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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. Copyright © 2011 John Wiley & Sons, Ltd.

Aim: To study the effects of drinking 0.5 L of two sodium-rich bicarbonated mineral waters (BMW-1 and 2), with a standard meal, on postprandial insulin and glucose changes. And to determine, if the effects vary depending on insulin resistance, measured by homeostasis model assessment (HOMA). Methods: In a 3-way randomized crossover study, 18 healthy postmenopausal women consumed two sodiumrich BMWs and a low-mineral water (LMW) with a standard fat-rich meal. Fasting and postprandial blood samples were taken at 30, 60 and 120 min. Serum glucose, insulin, cholesterol and triacylglycerols were determined. Insulin resistance was estimated by HOMA and insulin sensitivity was calculated by quantitative insulin sensitivity check index (QUICKY). Results: Glucose levels did not change. HOMA and QUICKY values were highly inversely correlated (r = -1,000; p < 0.0001). Insulin concentrations showed a significant time effect (p < 0.0001) and a significant water x time interaction (p < 0.021). At 120 min insulin levels with BMW-1 were significantly lower than with LMW (p = 0.022). Postprandial insulin concentrations showed significantly different patterns of mineral water intake depending on HOMA n-tiles (p = 0.016). Conclusion: Results suggests an increase in insulin sensitivity after BMWs consumption. This effect is more marked in the women, who have higher HOMA values. These waters should be considered part of a healthy diet in order to prevent insulin resistance and cardiovascular disease.