OBJECTIVE: To develop a long-term prediction model of first major cardiovascular event and to assess its clinical utility in a low-incidence European population. SETTING: Four independent population-based cohorts enrolled between 1986 and 1993 in Northern Italy. PARTICIPANTS AND METHODS: N=5247 35-year-old to 69-year-old men and women free of cardiovascular disease at baseline. Absolute 20-year risk of first fatal or non-fatal coronary or ischaemic stroke event (monitoring trends and determinants in cardiovascular disease (MONICA) validated) was estimated from gender-specific Cox models. MAIN OUTCOME MEASURES: Model discrimination (area under the receiver operating characteristic (ROC)-curve, AUC). 'High-risk' subjects were identified based on several threshold values for the 20-year predicted risk. Clinical utility was defined in terms of fraction of missed events (events among those considered at low-risk) and unnecessary treatment (false:true positive ratio). A net benefit curve was also provided. RESULTS: Kaplan-Meier 20-year risk was 16.1% in men (315 events) and 6.1% in women (123 events). Model discrimination (AUC=0.737 in men, 0.801 in women) did not change significantly as compared to 10-year prediction time interval. In men, with respect to risk stratification based on the number of risk factors, a 20% predicted risk cut-off would miss less events (36% vs 50%) and reduce unnecessary treatment (false:true positive ratio 2.2 vs 3.0); the net benefit was higher over the whole range of threshold values. Similar considerations hold for women. CONCLUSIONS: Long-term prediction has good discrimination ability and is clinically useful for risk stratification in primary prevention. A clinical utility analysis is recommended to identify the optimal stratification according to different public health goals.

Long-term prediction of major coronary or ischaemic stroke event in a low-incidence Southern European population: model development and evaluation of clinical utility.

VERONESI, GIOVANNI;GIANFAGNA, FRANCESCO;FERRARIO, MARCO MARIO ANGELO
2013-01-01

Abstract

OBJECTIVE: To develop a long-term prediction model of first major cardiovascular event and to assess its clinical utility in a low-incidence European population. SETTING: Four independent population-based cohorts enrolled between 1986 and 1993 in Northern Italy. PARTICIPANTS AND METHODS: N=5247 35-year-old to 69-year-old men and women free of cardiovascular disease at baseline. Absolute 20-year risk of first fatal or non-fatal coronary or ischaemic stroke event (monitoring trends and determinants in cardiovascular disease (MONICA) validated) was estimated from gender-specific Cox models. MAIN OUTCOME MEASURES: Model discrimination (area under the receiver operating characteristic (ROC)-curve, AUC). 'High-risk' subjects were identified based on several threshold values for the 20-year predicted risk. Clinical utility was defined in terms of fraction of missed events (events among those considered at low-risk) and unnecessary treatment (false:true positive ratio). A net benefit curve was also provided. RESULTS: Kaplan-Meier 20-year risk was 16.1% in men (315 events) and 6.1% in women (123 events). Model discrimination (AUC=0.737 in men, 0.801 in women) did not change significantly as compared to 10-year prediction time interval. In men, with respect to risk stratification based on the number of risk factors, a 20% predicted risk cut-off would miss less events (36% vs 50%) and reduce unnecessary treatment (false:true positive ratio 2.2 vs 3.0); the net benefit was higher over the whole range of threshold values. Similar considerations hold for women. CONCLUSIONS: Long-term prediction has good discrimination ability and is clinically useful for risk stratification in primary prevention. A clinical utility analysis is recommended to identify the optimal stratification according to different public health goals.
2013
http://bmjopen.bmj.com/content/3/11/e003630.long
Epidemiology; Prevention; cardiovascular risk; Mathematical models; prediction metrics; cost estimation; Discrimination; Stroke; Public Health
Veronesi, Giovanni; Gianfagna, Francesco; Chambless, L. E.; Giampaoli, S.; Mancia, G.; Cesana, G.; Ferrario, MARCO MARIO ANGELO
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11383/1906521
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