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基于开放式队列设计的阶梯型楔形群随机试验中,估计再发事件时间的干预效果的统计模型比较。

Comparison of statistical models for estimating intervention effects based on time-to-recurrent-event in stepped wedge cluster randomized trial using open cohort design.

机构信息

Division of Biostatistics, Tohoku University Graduate School of Medicine, Sendai, Japan.

Departments of Biostatistics, JORTC Data Center, Tokyo, Japan.

出版信息

BMC Med Res Methodol. 2022 Apr 26;22(1):123. doi: 10.1186/s12874-022-01552-6.

Abstract

BACKGROUND

There are currently no methodological studies on the performance of the statistical models for estimating intervention effects based on the time-to-recurrent-event (TTRE) in stepped wedge cluster randomised trial (SWCRT) using an open cohort design. This study aims to address this by evaluating the performance of these statistical models using an open cohort design with the Monte Carlo simulation in various settings and their application using an actual example.

METHODS

Using Monte Carlo simulations, we evaluated the performance of the existing extended Cox proportional hazard models, i.e., the Andersen-Gill (AG), Prentice-Williams-Peterson Total-Time (PWP-TT), and Prentice-Williams-Peterson Gap-time (PWP-GT) models, using the settings of several event generation models and true intervention effects, with and without stratification by clusters. Unidirectional switching in SWCRT was represented using time-dependent covariates.

RESULTS

Using Monte Carlo simulations with the various described settings, in situations where inter-individual variability do not exist, the PWP-GT model with stratification by clusters showed the best performance in most settings and reasonable performance in the others. The only situation in which the performance of the PWP-TT model with stratification by clusters was not inferior to that of the PWP-GT model with stratification by clusters was when there was a certain amount of follow-up period, and the timing of the trial entry was random within the trial period, including the follow-up period. In situations where inter-individual variability existed, the PWP-GT model consistently underperformed compared to the PWP-TT model. The AG model performed well only in a specific setting. By analysing actual examples, it was found that almost all the statistical models suggested that the risk of events during the intervention condition may be somewhat higher than in the control, although the difference was not statistically significant.

CONCLUSIONS

When estimating the TTRE-based intervention effects of SWCRT in various settings using an open cohort design, the PWP-GT model with stratification by clusters performed most reasonably in situations where inter-individual variability was not present. However, if inter-individual variability was present, the PWP-TT model with stratification by clusters performed best.

摘要

背景

目前尚无关于在采用开放式队列设计的阶梯式楔形群随机试验(SWCRT)中基于时间至复发性事件(TTRE)的干预效果的统计模型表现的方法学研究。本研究旨在通过在各种设置中使用开放式队列设计和蒙特卡罗模拟来评估这些统计模型的性能,并使用实际示例进行应用。

方法

使用蒙特卡罗模拟,我们评估了现有扩展的 Cox 比例风险模型(即 Andersen-Gill(AG)、Prentice-Williams-Peterson 总时间(PWP-TT)和 Prentice-Williams-Peterson 间隔时间(PWP-GT)模型)的性能,使用了几种事件生成模型和真实干预效果的设置,以及有无聚类分层。SWCRT 中的单向转换使用时间相关协变量表示。

结果

使用各种描述性设置的蒙特卡罗模拟,在不存在个体间变异性的情况下,具有聚类分层的 PWP-GT 模型在大多数设置下表现最好,在其他设置下表现合理。只有在存在一定随访期且试验进入时间在试验期间内随机(包括随访期)时,具有聚类分层的 PWP-TT 模型的性能才不劣于具有聚类分层的 PWP-GT 模型。在存在个体间变异性的情况下,PWP-GT 模型的表现始终劣于 PWP-TT 模型。AG 模型仅在特定设置下表现良好。通过分析实际示例,发现几乎所有统计模型都表明,干预条件下事件的风险可能略高于对照条件,但差异无统计学意义。

结论

在采用开放式队列设计的各种设置下,使用基于 TTRE 的 SWCRT 干预效果估计,在不存在个体间变异性的情况下,具有聚类分层的 PWP-GT 模型表现最为合理。但是,如果存在个体间变异性,则具有聚类分层的 PWP-TT 模型表现最佳。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/06fa/9040235/e904362148cd/12874_2022_1552_Fig1_HTML.jpg

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