Sample Size Reestimation in Clinical Trials

被引:0
|
作者
Zhenming Shun
机构
[1] Aventis Pharma,
来源
Drug information journal : DIJ / Drug Information Association | 2001年 / 35卷
关键词
Conditional power; Type I error; Efficiency; Group sequential method; Stochastic curtailment;
D O I
暂无
中图分类号
学科分类号
摘要
This paper describes an approach to performing interim sample size reestimation based on the observed treatment difference in clinical trials. The approach combines the advantages of the group sequential and sample size reestimation methods and provides an efficient design for clinical trials. It provides flexibility but still maintains the integrity of the trial. To control the overall type I error level, a method is proposed to adjust the group sequential stopping boundaries adjusted for sample size reestimation and negative stops. The adjusted stopping boundaries are flexible to different rules of sample size reestimation and reuse the alpha values saved by negative stops. The adjustment is based on the exact type I error change and, therefore, the penalty for the type I error inflation due to such an interim reestimation is kept to a minimum. The efficiency of sample size reestimation without positive stops is compared with the group sequential method using unconditional power and expected sample size. All results are based on sufficient mathematical justifications.
引用
收藏
页码:1409 / 1422
页数:13
相关论文
共 50 条
  • [41] Information-based sample size re-estimation in group sequential design for longitudinal trials
    Zhou, Jing
    Adewale, Adeniyi
    Shentu, Yue
    Liu, Jiajun
    Anderson, Keaven
    STATISTICS IN MEDICINE, 2014, 33 (22) : 3801 - 3814
  • [42] Conditional power and friends: The why and how of (un)planned, unblinded sample size recalculations in confirmatory trials
    Kunzmann, Kevin
    Grayling, Michael J.
    Lee, Kim May
    Robertson, David S.
    Rufibach, Kaspar
    Wason, James M. S.
    STATISTICS IN MEDICINE, 2022, 41 (05) : 877 - 890
  • [43] Adaptive two-stage bioequivalence trials with early stopping and sample size re-estimation
    Koenig, Franz
    Wolfsegger, Martin
    Jaki, Thomas
    Schuetz, Helmut
    Wassmer, Gernot
    TRIALS, 2015, 16
  • [44] Performance of analytical methods for overdispersed counts in cluster randomized trials: Sample size, degree of clustering and imbalance
    Pacheco, Gonzalo Duran
    Hattendorf, Jan
    Colford, John M., Jr.
    Maeusezahl, Daniel
    Smith, Thomas
    STATISTICS IN MEDICINE, 2009, 28 (24) : 2989 - 3011
  • [45] Sample size re-assessment leading to a raised sample size does not inflate type I error rate under mild conditions
    Per Broberg
    BMC Medical Research Methodology, 13
  • [46] Sample size re-assessment leading to a raised sample size does not inflate type I error rate under mild conditions
    Broberg, Per
    BMC MEDICAL RESEARCH METHODOLOGY, 2013, 13
  • [47] Covariate adjustment in randomized controlled trials with dichotomous outcomes increases statistical power and reduces sample size requirements
    Hernández, AV
    Steyerberg, EW
    Habbema, JDF
    JOURNAL OF CLINICAL EPIDEMIOLOGY, 2004, 57 (05) : 454 - 460
  • [48] Sample size calculation in three-level cluster randomized trials using generalized estimating equation models
    Liu, Jingxia
    Colditz, Graham A.
    STATISTICS IN MEDICINE, 2020, 39 (24) : 3347 - 3372
  • [49] Increasing the sample size when the unblinded interim result is promising
    Chen, YHJ
    DeMets, DL
    Lan, KKG
    STATISTICS IN MEDICINE, 2004, 23 (07) : 1023 - 1038
  • [50] Systematic review finds major deficiencies in sample size methodology and reporting for stepped-wedge cluster randomised trials
    Martin, James
    Taljaard, Monica
    Girling, Alan
    Hemming, Karla
    BMJ OPEN, 2016, 6 (02):