title: Prognostic models in the clinical arena.
abstract: Making a prognosis is to predict the course of a disease and estimate the probability (or risk) of the appearance of a given outcome in relationship to clinical or non-clinical characteristics. Prognostic assessment is usually modelled by multivariable mathematic equations (prognostic models). In this article we describe what a prognostic model is, how to build a good one, why and how it is important to evaluate its generalizability and accuracy by means of discrimination, calibration and reclassification.
authors.affiliation: CNR-IBIM, Clinical Epidemiology and Physiopathology of Renal Diseases and Hypertension, Reggio Calabria, Italy. davide.bolignano@gmail.com
authors.forename: Davide
authors.initials: D
authors.lastname: Bolignano
authors.forename: Francesco
authors.initials: F
authors.lastname: Mattace-Raso
authors.forename: Claudia
authors.initials: C
authors.lastname: Torino
authors.forename: Graziella
authors.initials: G
authors.lastname: D'Arrigo
authors.forename: Samar
authors.initials: S
authors.lastname: Abd ElHafeez
authors.forename: Fabio
authors.initials: F
authors.lastname: Provenzano
authors.forename: Carmine
authors.initials: C
authors.lastname: Zoccali
authors.forename: Giovanni
authors.initials: G
authors.lastname: Tripepi
mesh_terms: D002138:Calibration; D006801:Humans; D015233:Models, Statistical; D011336:Probability; D011379:Prognosis; D012306:Risk