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• W2894951751 abstract "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.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.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.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." @default.
• W2894951751 created "2018-10-12" @default.
• W2894951751 creator A5016437737 @default.
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• W2894951751 date "2018-10-01" @default.
• W2894951751 modified "2023-10-08" @default.
• W2894951751 title "Comparing survival functions with interval-censored data in the presence of an intermediate clinical event" @default.
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• W2894951751 doi "https://doi.org/10.1186/s12874-018-0558-y" @default.
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• W2894951751 hasPublicationYear "2018" @default.
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