In his song ‘Envelhecer’ (‘Aging’), Arnaldo Antunes states that “the most modern thing there is in this life is to grow old”.1 In this piece, he reframes aging not only as an inevitable biological process, but also as a privilege. His message resonates with ongoing scientific efforts to rethink approaches to ageing and the needs of older populations. In this context, advancing efforts to understand and improve health outcomes among older adults is imperative to ensure that ageing is recognised as the privilege it truly is.
Building on this perspective, Ganjali et al evaluated the performance of cardiovascular disease (CVD) risk prediction models, originally designed for middle-aged adults, and applied them to a cohort of community-dwelling individuals aged 70 and older.2 Using data from the Aspirin in Reducing Events in the Elderly (ASPREE) trial and its observational extension, ASPREE-XT, they assessed the model’s applicability in an older population and explored enhancements to improve predictive accuracy. In this work, the authors assessed the performance of original, recalibrated and updated models using discrimination, calibration and decision curve analysis and tested added predictors such as serum creatinine, depression and socioeconomic status index to determine whether these variables enhanced the models’ ability to accurately predict CVD risk in older adults. The CVD prediction models used by Ganjali et al were ACC/AHA, 2008 Framingham, GloboRisk, the National Vascular Disease Prevention Alliance (NVDPA), Predict1 and SCORE-OP, each with distinct origins, populations and features. In terms of representation, the ACC/AHA model (USA, 2013) evaluated adults aged 40–79; the 2008 Framingham …
