the final analysis.

Publisher

SAGE Publications

Subject

Clinical Neurology,Neurology

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