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带阈值识别的生物标志物引导自适应富集生存试验设计AI 解读

Biomarker-guided designs are increasingly used to evaluate personalized treatments based on patients' biomarker status in Phase II and III clinical trials. With adaptive enrichment, these designs can improve the efficiency of evaluating the treatment effect in biomarker-positive patients by increasing their proportion in the randomized trial. While time-to-event outcomes are often used as the primary endpoint to measure treatment effects for a new therapy in severe diseases…

多区域临床试验中基于限制平均生存时间的处理效应及区域修饰因素推断AI 解读

Multi-regional clinical trials (MRCTs) play an increasingly crucial role in global pharmaceutical development by expediting data gathering and regulatory approval across diverse patient populations. However, differences in recruitment practices and regional demographics often lead to variations in study participant characteristics, potentially biasing treatment effect estimates and undermining treatment effect consistency assessment across regions. To address this challenge,…

利用个体数据与限制平均生存时间回归开展生存结局网络荟萃分析AI 解读

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…