Bayesian modeling and prediction of accrual in multi-regional clinical trials. (April 2017)

• Record Type: Journal Article
• Authors: Deng, Yi; Zhang, Xiaoxi; Long, Qi
• Is Part Of: Statistical methods in medical research. Volume 26:Number 2(2017)
• Page Start: 752
• Page End: 765
• Publication Date: 2017-04
• Subjects: Bayesian modeling -- clinical trials -- multi-regional trials -- nonhomogeneous Poisson process -- patient accrual; Medicine -- Research -- Statistical methods -- Periodicals; Research -- Periodicals; Review Literature -- Periodicals; Statistics -- methods -- Periodicals; Médecine -- Recherche -- Méthodes statistiques -- Périodiques; 610.727
• DOI: 10.1177/0962280214557581
• Languages: English
• ISSNs: 0962-2802

Abstract

In multi-regional trials, the underlying overall and region-specific accrual rates often do not hold constant over time and different regions could have different start-up times, which combined with initial jump in accrual within each region often leads to a discontinuous overall accrual rate, and these issues associated with multi-regional trials have not been adequately investigated. In this paper, we clarify the implication of the multi-regional nature on modeling and prediction of accrual in clinical trials and investigate a Bayesian approach for accrual modeling and prediction, which models region-specific accrual using a nonhomogeneous Poisson process and allows the underlying Poisson rate in each region to vary over time. The proposed approach can accommodate staggered start-up times and different initial accrual rates across regions/centers. Our numerical studies show that the proposed method improves accuracy and precision of accrual prediction compared to existing methods including the nonhomogeneous Poisson process model that does not model region-specific accrual.