Long-term prediction of major coronary or ischaemic stroke event in a low-incidence Southern European population: model development and evaluation of clinical utility
- PMID: 24227872
- PMCID: PMC3831155
- DOI: 10.1136/bmjopen-2013-003630
Long-term prediction of major coronary or ischaemic stroke event in a low-incidence Southern European population: model development and evaluation of clinical utility
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.
Keywords: Preventive Medicine.
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