You may have worked on more adaptive designs than you think.
You may have worked on more adaptive designs than you think.
复制标题
您的适应性设计可能比您想象的要多。
DOI：
10.1161/strokeaha.114.004288
复制
发表时间：
2015
期刊：
影响因子：
8.3
通讯作者：
Coffey,ChristopherS
中科院分区：
文献类型：
--
作者：
Coffey,ChristopherS
随机削减方法通常用于评估无效性。[3]采用这种方法，如果在中期阶段，根据当前数据，可以预测试验结果的可能性很高，则应停止试验。例如，如果中期数据表明试验不太可能是积极的，则应强烈考虑终止试验。评估无效性的最常见方法是使用条件把握度，即在给定观察到的统计量并假设未来观察结果的预定效应的情况下，最终阶段的检验统计量被拒绝的概率。因此，如果在中期分析时观察到不利趋势，则条件把握度表示不利趋势在试验结束时可能逆转的概率。如果条件把握度低于某个预先设定的阈值，通常为10%至20%，则试验可能因无效而停止。然而，这种方法受到了批评，因为当观察到的效应接近空值时，在最初假设的替代方案下计算条件把握度可能会错误地夸大真实把握度，从而使试验因无效而停止的可能性降低。预测功效方法通过计算给定观测数据的治疗差异的后验分布的条件功效值的加权平均值来解决这个问题。与条件功效一样，预测功效可用于定义形式的无效停止规则。
Stochastic curtailment methods are generally used for assessing futility. 3 With this approach, a trial should be stopped if one can predict the outcome of the trial with high probability given the current data at an interim stage. For example, if the interim data suggest that the trial is unlikely to be positive, strong consideration should be made to terminating the trial. The most common approach for assessing futility is the use of conditional power, the probability that the test statistic at the final stage will be rejected given the observed statistic and assuming the prespecified effect for future observations. Hence, if an unfavorable trend is observed at an interim analysis, the conditional power represents the probability that the unfavorable trend might be reversed by the end of the trial. If the conditional power is below some prespecified threshold, typically 10% to 20%, the trial may be stopped for futility. However, this approach has been criticized because computing conditional power under the originally assumed alternative when the observed effect is near the null value may falsely overstate the true power and subsequently make it less likely the trial will stop for futility. A predictive power approach alleviates this problem by computing a weighted average of the conditional power values of the posterior distribution of the treatment difference given the observed data. As with conditional power, predictive power can be used to define a formal futility stopping rule.