CLINICAL TRIAL DESIGN & INTERIM ANALYSIS--PERSPECTIVE

该提案的总体目标是开发新的连续 临床试验设计和分析的统计方法， 补充现有的分组顺序方法。临床试验需求 中期分析和监测， 原因 关键的统计问题是重复的中期分析 积累数据可能会严重地使传统的 试验结束时比较治疗的固定样本检验 通过夸大第一类错误 因此，临床试验应利用 允许提前停止的（组）顺序程序。 则 问题是，我们在统计信息方面损失了什么（在 与固定样本检验相比），如果我们提前停止试验？ 而不是使用随机削减计算条件 功率，我们建议使用一种更直接的方法来计算 序贯检验与固定样本检验不一致。 最 重要的是，我们提出了一个正式的（组）顺序边界，允许 早期停止，并保留了固定样本设计的有效性， 以下意义：（1）固定样本的整个幂函数 试验和序贯设计几乎相同;（2） 序贯检验得出结论的不一致概率 与固定样本检验相反的最大值可以忽略不计; 样本量不大于相应固定样本量 样本量测试;预期样本量基本上 小于固定样本测试的大小。 所以这样的 序贯规划为决策者提供了更有力的客观依据 当需要提前停止时， 随机条件概率比检验和置信度 正态分布试验序贯停止后的间期 反应和二分的结果;（2）扩大使用不一致的 临床试验监测的可能性;（3）制定方法， 具有重复测量数据或至事件发生时间结局的临床试验; (4)将结果扩展到多个重复测量结果，和/或 时间事件的结果;（5）扩展快速算法计算 不同的试验设计的操作特性，并使 算法也适用于当前组顺序边界， 比较它们;（6）将所提出的方法应用于四个NIH赞助的 多中心试验和癌症试验。

The broad objective of this proposal is to develop new sequential statistical methods for the design and analysis of clinical trials that complement current group sequential methods. Clinical trials demand interim analyses and monitoring for ethical, economical and scientific reasons. The key statistical issue is that repeated interim analyses of accumulating data may seriously invalidate the use of a conventional fixed sample test in comparing the treatments at the end of the trial by inflating the type I error. Therefore clinical trials should utilize a (group) sequential procedures that allow early stopping. Then the issue is, What do we lose in terms of statistical information (in comparison with the fixed sample test) if we stopped the trial early? In stead of using stochastic curtailment that calculates a conditional power, we propose to use a more direct measure that computes the chance that the sequential test and the fixed sample test do not agree. Most importantly, we propose a formal (group) sequential boundary that allows early stopping and retains the validity of a fixed sample design in the following sense: (1) the entire power functions of the fixed sample test and the sequential design are virtually the same; (2) the discordant probability that the sequential test leads to a conclusion opposite to that of the fixed sample test is negligible; (3) the maximum sample size is no greater than the size of the corresponding fixed sample size test; and the expected sample sizes are substantially smaller than the size of the fixed sample test. Therefore, such a sequential plan provides stronger objective evidence to decision makers when early stopping is necessary than do the current group sequential and stochastic conditional probability ratio test and confidence intervals after sequential stopping for trials with normally distributed responses and dichotomous outcomes; (2) to extend the use of discordant probability to clinical trials monitoring; (3) to develop methods for clinical trials with repeated measures data or time-to-event outcomes; (4) to extend the results to multiple repeated measures outcomes, and/or time-to-event outcomes; (5) to extend the fast algorithm for calculating operating characteristics to different trial designs and make the algorithm applicable to current group sequential boundaries as well and compare them; (6) to apply the proposed methods to four NIH sponsored multicenter trials and a cancer trial.