Background Before considering whether to use a multivariable (diagnostic or prognostic)
prediction model, it is essential that its performance be evaluated in data that were not used …

Missing data are ubiquitous in clinical epidemiological research. Individuals with missing
data may differ from those with no missing data in terms of the outcome of interest and …

Multivariate imputation by chained equations (MICE) is commonly used for imputing missing
data in epidemiologic research. The “true” imputation model may contain nonlinearities …

Routinely collected health data, obtained for administrative and clinical purposes without
specific a priori research goals, are increasingly used for research. The rapid evolution and …

Background—This study sought to evaluate whether risks of diabetes mellitus and
cardiovascular disease are elevated across a range of organ-specific and multisystem …

Collaborative study designs (CSDs) that combine individual-level data from multiple
independent contributing studies (ICSs) are becoming much more common due to their …

Background Current treatment guidelines do not provide recommendations to support the
selection of treatment for most people with type 2 diabetes. We aimed to develop and …

Drug use in medicine is based on a balance between expected benefits (already
investigated before marketing authorization) and possible risks (ie, adverse effects), which …

The goal of cardiovascular disease (CVD) research using linked bespoke studies and
electronic health records (CALIBER) is to provide evidence to inform health care and public …

Context Serum total bilirubin levels in healthy patients reflect genetic and environmental
factors that could influence the risk of developing respiratory disease. Objective To examine …