Ensign L G, Gehan E A, Kamen D S, Thall P F
Department of Biomathematics, University of Texas M.D. Anderson Cancer Center, Houston 77030.
Stat Med. 1994 Sep 15;13(17):1727-36. doi: 10.1002/sim.4780131704.
A phase II clinical trial in cancer therapeutics is usually a single-arm study to determine whether an experimental treatment (E) holds sufficient promise to warrant further testing. When the criterion of treatment efficacy is a binary endpoint (response/no response) with probability of response p, we propose a three-stage optimal design for testing H0: p < or = p0 versus H1: p > or = p1, where p1 and p0 are response rates such that E does or does not merit further testing at given levels of statistical significance (alpha) and power (1--beta). The proposed design is essentially a combination of earlier proposals by Gehan and Simon. The design stops with rejection of H1 at stage 1 when there is an initial moderately long run of consecutive treatment failures; otherwise there is continuation to stage 2 and (possibly) stage 3 which have decision rules analogous to those in stages 1 and 2 of Simon's design. Thus, rejection of H1 is possible at any stage, but acceptance only at the final stage. The design is optimal in the sense that expected sample size is minimized when p = p0, subject to the practical constraint that the minimum stage 1 sample size is at least 5. The proposed design has greatest utility when the true response rate of E is small, it is desirable to stop early if there is a moderately long run of early treatment failures, and it is practical to implement a three-stage design. Compared to Simon's optimal two-stage design, the optimal three-stage design has the following features: stage 1 is the same size or smaller and has the possibility of stopping earlier when 0 successes are observed; the expected sample size under the null hypothesis is smaller; stages 1 and 2 generally have more patients than stage 1 of the two-stage design, but a higher probability of early termination under H0; and the total sample size and criteria for rejection of H1 at stage 3 are similar to the corresponding values at the end of stage 2 in the two-stage optimal design.
癌症治疗的II期临床试验通常是一项单臂研究,旨在确定一种实验性治疗方法(E)是否具有足够的前景以保证进一步测试。当治疗效果的标准是具有反应概率p的二元终点(反应/无反应)时,我们提出一种三阶段最优设计,用于检验原假设H0:p ≤ p0 与备择假设H1:p ≥ p1,其中p1和p0是反应率,使得在给定的统计显著性水平(α)和检验功效(1 - β)下,E分别值得或不值得进一步测试。所提出的设计本质上是Gehan和Simon早期提议的组合。当出现初始的一段适度长的连续治疗失败时,该设计在第1阶段就拒绝H1而停止;否则继续到第2阶段以及(可能)第3阶段,这两个阶段具有与Simon设计的第1阶段和第2阶段类似的决策规则。因此,在任何阶段都有可能拒绝H1,但只有在最后阶段才接受。该设计在p = p0时预期样本量最小的意义上是最优的,但要满足第1阶段最小样本量至少为5的实际约束。当E的真实反应率较小时,所提出的设计具有最大效用;如果有一段适度长的早期治疗失败情况,希望尽早停止;并且实施三阶段设计是可行的。与Simon的最优两阶段设计相比,最优三阶段设计具有以下特点:第1阶段规模相同或更小,并且在观察到0次成功时有可能更早停止;原假设下的预期样本量更小;第1阶段和第2阶段通常比两阶段设计的第1阶段有更多患者,但在H0下早期终止的概率更高;第3阶段的总样本量和拒绝H1的标准与两阶段最优设计第2阶段末尾的相应值相似。