SEQUENTIAL METHODS FOR CLINICAL TRIALS

这项建议的目的是进行统计研究， 使用序贯方法监测、设计和分析临床试验 要求提前终止，并调查提前终止的影响 终止对此类临床试验结果的解释。 我们将主要关注第三阶段的临床试验，在这些试验中，主要的 关注的结果变量是失败时间。 临床试验应该受到监督似乎是一种共识 在整个研究期间，并因道德和道德原因被终止 如果有实质性的证据表明治疗有差异或缺乏疗效 如此之大的差异。这项提案的目的是提出 基于条件或预测能力的随机缩减测试 提前终止最初设计为 一项固定持续时间的研究，以调查 随机截尾检验和成组序贯检验，并对 使用函数方法在序列设计中的结果 其运行特点。 当临床试验被顺序监测可能的早期 终止，它降低了用于检测 作为必要调整的结果的某些待遇差异 作为重复重要性的结果，保持重要性级别 测试。因此，“样本量”或研究持续时间应该足够 进行调整，以保持所需的灵敏度。具体来说，我们 建议研究序列计算的渐近性质 随着时间的推移，分层对数等级测试统计，以开发方法 用(I)分层的方法确定临床试验的研究期限 随机化和(Ii)多个端点。 序贯分析中样本空间的排序决定了 解释观测到的显著水平，即所谓的p值。 序贯试验中常用的最大似然估计是已知的。 由于可选抽样而产生偏差。因此，有很多 对重复的作用和解释的困惑和争议 显著性检验。因此，我们想回顾和比较属性 不同的构造置信度区间的方法如下 序贯检验和序贯样本空间的各种排序 分析。此外，我们还建议研究该点和可信区间 提前停止后的次要端点的估计程序 基于顺序进行的临床试验中的主要终点。

The objectives of this proposal are to carry out statistical research on monitoring, design and analysis of clinical trials using sequential methods for early termination, and to investigate the implications of early termination in the interpretation of the results from such clinical trials. We will focus primarily on Phase III clinical trials in which the major outcome variable of interest is a failure time. There seems to be a consensus that a clinical trial should be monitored throughout the study duration and be terminated on grounds of ethics and efficacy if there is substantial evidence of treatment difference or lack of such difference. The objective of this proposal is to propose stochastically curtailed tests based on conditional or predictive power for early termination of clinical trials which have initially been designed as a fixed duration study, to investigate the relationship between the stochastic curtailment tests and the group sequential tests, and to explore the consequence of the use function approach during sequential design on the operating characteristics. When clinical trials are sequentially monitored for possible early termination, it reduces the sensitivity of tests employed to detect a certain treatment difference as a consequence of adjustment necessary to maintain the significance level as a consequence of repeated significance testing. Hence the "sample size" or the study duration should be adequately adjusted so that the desired sensitivity is maintained. Specifically, we propose to investigate the asymptotic property of sequentially computed stratified log rank test statistics over time, to develop methods for determining the study duration for clinical trials with (i) stratified randomization and (ii) multiple endpoints. The ordering of the sample space in sequential analysis dictates the interpretation of the observed significance level, the so-called p value. The usual maximum likelihood estimators in sequential experiments are known to be biased due to the optional sampling. As a result there is a lot of confusion and controversy over the role and the interpretation of repeated significance testing. Hence we would like to review and compare properties of different methods for constructing confidence intervals following sequential tests and of various orderings of the sample space in sequential analysis. Also we propose to investigate the point and confidence interval estimation procedure for the secondary endpoint following early stopping based on the primary endpoint in sequentially conducted clinical trails.