Restricted mean survival time (RMST) models have gained popularity when analyzing time-to-event outcomes because RMST models offer more straightforward interpretations of treatment effects with fewer assumptions than hazard ratios commonly estimated from Cox models. However, few network meta-analysis (NMA) methods have been developed using RMST. In this paper, we propose advanced RMST NMA models when individual participant data are available. Our models allow us to study treatment effect moderation and provide comprehensive understanding about comparative effectiveness of treatments and subgroup effects. An extensive simulation study and a real data example about treatments for patients with atrial fibrillation are presented.

翻译：限制性平均生存时间（RMST）模型在分析事件发生时间结局时愈发流行，因为与Cox模型估计的风险比相比，RMST模型对治疗效果的解读更直观且所需假设更少。然而，目前基于RMST的网络荟萃分析（NMA）方法仍较为少见。本文针对可获取个体参与者数据的情形，提出了先进的RMST NMA模型。该模型能够研究治疗效果调节作用，并提供关于治疗比较疗效及亚组效应的全面理解。研究通过广泛模拟实验及关于房颤患者治疗的真实数据案例进行了验证。