Statistical analysis of censored endpoints under the Cox proportional hazard model for evaluation of targeted drug products under the enrichment design
Date Issued
2015
Date
2015
Author(s)
Lee, Kuan-Ting
Abstract
In traditional clinical trials, inclusion and exclusion criteria are considered based on some clinical endpoints, the genetic or genomic variability of the trial participants are not totally utilized in the criteria. After the Human Genome Project is completed, many molecules underlying disease can be identified, it is possible to develop a targeted molecular therapy. However, the accuracy of diagnostic devices for identification of such molecular targets is usually not perfect. Some patients with positive diagnosis result is actually might not have the specific molecular targets. As a result, the treatment effect may be underestimated in the patient population truly with the molecular target. In order to resolve this issue, we propose a method based on the mixture Cox’s proportional model for the k latent classes (Eng K.H. and Hanlon B.M., 2014) and under the enrichment design. We develop inferential procedures for the treatment effects of the targeted drug based on the censored endpoints in the patients truly with the molecular targets which also incorporates the inaccuracy of the diagnostic device for detection of the molecular targets on the inference of the treatment effects. We propose using the EM algorithm in conjunction with the bootstrap technique for estimation of hazard ratio and its variance. Though the simulation study, we empirically investigate the performance of the proposed methods and to compare with the current method. The numerical examples illustrate the proposed procedures.
Subjects
Targeted clinical trials
Enrichment design
censored data
EM algorithm
Cox proportion hazard model
SDGs
Type
thesis
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