A Bayesian analysis of relative cancer survival with geoadditive models

作者：Hennerfeind Andrea; Held Leonhard^*; Sauleau Erik A

来源：Statistical Modelling, 2008, 8(2): 117-139.

DOI：10.1177/1471082X0800800201

• Bayesian penalized splines
• breast cancer
• Gaussian Markov random fields
• MCMC
• relative survival
• structured hazard regression

In this paper, we develop a so-called relative survival analysis that is used to model the excess risk of a certain sub-population relative to the natural mortality risk which is present in the whole population. Such models are typically used in population-based studies that aim at identifying prognostic factors for disease-specific mortality, with data on specific causes of death not being available. This paper combines relative survival with Bayesian geoadditive regression allowing for a flexible semiparametric analysis. Our work has been motivated by continuous-time spatially referenced survival data on breast cancer where causes of death are not known. A detailed analysis of these data is given. The usefulness of the approach is further illustrated by means of a simulated data set.

• 出版日期2008-7