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Impact of unequal censoring on the comparison of survival curves

Abstract Number:

3327 

Submission Type:

Contributed Abstract 

Contributed Abstract Type:

Speed 

Participants:

Hyejeong Jang (1), Dipenkumar Modi (2), Seongho Kim (1)

Institutions:

(1) Wayne State University, Detroit, MI, (2) Karmanos Cancer Institute, Detroit, MI

Co-Author(s):

Dipenkumar Modi  
Karmanos Cancer Institute
Seongho Kim  
Wayne State University

First Author:

Hyejeong Jang  
Wayne State University

Presenting Author:

Hyejeong Jang  
Wayne State University

Abstract Text:

We investigate the impact of unequal censorings on the comparison of survival distributions by evaluating seven statistical tests: log-rank (LR), Gehan-Breslow generalized Wilcoxon (GB), Tarone-Ware (TW), Peto-Peto (PP), modified Peto-Peto (mPP) tests, a combined test using LR and TW methods, and an all-combined test. Through 1,000 simulations, we evaluate the performance of these in comparing two survival curves, considering the size and power of the tests across four types of censoring: overall, early, middle, and late censoring periods. We explore different scenarios with sample sizes of 20 and 50 for each group and varying levels of censoring (no censoring, 10%, and 25%). Additionally, we assess the proportional hazard assumption is also evaluated during the simulations. Regarding overall censoring, both LR and all-combined tests demonstrated the highest power. Early censoring appeared to minimally impact the size and power of all seven tests. However, LR and combined tests exhibited greater power overall, while GB showed the least power in the middle censoring scenario. In cases of late censoring, the all- combined tests displayed the highest power.

Keywords:

Log-rank test |Gehan-Breslow generalized Wilcoxon test|Tarone-Ware test|Peto-Peto test|Modified Peto-Peto test|Survival analysis

Sponsors:

Biometrics Section

Tracks:

Survival Analysis

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