Date Science, Sumitomo Pharma America, Marlborough, Massachusetts, USA.
Department of Biometrics, AstraZeneca, 1 Medimmune Way, Gaithersburg, MD.
Pharm Stat. 2024 May-Jun;23(3):399-407. doi: 10.1002/pst.2359. Epub 2024 Jan 11.
Since the publication of ICH E9 (R1), "Addendum to statistical principles for clinical trials: on choosing appropriate estimands and defining sensitivity analyses in clinical trials," there has been a lot of debate about the hypothetical strategy for handling intercurrent events. Arguments against the hypothetical strategy are twofold: (1) the clinical question has limited clinical/regulatory interest; (2) the estimation may need strong statistical assumptions. In this article, we provide an example of a hypothetical strategy handling use of rescue medications in the acute pain setting. We argue that the treatment effect of a drug that is attributable to the treatment alone is the clinical question of interest and is important to regulators. The hypothetical strategy is important when developing non-opioid treatment as it estimates the treatment effect due to treatment during the pre-specified evaluation period whereas the treatment policy strategy does not. Two widely acceptable and non-controversial clinical inputs are required to construct a reasonable estimator. More importantly, this estimator does not rely on additional strong statistical assumptions and is considered reasonable for regulatory decision making. In this article, we point out examples where estimators for a hypothetical strategy can be constructed without any strong additional statistical assumptions besides acceptable clinical inputs. We also showcase a new way to obtain estimation based on disease specific clinical knowledge instead of strong statistical assumptions. In the example presented, we clearly demonstrate the advantages of the hypothetical strategy compared to alternative strategies including the treatment policy strategy and a composite variable strategy.
自 ICH E9(R1)“临床试验统计原则补充说明:临床试验中恰当的目标值选择和敏感性分析定义”发表以来,关于处理伴随事件的假设策略一直存在很多争议。反对假设策略的论点有两点:(1)临床问题仅具有有限的临床/监管意义;(2)估计可能需要较强的统计假设。本文通过一个在急性疼痛治疗中应用抢救药物的假设策略处理示例,说明了处理伴随事件的假设策略的合理性。我们认为,药物的治疗效果归因于治疗本身,这是监管者关注的临床问题,非常重要。当开发非阿片类药物治疗时,假设策略很重要,因为它可以估计在指定的评估期内由于治疗而产生的治疗效果,而治疗政策策略则无法做到这一点。构建合理的估计器需要两个广泛接受且无争议的临床输入。更重要的是,该估计器不需要额外的强统计假设,被认为是监管决策的合理选择。本文指出了在除了可接受的临床输入外,没有任何其他强统计假设的情况下,如何构建假设策略的估计器的示例。本文还展示了一种基于特定疾病临床知识而不是强统计假设来获得估计值的新方法。在提出的示例中,我们清楚地展示了假设策略相对于替代策略(包括治疗政策策略和复合变量策略)的优势。
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