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Testing for the presence of cured patients: a simulation study
Y Peng1, K B Dear, K C Carriere
1Department of Mathematics and Statistics, Memorial University of Newfoundland, St. John's, Newfoundland A1C 5S7, Canada. ypeng@math.mun.ca
Statistics in Medicine
|June 15, 2001
Summary
Determining cured patients in clinical trials is challenging. This study examines the likelihood ratio test
Area of Science:
- Biostatistics
- Clinical Trials
- Survival Analysis
Background:
- Identifying cured patients in long-term clinical trials presents a significant challenge.
- The likelihood ratio test (LRT) is a statistical tool used for this purpose, often within mixture models.
- Standard asymptotic theory for the LRT's null distribution has limitations due to boundary condition violations.
Purpose of the Study:
- To investigate the validity of a proposed asymptotic null distribution for the likelihood ratio test.
- To assess the applicability of this distribution in Weibull and log-normal mixture models.
- To identify conditions under which the LRT's null distribution may deviate from the proposed approximation.
Main Methods:
- A simulation study was conducted to examine the proposed asymptotic null distribution of the likelihood ratio test.
- The study evaluated the LRT's performance in gamma, Weibull, and log-normal mixture models.
- Various censoring rates and hazard rates were simulated to assess distribution deviations.
Main Results:
- The proposed asymptotic null distribution approximates the LRT's null distribution in Weibull and log-normal models under moderate to low censoring rates.
- Deviations from the proposed distribution were observed under moderate sample sizes, especially with low censoring or high hazard rates.
- The study confirmed the presence of cured patients in a real-world leukemia clinical trial.
Conclusions:
- Caution is advised when using the proposed LRT null distribution with moderate sample sizes, low censoring, or high hazard rates.
- The findings provide insights into the reliability of the likelihood ratio test for identifying cured patients in mixture models.
- The study successfully applied the LRT to confirm cured patients in a leukemia study, demonstrating practical utility.
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