Point estimation in adaptive enrichment designs
Point estimation in adaptive enrichment designs
复制标题
DOI：
10.1002/sim.7412
复制
发表时间：
2017-11-10
影响因子：
2
通讯作者：
Kieser, Meinhard
中科院分区：
文献类型：
--
作者：
Kunzmann, Kevin;Benner, Laura;Kieser, Meinhard
自适应富集设计是旨在证明治疗有效性的临床试验的一个有吸引力的选择，这可能显示出整个患者人群和预先指定的亚组的不同获益。在这些设计中，基于中期数据，选择亚组或全部人群进行进一步探索。当选择是基于疗效数据时，这会给常用的最大似然估计量带来偏倚。对于两阶段设计与一个单一的预先指定的子群的情况下，我们提出了六种替代估计，并研究其性能在模拟研究。在考虑的情况下，最一致的减少偏差的范围内实现了一致的最小方差条件无偏估计与条件矩估计相结合的方法。通过一个临床试验的例子说明了该方法的应用。
Adaptive enrichment designs are an attractive option for clinical trials that aim at demonstrating efficacy of therapies, which may show different benefit for the full patient population and a prespecified subgroup. In these designs, based on interim data, either the subgroup or the full population is selected for further exploration. When selection is based on efficacy data, this introduces bias to the commonly used maximum likelihood estimator. For the situation of two-stage designs with a single prespecified subgroup, we present six alternative estimators and investigate their performance in a simulation study. The most consistent reduction of bias over the range of scenarios considered was achieved by a method combining the uniformly minimum variance conditionally unbiased estimator with a conditional moment estimator. Application of the methods is illustrated by a clinical trial example.