Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

    We have a manual that explains all the features 

Record number 426818
Title A framework for quantifying net benefits of alternative prognostic models
Author(s) Rapsomaniki, E.; White, I.R.; Wood, A.M.; Thompson, S.G.; Feskens, E.J.M.; Kromhout, D.
Source Statistics in Medicine 31 (2012)2. - ISSN 0277-6715 - p. 114 - 130.
DOI http://dx.doi.org/10.1002/sim.4362
Department(s) Chair Nutrition and Disease
VLAG
Publication type Refereed Article in a scientific journal
Publication year 2012
Keyword(s) coronary heart-disease - cardiovascular-disease - risk score - predictive ability - roc curve - reclassification - statins - cohort - metaanalysis - validation
Abstract New prognostic models are traditionally evaluated using measures of discrimination and risk reclassification, but these do not take full account of the clinical and health economic context. We propose a framework for comparing prognostic models by quantifying the public health impact (net benefit) of the treatment decisions they support, assuming a set of predetermined clinical treatment guidelines. The change in net benefit is more clinically interpretable than changes in traditional measures and can be used in full health economic evaluations of prognostic models used for screening and allocating risk reduction interventions. We extend previous work in this area by quantifying net benefits in life years, thus linking prognostic performance to health economic measures; by taking full account of the occurrence of events over time; and by considering estimation and cross-validation in a multiple-study setting. The method is illustrated in the context of cardiovascular disease risk prediction using an individual participant data meta-analysis. We estimate the number of cardiovascular-disease-free life years gained when statin treatment is allocated based on a risk prediction model with five established risk factors instead of a model with just age, gender and region. We explore methodological issues associated with the multistudy design and show that cost-effectiveness comparisons based on the proposed methodology are robust against a range of modelling assumptions, including adjusting for competing risks
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