How do cardiovascular risk prediction equations developed among 30–74 year olds perform in older age groups? A validation study in 125 000 people aged 75–89 years

BACKGROUND: Cardiovascular disease (CVD) risk prediction equations are being used to guide risk management among increasingly older individuals. We examined the performance of recent equations, derived from a 2006 cohort including almost all New Zealanders aged 30-74 years, among older people. METHODS: All New Zealanders aged 75-89 years in contact with state-funded health services in 2006 without prior CVD or heart failure and with complete predictor data were identified by anonymised individual-level linkage of eight national administrative health datasets. Baseline 5-year CVD risk was estimated using sex-specific New Zealand risk equations, and CVD hospitalisations or deaths occurring between 2007 and 2011 inclusive were ascertained. Performance was assessed with calibration plots and standard metrics. RESULTS: Among 124 358 New Zealanders aged 75-89 years old, 30 152 CVD events were recorded during follow-up. Sex-specific equations derived from 30-74 year olds slightly underestimated CVD risk among women and slightly overestimated risk among men aged 75-89 years. Discrimination metrics were poor in both sexes and the risk equations explained only 9.4% of the variation in time to CVD event among women and 6.0% for men. In the 5-year age bands, progressively worsening underprediction in women, overprediction in men and poorer performance metrics were observed with increasing age. CONCLUSION: Entire-population CVD risk equations developed among 30-74 year olds do not perform well among older people. Existing risk algorithms developed from primarily middle-aged or early-retirement cohorts should be used with caution in those aged ≥75 years until carefully validated in narrow age bands to avoid masking poorer performance in older age groups

Cohort · Cohort study · Disease · Environmental health · Generalized estimating equation · Population · Statistics · Cardiovascular Health and Risk Factors · Demography · Health Promotion and Cardiovascular Prevention · Internal Medicine · Lipoproteins and Cardiovascular Health · Medicine · Gerontology