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Comparing survival functions with interval-censored data in the presence of an intermediate clinical event.

Authors
 Sohee Kim  ;  Jinheum Kim  ;  Chung Mo Nam 
Citation
 BMC MEDICAL RESEARCH METHODOLOGY, Vol.18 : 98, 2018 
Journal Title
 BMC MEDICAL RESEARCH METHODOLOGY 
Issue Date
2018
Keywords
Intermediate clinical event ; Interval-censored ; Length-biased ; Multiple imputation ; Time-to-event
Abstract
BACKGROUND: In the presence of an intermediate clinical event, the analysis of time-to-event survival data by conventional approaches, such as the log-rank test, can result in biased results due to the length-biased characteristics. METHODS: In the present study, we extend the studies of Finkelstein and Nam & Zelen to propose new methods for handling interval-censored data with an intermediate clinical event using multiple imputation. The proposed methods consider two types of weights in multiple imputation: 1) uniform weight and 2) the weighted weight methods. RESULTS: Extensive simulation studies were performed to compare the proposed tests with existing methods regarding type I error and power. Our simulation results demonstrate that for all scenarios, our proposed methods exhibit a superior performance compared with the stratified log-rank and the log-rank tests. Data from a randomized clinical study to test the efficacy of sorafenib/sunitinib vs. sunitinib/sorafenib to treat metastatic renal cell carcinoma were analyzed under the proposed methods to illustrate their performance on real data. CONCLUSIONS: In the absence of intensive iterations, our proposed methods show a superior performance compared with the stratified log-rank and the log-rank test regarding type I error and power.
Files in This Item:
T201803767.pdf Download
DOI
10.1186/s12874-018-0558-y
Appears in Collections:
1. College of Medicine (의과대학) > Dept. of Preventive Medicine and Public Health (예방의학교실) > 1. Journal Papers
Yonsei Authors
Nam, Chung Mo(남정모) ORCID logo https://orcid.org/0000-0003-0985-0928
URI
https://ir.ymlib.yonsei.ac.kr/handle/22282913/165283
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