Medical Risk Prediction Models: With Ties to Machine Learning is a hands-on book for
clinicians, epidemiologists, and professional statisticians who need to make or evaluate a …

Background Prostate cancer is a very prevalent disease in men. Patients are monitored
regularly during and after treatment with repeated assessment of prostate-specific antigen …

Background Informing kidney transplant recipients of their prognosis and disease
progression is of primary importance in a patient-centred vision of care. By participating in …

Background Several models have been proposed to predict kidney graft failure in adult
recipients but none in younger recipients. Our objective was to propose a dynamic …

Purpose The CHHiP trial assessed moderately hypofractionated radiation therapy in
localized prostate cancer. We utilized longitudinal prostate-specific antigen (PSA) …

Background. In kidney transplantation, dynamic prediction of patient and kidney graft
survival (DynPG) may help to promote therapeutic alliance by delivering personalized …

Aims For type 2 diabetes persons, we assessed the association between renal function
decline and heart failure hospitalisation (HFH) and validated dynamic HFH predictions …

In kidney transplantation, dynamic predictions of graft survival may be obtained from joint
modelling of longitudinal and survival data for which a common assumption is that random …

This thesis aims to develop and validate dynamic predictive joint models (JMs) to
characterise the prognosis of patients with localised prostate cancer who are treated with …

Background. Time-to-event dynamic predictions are de ned as the probability to survive until
a de ned time horizon given being event-free at landmark times and given available …