Sample size determination for paired right-censored data based on the difference of Kaplan-Meier estimates

Sample size determination is essential to planning clinical trials. Jung (2008) established a sample size calculation formula for paired right-censored data based on the logrank test, which has been well-studied for comparing independent survival outcomes. An alternative to rank-based methods for independent right-censored data, advocated by Pepe and Fleming (1989), tests for differences between integrated weighted Kaplan-Meier estimates and is more sensitive to the magnitude of difference in survival times between groups. In this paper, we employ the concept of the Pepe-Fleming method to determine an adequate sample size by calculating differences between Kaplan-Meier estimators considering pair-wise correlation. We specify a positive stable frailty model for the joint distribution of paired survival times. We evaluate the performance of the proposed method by simulation studies and investigate the impacts of the accrual times, follow-up times, loss to follow-up rate, and sensitivity of power under misspecification of the model. The results show that ignoring the pair-wise correlation results in overestimating the required sample size. Furthermore, the proposed method is applied to two real-world studies, and the R code for sample size calculation is made available to users.

[1]  A. Patz,et al.  The ETDRS and Diabetes 2000. , 1991, Ophthalmology (Rochester, Minn.).

[2]  Zhiliang Ying,et al.  Nonparametric estimation of the gap time distributions for serial events with censored data , 1999 .

[3]  M S Pepe,et al.  Weighted Kaplan-Meier statistics: a class of distance tests for censored survival data. , 1989, Biometrics.

[4]  D. Harrington,et al.  Counting Processes and Survival Analysis , 1991 .

[5]  E. Gehan A GENERALIZED WILCOXON TEST FOR COMPARING ARBITRARILY SINGLY-CENSORED SAMPLES. , 1965, Biometrika.

[6]  P. Moran,et al.  Testing for correlation between non-negative variates. , 1967, Biometrika.

[7]  R. Prentice Linear rank tests with right censored data , 1978 .

[8]  Michael R. Kosorok,et al.  Sample‐size formula for clustered survival data using weighted log‐rank statistics , 2004 .

[9]  N. Mantel Evaluation of survival data and two new rank order statistics arising in its consideration. , 1966, Cancer chemotherapy reports.

[10]  Yunchan Chi,et al.  The simultaneous use of weighted logrank and weighted Kaplan–Meier statistics with clustered right‐censored data , 2010, Statistics in medicine.

[11]  Shyr Yu,et al.  Analyzing survival curves at a fixed point in time for paired and clustered right-censored data , 2011, Comput. Stat. Data Anal..

[12]  S Murray,et al.  Nonparametric Rank‐Based Methods for Group Sequential Monitoring of Paired Censored Survival Data , 2000, Biometrics.

[13]  J. D. Holt,et al.  Survival analyses in twin studies and matched pair experiments , 1974 .

[14]  Min-Hsiao Tsai,et al.  SOME VERSATILE TESTS BASED ON THE SIMULTANEOUS USE OF WEIGHTED LOGRANK AND WEIGHTED KAPLAN-MEIER STATISTICS , 2001 .

[15]  Sin-Ho Jung,et al.  Sample size calculation for the weighted rank statistics with paired survival data , 2008, Statistics in medicine.

[16]  P. Hougaard A class of multivanate failure time distributions , 1986 .

[17]  J. Shih,et al.  A goodness-of-fit test for association in a bivariate survival model , 1998 .

[18]  Wayne Nelson Theory and applications of hazard plotting for censored failure data , 2000 .

[19]  E. Kaplan,et al.  Nonparametric Estimation from Incomplete Observations , 1958 .

[20]  Susan Murray,et al.  Simultaneous Group Sequential Analysis of Rank‐Based and Weighted Kaplan–Meier Tests for Paired Censored Survival Data , 2005, Biometrics.

[21]  S Murray,et al.  Using Weighted Kaplan‐Meier Statistics in Nonparametric Comparisons of Paired Censored Survival Outcomes , 2001, Biometrics.

[22]  Sin-Ho Jung Rank Tests for Matched Survival Data , 1999, Lifetime data analysis.

[23]  D. Clayton A model for association in bivariate life tables and its application in epidemiological studies of familial tendency in chronic disease incidence , 1978 .