Sample size calculation for the proportional hazards cure model

被引:30
|
作者
Wang, Songfeng [1 ]
Zhang, Jiajia [1 ]
Lu, Wenbin [2 ]
机构
[1] Univ S Carolina, Dept Epidemiol & Biostat, Columbia, SC 29208 USA
[2] N Carolina State Univ, Dept Stat, Raleigh, NC 27695 USA
基金
美国国家卫生研究院;
关键词
clinical trial; proportional hazards cure model; power; sample size; weighted log-rank test; LONG-TERM SURVIVORS; GENERALIZED WILCOXON TEST; CLINICAL-TRIALS; FOLLOW-UP; MIXTURE MODEL; LOG-RANK; TESTS; POWER; DISTRIBUTIONS; REGRESSION;
D O I
10.1002/sim.5465
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
In clinical trials with time-to-event endpoints, it is not uncommon to see a significant proportion of patients being cured (or long-term survivors), such as trials for the non-Hodgkins lymphoma disease. The popularly used sample size formula derived under the proportional hazards (PH) model may not be proper to design a survival trial with a cure fraction, because the PH model assumption may be violated. To account for a cure fraction, the PH cure model is widely used in practice, where a PH model is used for survival times of uncured patients and a logistic distribution is used for the probability of patients being cured. In this paper, we develop a sample size formula on the basis of the PH cure model by investigating the asymptotic distributions of the standard weighted log-rank statistics under the null and local alternative hypotheses. The derived sample size formula under the PH cure model is more flexible because it can be used to test the differences in the short-term survival and/or cure fraction. Furthermore, we also investigate as numerical examples the impacts of accrual methods and durations of accrual and follow-up periods on sample size calculation. The results show that ignoring the cure rate in sample size calculation can lead to either underpowered or overpowered studies. We evaluate the performance of the proposed formula by simulation studies and provide an example to illustrate its application with the use of data from a melanoma trial. Copyright (C) 2012 John Wiley & Sons, Ltd.
引用
下载
收藏
页码:3959 / 3971
页数:13
相关论文
共 50 条
  • [31] A proportional hazards cure model for the analysis of time to event with frequently unidentifiable causes
    Dahlberg, Suzanne E.
    Wang, Molin
    BIOMETRICS, 2007, 63 (04) : 1237 - 1244
  • [32] Assessing the prediction accuracy of cure in the Cox proportional hazards cure model: an application to breast cancer data
    Asano, Junichi
    Hirakawa, Akihiro
    Hamada, Chikuma
    PHARMACEUTICAL STATISTICS, 2014, 13 (06) : 357 - 363
  • [33] Sample size calculation for mixture cure model with restricted mean survival time as a primary endpoint
    Li, Zhaojin
    Geng, Xiang
    Hou, Yawen
    Chen, Zheng
    STATISTICAL METHODS IN MEDICAL RESEARCH, 2024,
  • [34] Calculation of changes in life expectancy based on proportional hazards model of an intervention
    Kulinskaya, Elena
    Gitsels, Lisanne A.
    Bakbergenuly, Ilyas
    Wright, Nigel R.
    INSURANCE MATHEMATICS & ECONOMICS, 2020, 93 : 27 - 35
  • [35] Estimating baseline distribution in proportional hazards cure models
    Peng, YW
    COMPUTATIONAL STATISTICS & DATA ANALYSIS, 2003, 42 (1-2) : 187 - 201
  • [36] penPHcure: Variable Selection in Proportional Hazards Cure Model with Time-Varying Covariates
    Beretta, Alessandro
    Heuchenne, Cedric
    R JOURNAL, 2021, 13 (01): : 116 - 129
  • [37] Profile likelihood estimation for the cox proportional hazards (PH) cure model and standard errors
    Mohammad, Khandoker Akib
    Hirose, Yuichi
    Surya, Budhi
    Yao, Yuan
    STATISTICAL PAPERS, 2024, 65 (01) : 181 - 201
  • [38] Profile likelihood estimation for the cox proportional hazards (PH) cure model and standard errors
    Khandoker Akib Mohammad
    Yuichi Hirose
    Budhi Surya
    Yuan Yao
    Statistical Papers, 2024, 65 : 181 - 201
  • [39] Reducing sample size needed for cox-proportional hazards model analysis using more efficient sampling method
    Samawi, Hani M.
    Yu, Lili
    Rochani, Haresh
    Vogel, Robert
    COMMUNICATIONS IN STATISTICS-THEORY AND METHODS, 2020, 49 (06) : 1281 - 1298
  • [40] Small sample confidence intervals for survival functions under the proportional hazards model
    Paige, Robert L.
    Abdurasul, Emad
    COMMUNICATIONS IN STATISTICS-THEORY AND METHODS, 2018, 47 (24) : 6108 - 6124