论文标题
在患者辍学的临床试验中进行建模和预测患者招募
Modelling and forecasting patient recruitment in clinical trials with patients' dropout
论文作者
论文摘要
本文重点介绍了对患者辍学的临床试验中患者招募的统计建模和预测。招聘模型基于Anisimov和Fedorov（2007）引入的泊松 - 伽马模型，该模型根据泊松过程，患者到达不同的中心，其速率被视为伽马分布的随机变量。每个患者可以在某个筛查期间放弃研究。管理辍学过程至关重要，但与辍学有关的数据很少正确地收集。在本文中，提出了一些辍学模型。估计参数并预测招募患者数量和招募时间的技术。仿真结果证实了该技术的适用性，因此，在临床试验中预测招募阶段的辍学阶段的必要性。
This paper focuses on statistical modelling and prediction of patient recruitment in clinical trials accounting for patients dropout. The recruitment model is based on a Poisson-gamma model introduced by Anisimov and Fedorov (2007), where the patients arrive at different centres according to Poisson processes with rates viewed as gamma-distributed random variables. Each patient can drop the study during some screening period. Managing the dropout process is of a major importance but data related to dropout are rarely correctly collected. In this paper, a few models of dropout are proposed. The technique for estimating parameters and predicting the number of recruited patients over time and the recruitment time is developed. Simulation results confirm the applicability of the technique and thus, the necessity to account for patients dropout at the stage of forecasting recruitment in clinical trials.
