Treatment Effect Measures Under Nonproportional Hazards.

IF 1.3 4区 医学 Q4 PHARMACOLOGY & PHARMACY Pharmaceutical Statistics Pub Date : 2024-10-27 DOI:10.1002/pst.2449
Dan Jackson, Michael Sweeting, Rose Baker
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引用次数: 0

Abstract

'Treatment effect measures under nonproportional hazards' by Snapinn et al. (Pharmaceutical Statistics, 22, 181-193) recently proposed some novel estimates of treatment effect for time-to-event endpoints. In this note, we clarify three points related to the proposed estimators that help to elucidate their properties. We hope that their work, and this commentary, will motivate further discussion concerning treatment effect measures that do not require the proportional hazards assumption.

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非比例危害下的治疗效果测量。
Snapinn 等人的 "非比例危险下的治疗效果测量"(《医药统计》,22,181-193)最近提出了一些新的时间到事件终点治疗效果估计值。在本说明中,我们将阐明与所提估计值有关的三点,以帮助阐明其特性。我们希望他们的工作和这篇评论能激励人们进一步讨论不需要比例危险假设的治疗效果测量方法。
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来源期刊
Pharmaceutical Statistics
Pharmaceutical Statistics 医学-统计学与概率论
CiteScore
2.70
自引率
6.70%
发文量
90
审稿时长
6-12 weeks
期刊介绍: Pharmaceutical Statistics is an industry-led initiative, tackling real problems in statistical applications. The Journal publishes papers that share experiences in the practical application of statistics within the pharmaceutical industry. It covers all aspects of pharmaceutical statistical applications from discovery, through pre-clinical development, clinical development, post-marketing surveillance, consumer health, production, epidemiology, and health economics. The Journal is both international and multidisciplinary. It includes high quality practical papers, case studies and review papers.
期刊最新文献
Optimizing Sample Size Determinations for Phase 3 Clinical Trials in Type 2 Diabetes. Prediction Intervals for Overdispersed Poisson Data and Their Application in Medical and Pre-Clinical Quality Control. Treatment Effect Measures Under Nonproportional Hazards. Bayesian Response Adaptive Randomization for Randomized Clinical Trials With Continuous Outcomes: The Role of Covariate Adjustment. PKBOIN-12: A Bayesian Optimal Interval Phase I/II Design Incorporating Pharmacokinetics Outcomes to Find the Optimal Biological Dose.
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