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本文引用的文献

1
Joint Inference for Competing Risks Survival Data.竞争风险生存数据的联合推断
J Am Stat Assoc. 2016;111(515):1289-1300. doi: 10.1080/01621459.2015.1093942. Epub 2016 Oct 18.
2
A competing risks analysis should report results on all cause-specific hazards and cumulative incidence functions.竞争风险分析应报告所有病因特异性危害和累积发生率函数的结果。
J Clin Epidemiol. 2013 Jun;66(6):648-53. doi: 10.1016/j.jclinepi.2012.09.017. Epub 2013 Feb 14.
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Simulating competing risks data in survival analysis.在生存分析中模拟竞争风险数据。
Stat Med. 2009 Mar 15;28(6):956-71. doi: 10.1002/sim.3516.
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Sample size calculations in the presence of competing risks.存在竞争风险时的样本量计算。
Stat Med. 2007 Dec 30;26(30):5370-80. doi: 10.1002/sim.3114.
5
Evaluation of sample size and power for multi-arm survival trials allowing for non-uniform accrual, non-proportional hazards, loss to follow-up and cross-over.考虑到非均匀入组、非比例风险、失访和交叉的多臂生存试验的样本量和检验效能评估。
Stat Med. 2006 Aug 15;25(15):2521-42. doi: 10.1002/sim.2517.
6
Sample sizes for clinical trials with time-to-event endpoints and competing risks.具有事件发生时间终点和竞争风险的临床试验的样本量。
Contemp Clin Trials. 2005 Jun;26(3):386-96. doi: 10.1016/j.cct.2005.01.010. Epub 2005 Apr 26.
7
A sample size formula for the supremum log-rank statistic.用于最大对数秩统计量的样本量公式。
Biometrics. 2005 Mar;61(1):86-91. doi: 10.1111/j.0006-341X.2005.031206.x.
8
Sample size formula for proportional hazards modelling of competing risks.用于竞争风险比例风险建模的样本量公式。
Stat Med. 2004 Nov 15;23(21):3263-74. doi: 10.1002/sim.1915.
9
Dealing with competing risks: testing covariates and calculating sample size.处理竞争风险：检验协变量与计算样本量
Stat Med. 2002 Nov 30;21(22):3317-24. doi: 10.1002/sim.1271.
10
Sample size considerations for the evaluation of prognostic factors in survival analysis.生存分析中评估预后因素时的样本量考量
Stat Med. 2000 Feb 29;19(4):441-52. doi: 10.1002/(sici)1097-0258(20000229)19:4<441::aid-sim349>3.0.co;2-n.

联合检验有竞争风险时的特定原因风险和全因风险的样本量确定。

Sample size determination for jointly testing a cause-specific hazard and the all-cause hazard in the presence of competing risks.

机构信息

School of Nursing, Duke University, Durham, NC, USA.

Department of Statistics and Actuarial Science, University of Hong Kong, Pokfulam Road, Pokfulam, Hong Kong.

出版信息

Stat Med. 2018 Apr 15;37(8):1389-1401. doi: 10.1002/sim.7590. Epub 2017 Dec 27.

DOI:10.1002/sim.7590
PMID:29282764
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6148356/
Abstract

This article considers sample size determination for jointly testing a cause-specific hazard and the all-cause hazard for competing risks data. The cause-specific hazard and the all-cause hazard jointly characterize important study end points such as the disease-specific survival and overall survival, which are commonly used as coprimary end points in clinical trials. Specifically, we derive sample size calculation methods for 2-group comparisons based on an asymptotic chi-square joint test and a maximum joint test of the aforementioned quantities, taking into account censoring due to lost to follow-up as well as staggered entry and administrative censoring. We illustrate the application of the proposed methods using the Die Deutsche Diabetes Dialyse Studies clinical trial. An R package "powerCompRisk" has been developed and made available at the CRAN R library.

摘要

本文考虑了联合检验竞争风险数据的特定原因风险和全因风险的样本量确定。特定原因风险和全因风险共同描述了重要的研究终点，如疾病特异性生存和总生存，这些终点通常作为临床试验的主要终点。具体来说，我们基于渐近卡方联合检验和上述量的最大联合检验，推导了 2 组比较的样本量计算方法，考虑了因失访而导致的删失以及交错入组和行政删失。我们使用 Die Deutsche Diabetes Dialyse Studies 临床试验说明了所提出方法的应用。一个名为“powerCompRisk”的 R 包已经开发完成，并在 CRAN R 库中提供。