Litwin Samuel, Basickes Stanley, Ross Eric A
Biostatistics and Bioinformatics Facility, Fox Chase Cancer Center, 333 Cottman Avenue, Philadelphia, 19111, PA, U.S.A.
Greenfield Manufacturing, 920 Levick Street, Philadelphia PA, 19111, U.S.A.
Stat Med. 2017 Apr 30;36(9):1383-1394. doi: 10.1002/sim.7226. Epub 2017 Jan 24.
We address design of two-stage clinical trials comparing experimental and control patients. Our end point is success or failure, however measured, with null hypothesis that the chance of success in both arms is p and alternative that it is p among controls and p > p among experimental patients. Standard rules will have the null hypothesis rejected when the number of successes in the (E)xperimental arm, E, sufficiently exceeds C, that among (C)ontrols. Here, we combine one-sample rejection decision rules, E⩾m, with two-sample rules of the form E - C > r to achieve two-sample tests with low sample number and low type I error. We find designs with sample numbers not far from the minimum possible using standard two-sample rules, but with type I error of 5% rather than 15% or 20% associated with them, and of equal power. This level of type I error is achieved locally, near the stated null, and increases to 15% or 20% when the null is significantly higher than specified. We increase the attractiveness of these designs to patients by using 2:1 randomization. Examples of the application of this new design covering both high and low success rates under the null hypothesis are provided. Copyright © 2017 John Wiley & Sons, Ltd.
我们探讨了比较试验组和对照组患者的两阶段临床试验设计。我们的终点是成功或失败,无论如何衡量,原假设是两组的成功概率均为p,备择假设是对照组的成功概率为p,试验组患者的成功概率为p > p。当试验组(E)的成功次数E充分超过对照组(C)的成功次数C时,标准规则将拒绝原假设。在此,我们将单样本拒绝决策规则E⩾m与形式为E - C > r的两样本规则相结合,以实现具有低样本量和低I型错误的两样本检验。我们发现,使用标准两样本规则得到的设计,其样本量与可能的最小样本量相差不远,但与之相关的I型错误为5%,而不是15%或20%,且检验效能相同。这种I型错误水平在原假设附近局部实现,当原假设显著高于规定值时,会增加到15%或20%。我们通过使用2:1随机化提高了这些设计对患者的吸引力。提供了在原假设下涵盖高成功率和低成功率的这种新设计的应用示例。版权所有© 2017约翰威立父子有限公司。