随机临床试验中的有条件和无条件治疗效果：估计因子、估计和解释

IF 1.5 4区医学 Q3 MATHEMATICAL & COMPUTATIONAL BIOLOGY

Statistics in Biopharmaceutical Research Pub Date : 2023-12-12 DOI:10.1080/19466315.2023.2292774

Jiawei Wei, Jiajun Xu, Björn Bornkamp, Ray Lin, Hong Tian, Dong Xi, Xin Zhang, Ziqiang Zhao, Satrajit Roychoudhury

引用次数: 0

摘要

ICH E9(R1)明确规定了精确定义临床试验治疗效果的重要性--为患者的选择提供信息并促进循证决策。美国食品和药物管理局（FDA）关于临床试验疗效一致性的指导意见...

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Conditional and Unconditional treatment effects in randomized clinical trials: Estimands, Estimation, and Interpretation

ICH E9(R1) specifies the importance of precisely defining the treatment effect for clinical trials – to inform patient choices and facilitate evidence-based decision-making. FDA's guidance on covar...

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来源期刊

Statistics in Biopharmaceutical Research MATHEMATICAL & COMPUTATIONAL BIOLOGY-STATISTICS & PROBABILITY

CiteScore

3.90

自引率

16.70%

发文量

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.