GROUP SEQUENTIAL METHODS FOR LONGITUDINAL DATA

现在，在临床试验中进行中期分析是很常见的。这种对临床试验数据的监测对于确保参与试验的志愿者患者得到合乎道德的治疗至关重要。此外，使用分组顺序停止规则可以大大提高采用新处理的效率。这项研究的目标是拓宽可以使用中期分析的研究范围，特别强调适用于临床试验的方法，这些方法涉及基于一段时间的测量结果的测量。由于数据在最早的分析中所涵盖的时间跨度有限，这种纵向研究在群体顺序监测中提出了独特的问题。在研究过程中，这种随访时间的变化可能会对用于确定治疗效果的分析方法的稳健性产生重大影响。在本项目下将开展的具体研究领域包括：1)开发对跨越危险具有健壮性的生存数据测试策略；2)针对纵向非存活数据开发对随时间的非线性治疗效应具有健壮性的测试策略；3)开发用于临床试验监测的贝叶斯方法，其显示出与针对生存数据和其他纵向数据的频域分析所开发的方法类似的稳健性；4)推广针对多个端点开发的方法以解决纵向数据问题；5)推广灵活的监测方案以适应稳健的纵向方法；以及6)开发计算机软件以在临床试验模块中实施这些策略。

It is now commonplace for interim analyses to be performed in clinical trials. Such monitoring of the clinical trial data is essential to ensure that volunteer patients participating in the trial are treated ethically. Furthermore, the use of group sequential stopping rules can greatly increase the efficiency with which new treatments are adopted. The goal of this research is to broaden the spectrum of studies in which interim analyses can be used, with specific emphasis placed on methods appropriate for clinical trials which involve outcome measures based on measurements made over time. Such longitudinal studies pose unique problems in group sequential monitoring due to the limited timespan covered by the data at the earliest analyses. This variation in length of follow-up over the course of the study can have major impact on the robustness of the analytic methods used for determining treatment efficacy. Specific areas of research to be conducted under this project include: 1) development of testing strategies for survival data that are robust to crossing hazards; 2) development of testing strategies for longitudinal nonsurvival data that are robust to nonlinear treatment effects over time; 3) development of Bayesian methods for clinical trial monitoring that exhibit robustness properties similar to those developed for frequentist analysis of survival and other longitudinal data; 4) generalization of methods developed for multiple endpoints in order to address longitudinal data issues; 5) generalization of flexible monitoring schemes to accommodate robust longitudinal methods; and 6) development of computer software to implement these strategies in a clinical trials module.