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

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.

[1]  E. Lakatos,et al.  Sample size determination in clinical trials with time-dependent rates of losses and noncompliance. , 1986, Controlled clinical trials.

[2]  E. Ritz,et al.  Serum lipids predict cardiac death in diabetic patients on maintenance hemodialysis. Results of a prospective study. The German Study Group Diabetes and Uremia. , 1993, Nephron.

[3]  K K Lan,et al.  A comparison of sample size methods for the logrank statistic. , 1992, Statistics in medicine.

[4]  A. Skene,et al.  Sample sizes for proportional hazards survival studies with arbitrary patient entry and loss to follow-up distributions. , 1992, Statistics in medicine.

[5]  Michael R. Kosorok,et al.  The Versatility of Function-Indexed Weighted Log-Rank Statistics , 1999 .

[6]  Gang Li,et al.  Joint Inference for Competing Risks Survival Data , 2016, Journal of the American Statistical Association.

[7]  Melania Pintilie,et al.  Dealing with competing risks: testing covariates and calculating sample size , 2002, Statistics in medicine.

[8]  D. Schoenfeld,et al.  Sample-size formula for the proportional-hazards regression model. , 1983, Biometrics.

[9]  Bruce W. Turnbull,et al.  COMPARING TWO TREATMENTS WITH MULTIPLE COMPETING RISKS ENDPOINTS , 1999 .

[10]  Martin Schumacher,et al.  Simulating competing risks data in survival analysis , 2009, Statistics in medicine.

[11]  F. Kronenberg,et al.  Apolipoprotein B, fibrinogen, HDL cholesterol, and apolipoprotein(a) phenotypes predict coronary artery disease in hemodialysis patients. , 1997, Journal of the American Society of Nephrology : JASN.

[12]  R. Gill Censoring and stochastic integrals , 1980 .

[13]  M Schumacher,et al.  Sample size considerations for the evaluation of prognostic factors in survival analysis. , 2000, Statistics in medicine.

[14]  J M Lachin,et al.  Evaluation of sample size and power for analyses of survival with allowance for nonuniform patient entry, losses to follow-up, noncompliance, and stratification. , 1986, Biometrics.

[15]  Sylvie Chevret,et al.  Sample size formula for proportional hazards modelling of competing risks , 2004, Statistics in medicine.

[16]  P Royston,et al.  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 , 2006, Statistics in medicine.

[17]  R. Gray A Class of $K$-Sample Tests for Comparing the Cumulative Incidence of a Competing Risk , 1988 .

[18]  W. März,et al.  Rationale and design of a trial improving outcome of type 2 diabetics on hemodialysis , 1999 .

[19]  Martin Schumacher,et al.  Sample sizes for clinical trials with time-to-event endpoints and competing risks. , 2005, Contemporary clinical trials.

[20]  D. Schoenfeld The asymptotic properties of nonparametric tests for comparing survival distributions , 1981 .

[21]  J. Lachin Introduction to sample size determination and power analysis for clinical trials. , 1981, Controlled clinical trials.

[22]  R Porcher,et al.  Sample size calculations in the presence of competing risks , 2007, Statistics in medicine.

[23]  M. Kosorok,et al.  A Sample Size Formula for the Supremum Log‐Rank Statistic , 2005, Biometrics.

[24]  E. Lakatos,et al.  Sample sizes based on the log-rank statistic in complex clinical trials. , 1988, Biometrics.

[25]  Robert Gray,et al.  A Proportional Hazards Model for the Subdistribution of a Competing Risk , 1999 .

[26]  J. Fine,et al.  A competing risks analysis should report results on all cause-specific hazards and cumulative incidence functions. , 2013, Journal of clinical epidemiology.