Clinical prediction models are increasingly used to complement clinical reasoning and decision-making in modern medicine, in general, and in the cardiovascular domain, in particular. To these ends, developed models first and foremost need to provide accurate and (internally and externally) validated estimates of probabilities of specific health conditions or outcomes in the targeted individuals. Subsequently, the adoption of such models by professionals must guide their decision-making, and improve patient outcomes and the cost-effectiveness of care. In the first paper of this series of two companion papers, issues relating to prediction model development, their internal validation, and estimating the added value of a new (bio)marker to existing predictors were discussed. In this second paper, an overview is provided of the consecutive steps for the assessment of the model's predictive performance in new individuals (external validation studies), how to adjust or update existing models to local circumstances or with new predictors, and how to investigate the impact of the uptake of prediction models on clinical decision-making and patient outcomes (impact studies). Each step is illustrated with empirical examples from the cardiovascular field.
AD - Julius Centre for Health Sciences and Primary Care, UMC Utrecht, PO Box 85500, 3508 GA Utrecht, The Netherlands; k.g.m.moons@umcutrecht.nl. AN - 22397946 BT - Heart ET - 2012/03/09 LA - eng M1 - 9 N1 - Moons, Karel G MKengne, Andre PascalGrobbee, Diederick ERoyston, PatrickVergouwe, YvonneAltman, Douglas GWoodward, MarkEnglandHeart (British Cardiac Society)Heart. 2012 May;98(9):691-8. Epub 2012 Mar 7. N2 -Clinical prediction models are increasingly used to complement clinical reasoning and decision-making in modern medicine, in general, and in the cardiovascular domain, in particular. To these ends, developed models first and foremost need to provide accurate and (internally and externally) validated estimates of probabilities of specific health conditions or outcomes in the targeted individuals. Subsequently, the adoption of such models by professionals must guide their decision-making, and improve patient outcomes and the cost-effectiveness of care. In the first paper of this series of two companion papers, issues relating to prediction model development, their internal validation, and estimating the added value of a new (bio)marker to existing predictors were discussed. In this second paper, an overview is provided of the consecutive steps for the assessment of the model's predictive performance in new individuals (external validation studies), how to adjust or update existing models to local circumstances or with new predictors, and how to investigate the impact of the uptake of prediction models on clinical decision-making and patient outcomes (impact studies). Each step is illustrated with empirical examples from the cardiovascular field.
PY - 2012 SN - 1468-201X (Electronic)1355-6037 (Linking) SP - 691 EP - 8 T2 - Heart TI - Risk prediction models: II. External validation, model updating, and impact assessment VL - 98 ER -