Parametric Estimation of the Cure Fraction Based on BCH Model Using Left-Censored Data with Covariates

Bader Aljawadi, Mohd Rizam A. Bakar, Noor Akma Ibrahim, Habshah Midi

Abstract


Medical investigations nowadays allow the incorporation of cure individuals in the analysis, especially for chronic diseases such as cancer. Therefore, survival models that incorporate the cured patients in the analysis are called cure rate models.  In this paper, we propose an analytical approach for parametric estimation of the cure fraction in cancer clinical trials based on the bounded cumulative hazard (BCH) model with covariates involved in the data set. The analysis is constructed by means of the exponential distribution in the case of left censoring and within the framework of the expectation maximization (EM) algorithm. The analysis provided an analytical solution for the estimation equations of the cure rate parameter.


Full Text: PDF DOI: 10.5539/mas.v5n3p103

Creative Commons License
This work is licensed under a Creative Commons Attribution 3.0 License.

Modern Applied Science   ISSN 1913-1844 (Print)   ISSN 1913-1852 (Online)

Copyright © Canadian Center of Science and Education

To make sure that you can receive messages from us, please add the 'ccsenet.org' domain to your e-mail 'safe list'. If you do not receive e-mail in your 'inbox', check your 'bulk mail' or 'junk mail' folders.