临床试验中的假设估计:因果推断和缺失数据方法的统一。

IF 1.5 4区 医学 Q3 MATHEMATICAL & COMPUTATIONAL BIOLOGY
Camila Olarte Parra, Rhian M Daniel, Jonathan W Bartlett
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引用次数: 11

摘要

ICH E9附录引入了“并发事件”一词,指的是在治疗开始后发生的事件,这些事件可能会妨碍对目标结果的观察或影响其解释。它提出了五种策略来处理并发事件以形成估计,但没有提出估计的统计方法。在本文中,我们关注的是假设策略,其中治疗效果是在假设的情况下定义的,在这种情况下,并发事件被阻止了。对于其估计,我们考虑了因果推理和缺失数据方法。我们建立了某些“因果推理估计量”与某些“缺失数据估计量”相同。这些链接可能对那些熟悉其中一组方法而不熟悉另一组方法的人有所帮助。此外,使用潜在结果表示法使我们能够更清楚地陈述缺失数据方法所依赖的假设,以估计假设的估计。这有助于表明估计假设估计是否合理,以及应该在分析中使用哪些数据。我们表明,假设的估计可以通过利用交互事件发生后的数据来估计,这通常是不使用的。本文的补充材料可在网上获得。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Hypothetical Estimands in Clinical Trials: A Unification of Causal Inference and Missing Data Methods.

Hypothetical Estimands in Clinical Trials: A Unification of Causal Inference and Missing Data Methods.

Hypothetical Estimands in Clinical Trials: A Unification of Causal Inference and Missing Data Methods.

Hypothetical Estimands in Clinical Trials: A Unification of Causal Inference and Missing Data Methods.

The ICH E9 addendum introduces the term intercurrent event to refer to events that happen after treatment initiation and that can either preclude observation of the outcome of interest or affect its interpretation. It proposes five strategies for handling intercurrent events to form an estimand but does not suggest statistical methods for estimation. In this article we focus on the hypothetical strategy, where the treatment effect is defined under the hypothetical scenario in which the intercurrent event is prevented. For its estimation, we consider causal inference and missing data methods. We establish that certain "causal inference estimators" are identical to certain "missing data estimators." These links may help those familiar with one set of methods but not the other. Moreover, using potential outcome notation allows us to state more clearly the assumptions on which missing data methods rely to estimate hypothetical estimands. This helps to indicate whether estimating a hypothetical estimand is reasonable, and what data should be used in the analysis. We show that hypothetical estimands can be estimated by exploiting data after intercurrent event occurrence, which is typically not used. Supplementary materials for this article are available online.

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来源期刊
Statistics in Biopharmaceutical Research
Statistics in Biopharmaceutical Research MATHEMATICAL & COMPUTATIONAL BIOLOGY-STATISTICS & PROBABILITY
CiteScore
3.90
自引率
16.70%
发文量
56
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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