Risk prediction models are useful for identifying kidney recipients at high risk of graft failure,
thus optimizing clinical care. Our objective was to systematically review the models that have …

Purpose Initial or single time point serum albumin levels have been shown to be important in
predicting the prognosis of peritoneal dialysis (PD) patients. However, we assume the …

Accurate models of clinical actions and their impacts on disease progression are critical for
estimating personalized optimal dynamic treatment regimes (DTRs) in medical/health …

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 …

Objective Precision medicine drug therapy seeks to maximize efficacy and minimize harm
for individual patients. This will be difficult if drug response and side effects are positively …

In the context of chronic diseases, patient's health evolution is often evaluated through the
study of longitudinal markers and major clinical events such as relapses or death. Dynamic …

In clinical practice, individuals are followed up to predict the outcome event of interest, and
their longitudinal measurements are collected on a regular or irregular basis. We aimed to …

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

Identification of patients at risk of kidney graft loss relies on early individual prediction of graft
failure. Data from 616 kidney transplant recipients with a follow‐up of at least one year were …

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 …