Statistical power and validity of Ebola vaccine trials in Sierra Leone: a simulation study of trial design and analysis

• Authors: Steven E. Bellan, University of Texas at Austin; Juliet R. C. Pulliam, University of Florida; Carl A. B. Pearson, University of Florida; David Champredon, McMaster University; Spencer J. Fox, University of Texas at Austin; Laura Skrip, Yale University; Alison P. Galvani, Yale University; Manoj Gambhir, Monash University; Benjamin Lopman, Emory University; Travis C. Porco, University of California, San Francisco; Lauren Ancel Meyers, University of Texas at Austin; Jonathan Dushoff, McMaster University
• Journal Title: Lancet Infectious Diseases
• Volume: Volume 15, Number 6
• Publisher: Elsevier: Lancet | 2015-06-01, Pages 703-710
• Type of Work: Article | Post-print: After Peer Review
• Publisher DOI: http://doi.org/10.1016/S1473-3099(15)70139-8
• Subjects: Biology, Biostatistics; Health Sciences, Epidemiology
• Keywords: Science & Technology; Life Sciences & Biomedicine; Infectious Diseases; stepped wedge trial; cluster-randomization; cross-over trial; covariance-variance misspecification; emerging infectious disease; study design simulation; mathematical modeling; permutation test; randomization test; equipoise

Abstract

BACKGROUND: Safe and effective vaccines could help to end the ongoing Ebola virus disease epidemic in parts of west Africa, and mitigate future outbreaks of the virus. We assess the statistical validity and power of randomised controlled trial (RCT) and stepped-wedge cluster trial (SWCT) designs in Sierra Leone, where the incidence of Ebola virus disease is spatiotemporally heterogeneous, and is decreasing rapidly. METHODS: We projected district-level Ebola virus disease incidence for the next 6 months, using a stochastic model fitted to data from Sierra Leone. We then simulated RCT and SWCT designs in trial populations comprising geographically distinct clusters at high risk, taking into account realistic logistical constraints, and both individual-level and cluster-level variations in risk. We assessed false-positive rates and power for parametric and non-parametric analyses of simulated trial data, across a range of vaccine efficacies and trial start dates. FINDINGS: For an SWCT, regional variation in Ebola virus disease incidence trends produced increased false-positive rates (up to 0·15 at α=0·05) under standard statistical models, but not when analysed by a permutation test, whereas analyses of RCTs remained statistically valid under all models. With the assumption of a 6-month trial starting on Feb 18, 2015, we estimate the power to detect a 90% effective vaccine to be between 49% and 89% for an RCT, and between 6% and 26% for an SWCT, depending on the Ebola virus disease incidence within the trial population. We estimate that a 1-month delay in trial initiation will reduce the power of the RCT by 20% and that of the SWCT by 49%. INTERPRETATION: Spatiotemporal variation in infection risk undermines the statistical power of the SWCT. This variation also undercuts the SWCT's expected ethical advantages over the RCT, because an RCT, but not an SWCT, can prioritise vaccination of high-risk clusters.