论文标题
使用修改后的意向性治疗作为主要层估计器未能启动治疗
Using modified intention-to-treat as a principal stratum estimator for failure to initiate treatment
论文作者
论文摘要
背景：影响许多试验的常见事件是某些参与者未开始分配的治疗。许多试验都使用修改后的意向治疗方法（MITT）方法，从而将未启动治疗的参与者排除在分析之外。但是，尚不清楚这种方法或公正所必需的假设所针对的估计和估计。 方法：我们证明，不包括不开始治疗的参与者的手套分析是估计主要层面的估计（即，无论他们分配了哪种手臂，都会开始治疗的参与者亚人群的治疗效果）。 MITT估计器对主要层次估计的估计量是公正的，假设互动事件不受指定的治疗部门的影响，即在另一只手臂中启动治疗的参与者也会在另一只部门中这样做。 结果：我们确定了确定手套估计量是否可能公正的两个关键标准：首先，我们必须能够衡量每个经历互联事件的治疗部门的参与者，其次，假设治疗分配不会影响参与者是否开始治疗是否必须合理。大多数双盲试验都将满足这些标准，我们提供了一个开放标签试验的示例，其中也可能满足这些标准。 结论：经过修改的意向性治疗分析，不包括未开始治疗的参与者可以是主要层次估算的公正估计器。我们的框架可以帮助识别何时可以实现无偏的假设，从而修改了意向治疗是否合适。
Background: A common intercurrent event affecting many trials is when some participants do not begin their assigned treatment. Many trials use a modified intention-to-treat (mITT) approach, whereby participants who do not initiate treatment are excluded from the analysis. However, it is not clear the estimand being targeted by such an approach or the assumptions necessary for it to be unbiased. Methods: We demonstrate that a mITT analysis which excludes participants who do not begin treatment is estimating a principal stratum estimand (i.e. the treatment effect in the subpopulation of participants who would begin treatment, regardless of which arm they were assigned to). The mITT estimator is unbiased for the principal stratum estimand under the assumption that the intercurrent event is not affected by the assigned treatment arm, that is, participants who initiate treatment in one arm would also do so in the other arm. Results: We identify two key criteria in determining whether the mITT estimator is likely to be unbiased: first, we must be able to measure the participants in each treatment arm who experience the intercurrent event, and second, the assumption that treatment allocation will not affect whether the participant begins treatment must be reasonable. Most double-blind trials will satisfy these criteria, and we provide an example of an open-label trial where these criteria are likely to be satisfied as well. Conclusions: A modified intention-to-treat analysis which excludes participants who do not begin treatment can be an unbiased estimator for the principal stratum estimand. Our framework can help identify when the assumptions for unbiasedness are likely to hold, and thus whether modified intention-to-treat is appropriate or not.
