Aligning sample size calculations with estimands in clinical trials with time-to-event outcomes

被引:0
|
作者
Fang, Yixin [1 ]
Jin, Man [1 ]
Wu, Chengqing [2 ]
机构
[1] Fang 1 North Waukegan Rd, N Chicago, IL 60064 USA
[2] 55,Challenger Rd STE 501, Ridgefield Pk, NJ 07660 USA
关键词
AND PHRASES; Clinical trials; Estimand; current events; Sample size; Time-to-event;
D O I
暂无
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
The ICH E9(R1) guidance recommended a framework to align planning, design, conduct, analysis, and interpretation of any clincial trial with its objective and estimand. How to handle intercurrent events (ICEs) is one of the five attributes of an estimand and sample size calculation is a key step in the trial planning and design. Therefore, sample size calcula-tion should be aligned with the estimand and, in particular, with how the ICEs are handled. ICH E9(R1) summarized five strategies for handling ICEs, and five approaches have been proposed in the literature for sample size calculation when planning trials with quantitative and binary outcomes. In this paper, we discuss how to apply the five strategies to deal with ICEs in clinical trials with time-to-event outcomes and propose five approaches for sample size calculation that are aligned with the five strategies, respectively. AMS 2000 SUBJECT CLASSIFICATIONS: Primary 62N03, 62G10; secondary 62G99.
引用
收藏
页码:63 / 68
页数:6
相关论文
共 50 条
  • [21] Power and sample-size analysis for the Royston Parmar combined test in clinical trials with a time-to-event outcome
    Royston, Patrick
    STATA JOURNAL, 2018, 18 (01): : 3 - 21
  • [22] Sample size calculation for time-to-event data in stepped wedge cluster randomised trials
    Takanashi, Fumihito
    Keding, Ada
    Crouch, Simon
    Kanaan, Mona
    TRIALS, 2016, 17
  • [23] Comparison of Time-to-Event Data for Clinical Trials
    Nadarajah, Saralees
    MONTE CARLO METHODS AND APPLICATIONS, 2007, 13 (01): : 21 - 35
  • [24] Multivariate two-sample permutation tests for trials with multiple time-to-event outcomes
    Persson, Inger
    Arnroth, Lukas
    Thulin, Mans
    PHARMACEUTICAL STATISTICS, 2019, 18 (04) : 476 - 485
  • [25] Sample size calculations for clinical trials
    Chow, Shein-Chung
    WILEY INTERDISCIPLINARY REVIEWS-COMPUTATIONAL STATISTICS, 2011, 3 (05): : 414 - 427
  • [26] Survival plots of time-to-event outcomes in clinical trials: good practice and pitfalls
    Pocock, SJ
    Clayton, TC
    Altman, DG
    LANCET, 2002, 359 (9318): : 1686 - 1689
  • [27] Discrimination-based sample size calculations for multivariable prognostic models for time-to-event data
    Jinks, Rachel C.
    Royston, Patrick
    Parmar, Mahesh K. B.
    BMC MEDICAL RESEARCH METHODOLOGY, 2015, 15
  • [28] Analysis of time-to-event and duration outcomes in neonatal clinical trials with twin births
    Shaffer, Michele L.
    Hiriote, Sasiprapa
    CONTEMPORARY CLINICAL TRIALS, 2009, 30 (02) : 150 - 154
  • [29] Discrimination-based sample size calculations for multivariable prognostic models for time-to-event data
    Rachel C. Jinks
    Patrick Royston
    Mahesh KB Parmar
    BMC Medical Research Methodology, 15
  • [30] Time-to-event estimands and loss to follow-up in oncology in light of the estimands guidance
    Siegel, Jonathan M.
    Weber, Hans-Jochen
    Englert, Stefan
    Liu, Feng
    Casey, Michelle
    PHARMACEUTICAL STATISTICS, 2024, 23 (05) : 709 - 727