Modelling of time to event breast cancer data using accelerated failure time (Aft) in south India women.

Dayal, P.L.; Alexander, L.T.; Ponnuraja, C.; Rama, R.; Venkatesan, P.

Global Research Analysis; 2013; 2; 192-194.

Abstract: Most of the studies have been widely studied between breast cancer and risk factor using the classical way of statistical methods. This paper aims to implement a class of flexible parametric survival models through accelerated failure time models for identifying risk factors for breast cancer time to death among South India women. This study also attempts to explore the survival experience of breast cancer patients. Since the death due to severity of the stages varies with age; the age is broadly classified into two groups <50 years & 50 years. The survival experiences between these age groups are presented using Kaplan-Meier survival curves and there is no significant difference between groups. However, the stages differ significantly in each group. The accelerated failure time (AFT) models using Exponential, Weibull, Gamma, Log logistic and lognormal were explored and compared by using the AIC and deviance. The Gamma and log normal models produced similar results.

Keywords: Survival analysis; AFT models; Kaplan-Meier, log rank test.

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