Betensky R A
Department of Biostatistics, Harvard School of Public Health, Boston, Massachusetts 02115, USA.
Biometrics. 1998 Mar;54(1):229-42.
It is desirable to have procedures available for stopping a clinical trial early if there appears to be no treatment effect. Conditional power procedures allow for early stopping in favor of the null hypothesis if the probability of rejecting H0 at the planned end of the trial given the current data and a value of the parameter of interest is below some threshold level. Lan, Simon, and Halperin (1982, Communications in Statistics C1, 207-219) proposed a stochastic curtailment procedure that calculates the conditional power under the alternative hypothesis. Alternatively, predictive power procedures incorporate information from the observed data by averaging the conditional power over the posterior distribution of the parameter. For complex problems in which explicit evaluation of conditional power is not possible, we propose treating the problem of projecting the outcome of a trial given the current data as a missing data problem. We then complete the data using multiple imputation and thus eliminate the need for explicit calculation of conditional power. We apply this method to AIDS Clinical Trials Group (ACTG) protocol 118 and to several simulated clinical trials.
如果似乎没有治疗效果，希望有可供使用的程序来提前终止临床试验。条件效能程序允许在给定当前数据和感兴趣参数值的情况下，如果在试验计划结束时拒绝原假设的概率低于某个阈值水平，则提前终止试验并支持原假设。Lan、Simon和Halperin（1982年，《统计通信C1》，第207 - 219页）提出了一种随机截尾程序，该程序在备择假设下计算条件效能。另外，预测效能程序通过对参数的后验分布上的条件效能进行平均来纳入来自观察数据的信息。对于无法明确评估条件效能的复杂问题，我们建议将根据当前数据预测试验结果的问题视为一个缺失数据问题。然后我们使用多重填补来完成数据，从而无需明确计算条件效能。我们将此方法应用于艾滋病临床试验组（ACTG）方案118以及几个模拟临床试验。
