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.

翻译：背景：影响许多试验的常见并发事件是部分参与者未开始接受指定治疗。众多试验采用修正意向治疗（mITT）方法，即排除未开始治疗的参与者进行分析。然而，该方法所针对的目标估计量及其无偏性所需假设尚不明确。方法：我们证明，排除未开始治疗参与者的mITT分析实际上是在估计首要分层估计量（即无论分配到哪一组都会开始治疗的亚组人群中的治疗效果）。在并发事件不受指定治疗组影响的前提下（即在一个治疗组中开始治疗的参与者在另一组也会同样开始治疗），mITT估计量对首要分层估计量具有无偏性。结果：我们确定了判断mITT估计量是否可能无偏的两个关键标准：首先，必须能够测量各治疗组中经历并发事件的参与者；其次，治疗分配不会影响参与者是否开始治疗的假设必须合理。大多数双盲试验满足这些标准，我们同时提供了开放标签试验中这些标准可能同样得到满足的实例。结论：排除未开始治疗参与者的修正意向治疗分析可作为首要分层估计量的无偏估计量。我们的框架有助于识别无偏性假设可能成立的条件，从而判定修正意向治疗是否适用。