Bayesian assessment of times to diagnosis in breast cancer screening

Abstract

Breast cancer is one of the diseases with the most profound impact on health in developed countries and mammography is the most popular method for detecting breast cancer at a very early stage. This paper focuses on the waiting period from a positive mammogram until a confirmatory diagnosis is carried out in hospital. Generalized linear mixed models are used to perform the statistical analysis, always within the Bayesian reasoning. Markov chain Monte Carlo algorithms are applied for estimation by simulating the posterior distribution of the parameters and hyperparameters of the model through the free software WinBUGS.

Keywords:

• Bayesian statistics
• breast cancer screening program
• generalized linear mixed models
• Markov Chain Monte Carlo

Acknowledgements

This research is partially supported by the Ministerio de Educació y Ciencia, under grant MTM2007-61554 and the Conselleria de Sanitat de la Generalitat Valenciana. The authors would like to thank the working group of the Programa de Prevenció del Cáncer de Mama de la Comunidad Valenciana for their collaboration. We also acknowledge the constructive comments and suggestions on the original version of this paper by two anonymous referees.