采用修改后的意向治疗作为启动治疗失败的主要分层估计器。
Using modified intention-to-treat as a principal stratum estimator for failure to initiate treatment.
机构信息
MRC Clinical Trials Unit at UCL, London, UK.
Department of Anaesthesia, University Hospital Southampton NHS Foundation Trust, Southampton, UK.
出版信息
Clin Trials. 2023 Jun;20(3):269-275. doi: 10.1177/17407745231160074. Epub 2023 Mar 14.
BACKGROUND
A common intercurrent event affecting many trials is when some participants do not begin their assigned treatment. For example, in a double-blind drug trial, some participants may not receive any dose of study medication. Many trials use a 'modified intention-to-treat' approach, whereby participants who do not initiate treatment are excluded from the analysis. However, it is not clear (a) the estimand being targeted by such an approach and (b) the assumptions necessary for such an approach to be unbiased.
METHODS
Using potential outcome notation, we demonstrate that a modified intention-to-treat analysis which excludes participants who do not begin treatment is estimating a estimand (i.e. the treatment effect in the subpopulation of participants who would begin treatment, regardless of which arm they were assigned to). The modified intention-to-treat 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 (i.e. if someone began the intervention, they would also have begun the control, and vice versa).
RESULTS
We identify two key criteria in determining whether the modified intention-to-treat 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, as the decision to start treatment cannot be influenced by the allocation, and we provide an example of an open-label trial where these criteria are likely to be satisfied as well, implying that a modified intention-to-treat analysis which excludes participants who do not begin treatment is an unbiased estimator for the principal stratum effect in these settings. We also give two examples where these criteria will not be satisfied (one comparing an active intervention vs usual care, where we cannot identify which usual care participants would have initiated the active intervention, and another comparing two active interventions in an unblinded manner, where knowledge of the assigned treatment arm may affect the participant's choice to begin or not), implying that a modified intention-to-treat estimator will be biased in these settings.
CONCLUSION
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.
背景
许多试验中都会出现一种常见的并发事件，即部分参与者未开始接受其指定的治疗。例如，在一项双盲药物试验中，部分参与者可能未接受任何剂量的研究药物。许多试验采用“改良意向治疗”方法，即不启动治疗的参与者将被排除在分析之外。然而，目前尚不清楚（a）该方法针对的估计量是什么，以及（b）该方法无偏倚的必要假设是什么。
方法
我们使用潜在结果表示法，证明排除未开始治疗的参与者的改良意向治疗分析估计的是一个治疗效果的估计量（即，无论分配到哪个治疗组，都会开始治疗的参与者亚组的治疗效果）。在并发事件不受指定治疗组影响的假设下，改良意向治疗估计值对于主要层估计量是无偏的，也就是说，在一个治疗组中开始治疗的参与者在另一个治疗组中也会开始治疗（即，如果某人开始接受干预，他们也会开始接受对照，反之亦然）。
结果
我们确定了确定改良意向治疗估计值是否可能无偏的两个关键标准：首先，我们必须能够测量每个治疗组中发生并发事件的参与者；其次，参与者开始治疗的决定不受治疗分配影响的假设必须合理。大多数双盲试验都满足这些标准，因为治疗的决定不能受到分配的影响，我们提供了一个开放标签试验的例子，在这些情况下，这些标准很可能得到满足，这意味着排除未开始治疗的参与者的改良意向治疗分析是这些情况下主要层效果的无偏估计值。我们还给出了两个不满足这些标准的例子（一个是比较活性干预与常规护理，在这种情况下，我们无法确定哪些常规护理参与者会开始接受活性干预；另一个是在非盲法下比较两种活性干预，在这种情况下，对指定治疗组的了解可能会影响参与者开始或不开始治疗的选择），这意味着在这些情况下，改良意向治疗估计值会有偏差。
结论
排除未开始治疗的参与者的改良意向治疗分析可以是主要层估计量的无偏估计值。我们的框架可以帮助确定无偏性假设成立的可能性，从而确定改良意向治疗是否合适。
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