We consider estimation in a randomised placebo-controlled or standard-of-care-controlled drug trial with quantitative outcome, where participants who discontinue an investigational treatment are not followed up thereafter, and the estimand follows a treatment policy strategy for handling treatment discontinuation. Our approach is also useful in situations where participants take rescue medication or a subsequent line of therapy and the estimand follows a hypothetical strategy to estimate the effect of initially randomised treatment in the absence of rescue or other active treatment. Carpenter et al proposed reference-based imputation methods which use a reference arm to inform the distribution of post-discontinuation outcomes and hence to inform an imputation model. However, the reference-based imputation methods were not formally justified. We present a causal model which makes an explicit assumption in a potential outcomes framework about the maintained causal effect of treatment after discontinuation. We use mathematical argument and a simulation study to show that the "jump to reference", "copy reference" and "copy increments in reference" reference-based imputation methods, with the control arm as the reference arm, are special cases of the causal model with specific assumptions about the causal treatment effect. We also show that the causal model provides a flexible and transparent framework for a tipping point sensitivity analysis in which we vary the assumptions made about the causal effect of discontinued treatment. We illustrate the approach with data from two longitudinal clinical trials.

中文翻译：

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在具有定量结果的临床试验中用于基于参考的插补和临界点分析的因果建模框架。

我们考虑在具有定量结果的随机安慰剂对照或标准护理对照药物试验中进行估计，其中停止研究性治疗的参与者此后不进行随访，并且估计遵循处理治疗中断的治疗政策策略。我们的方法在参与者服用救援药物或后续治疗线并且估计值遵循假设策略来估计初始随机治疗在没有救援或其他积极治疗的情况下的效果的情况下也很有用。Carpenter 等人提出了基于参考的插补方法，该方法使用参考臂来告知停药后结果的分布，从而告知插补模型。然而，基于参考的插补方法并没有正式的合理性。我们提出了一个因果模型，该模型在潜在结果框架中做出了关于停药后维持因果效应的明确假设。我们使用数学论证和模拟研究表明，以控制臂为参考臂的“跳转到参考”、“复制参考”和“参考中的复制增量”基于参考的插补方法是因果关系的特例。具有关于因果处理效应的特定假设的模型。我们还表明，因果模型为临界点敏感性分析提供了一个灵活和透明的框架，在该框架中，我们改变了对停止治疗的因果效应所做的假设。我们用来自两个纵向临床试验的数据说明了该方法。