A. Bauer, G. Zauner, C. Urach:

"Evaluation of Risk Factors for Parametrization of Cancer Models";

Simulation Notes Europe,25(2015), 3-4; S. 141 - 144.

Abstract. Cancer is the second most cause of death in

Austria and around 38000 people are diagnosed with

cancer each year [1]. The goal of this paper is to analyze

methods for evaluation of risk factors in order to parametrize

a micro simulation model for cancer prevalence.

The focus of this paper is on modeling the survival time.

This is done by the methods of survival analysis and

model selection. Firstly, the survival function is estimated

by the Kaplan-Meier estimate. Afterwards, a Cox proportional

hazards regression is performed with all possible

sets of parameters. These models are tested by twos

with the likelihood ratio test in order to compare them.

Another approach is the so-called Lasso method. This

method puts a constraint on the sum of the absolute

values of the regression coefficients and in most cases

forces some of the coefficients to go to zero. The Akaike

Information Criterion is also applied. All three methods

are compared and the parameters which are supported,

at least to a certain extent, by all of them are included in

the estimation of the survival time of the prevalence

model.

http://dx.doi.org/10.11128/sne.25.sn.10304

http://publik.tuwien.ac.at/files/publik_255547.pdf

Erstellt aus der Publikationsdatenbank der Technischen Universität Wien.