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Validity and power of minimization algorithm in longitudinal analysis of clinical trials.

ABSTRACT: We studied the validity of longitudinal statistical inferences of clinical trials using minimization, a dynamic randomization algorithm designed to minimize treatment imbalance for prognostic factors. Repeated measures analysis of covariance and the random intercept and slope models, were used to simulate longitudinal clinical trials randomized by minimization or simple randomization. The simulations represented a wide range of analyses in real-world trials, including missing data caused by dropouts, unequal allocation of treatment arms, and efficacy analyses on either the original outcome or its change from baseline. We also analyzed the database from the Dominantly Inherited Alzheimer Network (DIAN), and used the estimated parameters to simulate the ongoing DIAN trial. Our analyses demonstrated minimization had conservative type I errors when the prognostic factor used in the minimization algorithm had a relatively strong correlation with the outcome and was not adjusted for in analyses. In contrast, adjusted tests for the prognostic factor as a covariate resulted in type I errors close to the nominal significance level. In many simulation scenarios, the adjusted tests using minimization had slightly greater statistical power than those using simple randomization, whereas in the other scenarios, the power of adjusted tests using these two randomization methods are almost indistinguishable.

SUBMITTER: Weng H

PROVIDER: S-EPMC5730087 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

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Validity and power of minimization algorithm in longitudinal analysis of clinical trials.

Weng Hua H Bateman Randall R Morris John C JC Xiong Chengjie C

Biostatistics & epidemiology 20170613 1

We studied the validity of longitudinal statistical inferences of clinical trials using minimization, a dynamic randomization algorithm designed to minimize treatment imbalance for prognostic factors. Repeated measures analysis of covariance and the random intercept and slope models, were used to simulate longitudinal clinical trials randomized by minimization or simple randomization. The simulations represented a wide range of analyses in real-world trials, including missing data caused by drop ...[more]

PMID: 29250611

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Project description: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.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.For an SWCT, regional variation in Ebola virus disease incidence trends produced increased false-positive rates (up to 0·15 at ?=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%.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.US National Institutes of Health, US National Science Foundation, and Canadian Institutes of Health Research.

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Validity and power of minimization algorithm in longitudinal analysis of clinical trials.

Publications

Validity and power of minimization algorithm in longitudinal analysis of clinical trials.

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