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. Issue 6 (6th March 2020)

• Record Type: Journal Article
• Authors: Mehta, Suneela; Jackson, Rod; Poppe, Katrina; Kerr, Andrew J; Pylypchuk, Romana; Wells, Sue
• Is Part Of: Journal of epidemiology and community health. Volume 74:Issue 6(2020)
• Page Start: 527
• Page End: 533
• Publication Date: 2020-03-06
• Subjects: cardiovascular disease -- elderly -- prevention -- record linkage; Public health -- Periodicals; Epidemiology -- Periodicals; 614.4
• DOI: 10.1136/jech-2019-213466
• Languages: English
• ISSNs: 0143-005X

Abstract

Abstract : 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.