In this thesis statistical methods are developed to incorporate external information into existing risk prediction tools. Statistical concepts motivated by practical applications are introduced, which update the Prostate Cancer Prevention Trial Risk Calculator by two genetic markers, detailed family history and single nucleotide polymorphisms. Both updates are available online for physician and patient use as well as for research and validation purposes. In addition, several methods in this updating context are compared by extensive synthetic and data-based simulations.
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In this thesis statistical methods are developed to incorporate external information into existing risk prediction tools. Statistical concepts motivated by practical applications are introduced, which update the Prostate Cancer Prevention Trial Risk Calculator by two genetic markers, detailed family history and single nucleotide polymorphisms. Both updates are available online for physician and patient use as well as for research and validation purposes. In addition, several methods in this upda...
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