Often in Phase 3 clinical trials measuring a long-term time-to-event endpoint, such as overall survival or progression-free survival, investigators also collect repeated measures on biomarkers which may be predictive of the primary endpoint. Although these data may not be leveraged directly to support early stopping decisions, can we make greater use of these data to increase efficiency and improve interim decision making? We present a joint model for longitudinal and time-to-event data and a method which establishes the distribution of successive estimates of parameters in the joint model across interim analyses. With this in place, we can use the estimates to define both efficacy and futility stopping rules. Using simulation, we evaluate the benefits of incorporating biomarker information and the affects on interim decision making.
翻译:通常在第3阶段临床试验中,测量长期时间到活动终点(如总体生存或逐步无损生存),调查人员还收集生物标记的反复措施,这些措施可以预测主要终点。虽然这些数据可能不能直接用于支持早期停止决策,但我们能否更多地利用这些数据来提高效率和改善临时决策?我们提出了一个纵向和时间到活动数据的联合模型,以及一种确定在联合模型中将参数的连续估计分布在临时分析中的方法。有了这个方法,我们可以使用这些估计数来界定有效性和徒劳性停止规则。我们利用模拟来评估纳入生物标记信息的好处和对临时决策的影响。