Background— Prediction models are developed to aid health care providers in estimating the
probability or risk that a specific disease or condition is present (diagnostic models) or that …

Objective To review and appraise the validity and usefulness of published and preprint reports
of prediction models for prognosis of patients with covid-19, and for detecting people in …

In most situations, simple techniques for handling missing data (such as complete case
analysis, overall mean imputation, and the missing-indicator method) produce biased results, …

The TRIPOD (Transparent Reporting of a multivariable prediction model for Individual
Prognosis Or Diagnosis) Statement includes a 22-item checklist, which aims to improve the …

Background Previous studies have relied predominantly on the body-mass index (BMI, the
weight in kilograms divided by the square of the height in meters) to assess the association of …

Doctors have little specific research to draw on when predicting outcome. In this first article
in a series Karel Moons and colleagues explain why research into prognosis is important …

… Royston P, Moons KGM, Altman DG, Vergouwe Y. Prognosis and prognostic research:
developing a prognostic model. BMJ 2009;338:b604. … Moons KGM, Royston P, Vergouwe Y …

Carl Moons and colleagues provide a checklist and background explanation for critically
appraising and extracting data from systematic reviews of prognostic and diagnostic …

Clinical prediction models combine multiple predictors to estimate risk for the presence of a
particular condition (diagnostic models) or the occurrence of a certain event in the future (…

In this article, the third in the PROGRESS series on prognostic factor research, Sara Schroter
and colleagues review how prognostic models are developed and validated, and then …