Response-adaptive randomization for clinical trials with adjustment for covariate imbalance.

Statistics in Medicine
Jing Ning, Xuelin Huang

Abstract

In clinical trials with a small sample size, the characteristics (covariates) of patients assigned to different treatment arms may not be well balanced. This may lead to an inflated type I error rate. This problem can be more severe in trials that use response-adaptive randomization rather than equal randomization because the former may result in smaller sample sizes for some treatment arms. We have developed a patient allocation scheme for trials with binary outcomes to adjust the covariate imbalance during response-adaptive randomization. We used simulation studies to evaluate the performance of the proposed design. The proposed design keeps the important advantage of a standard response-adaptive design, that is to assign more patients to the better treatment arms, and thus it is ethically appealing. On the other hand, the proposed design improves over the standard response-adaptive design by controlling covariate imbalance between treatment arms, maintaining the nominal type I error rate, and offering greater power.

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Citations

Jun 24, 2015·Pharmaceutical Statistics·Tomoyoshi HatayamaKentaro Sakamaki
Mar 7, 2017·Pharmaceutical Statistics·Benjamin R Saville, Scott M Berry
Jan 30, 2020·The British Journal of Psychiatry : the Journal of Mental Science·Ashleigh CharlesRichard Mpango
Sep 4, 2018·Alzheimer's & Dementia : Translational Research & Clinical Interventions·Guogen ShanJeffrey L Cummings
Dec 12, 2018·Biometrical Journal. Biometrische Zeitschrift·Selvakkadunko SelvaratnamAlwell Oyet
May 25, 2021·Journal of Applied Statistics·Fang XiaXuelin Huang
Aug 3, 2021·Current Opinion in Critical Care·Ary Serpa NetoCarol L Hodgson

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