Hennerfeind, Andrea; Held, Leonhard
A Bayesian geoadditive relative survival analysis of registry data on breast cancer mortality.
Collaborative Research Center 386, Discussion Paper 515
In this paper we develop a so called relative survival analysis, that is used to model the excess risk of a certain subpopulation relative to the natural mortality risk, i.e. the base risk that is present in the whole population. Such models are typically used in the area of clinical studies, that aim at identifying prognostic factors for disease specific mortality with data on specific causes of death being not available. Our work has been motivated by continuous-time spatially referenced survival data on breast cancer where causes of death are not known. This paper forms an extension of the analyses presented in Sauleau et al. (2007), where those data are analysed via a geoadditive, semiparametric approach, however without allowance to incorporate natural mortality. The usefulness of this relative survival approach is supported by means of a simulated data set.