We Need Subject Matter Expertise to Choose and Identify Causal Estimands: Comment on “Estimands for Recurrent Event Endpoints in the Presence of a Terminal Event”
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引用次数: 1
Abstract
Abstract We summarize what we consider to be the two main limitations of the “Estimands for Recurrent Event Endpoints in the Presence of a Terminal Event” (Schmidli et al. 2022). First, the authors did not give detailed guidance on how to choose an appropriate estimand in light of subject-matter considerations. Reasoning about the mechanism by which treatment affects different types of events is central when selecting a causal estimand, and such reasoning can be grounded in the interventionist mediation literature. Second, the article also did not discuss the crucial task of identification when the aim is to study a causal question. Thereby, the authors omit important differences in the uncertainty of the assumptions needed to target each estimand by particular statistical methods. These assumptions have crucial implications for the confidence that can be placed in a given effect estimate, and for the planning and collection of relevant variables in the study design.
摘要我们总结了我们认为的“在终端事件存在的情况下对重复事件终点的估计”的两个主要限制(Schmidli et al. 2022)。首先，作者没有就如何根据主题事项考虑选择适当的估计给出详细的指导。在选择因果估计时，关于治疗影响不同类型事件的机制的推理是核心，这种推理可以在干预主义调解文献中建立基础。其次，本文也没有讨论识别的关键任务，当目的是研究一个因果问题。因此，作者通过特定的统计方法忽略了针对每个估计所需的假设不确定性中的重要差异。这些假设对于给定效果估计的置信度以及研究设计中相关变量的规划和收集具有至关重要的意义。
期刊介绍：
Statistics in Biopharmaceutical Research ( SBR), publishes articles that focus on the needs of researchers and applied statisticians in biopharmaceutical industries; academic biostatisticians from schools of medicine, veterinary medicine, public health, and pharmacy; statisticians and quantitative analysts working in regulatory agencies (e.g., U.S. Food and Drug Administration and its counterpart in other countries); statisticians with an interest in adopting methodology presented in this journal to their own fields; and nonstatisticians with an interest in applying statistical methods to biopharmaceutical problems.
Statistics in Biopharmaceutical Research accepts papers that discuss appropriate statistical methodology and information regarding the use of statistics in all phases of research, development, and practice in the pharmaceutical, biopharmaceutical, device, and diagnostics industries. Articles should focus on the development of novel statistical methods, novel applications of current methods, or the innovative application of statistical principles that can be used by statistical practitioners in these disciplines. Areas of application may include statistical methods for drug discovery, including papers that address issues of multiplicity, sequential trials, adaptive designs, etc.; preclinical and clinical studies; genomics and proteomics; bioassay; biomarkers and surrogate markers; models and analyses of drug history, including pharmacoeconomics, product life cycle, detection of adverse events in clinical studies, and postmarketing risk assessment; regulatory guidelines, including issues of standardization of terminology (e.g., CDISC), tolerance and specification limits related to pharmaceutical practice, and novel methods of drug approval; and detection of adverse events in clinical and toxicological studies. Tutorial articles also are welcome. Articles should include demonstrable evidence of the usefulness of this methodology (presumably by means of an application).
The Editorial Board of SBR intends to ensure that the journal continually provides important, useful, and timely information. To accomplish this, the board strives to attract outstanding articles by seeing that each submission receives a careful, thorough, and prompt review.
Authors can choose to publish gold open access in this journal.
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