Prolonging survival in good health is a fundamental societal goal. However, the leading determinants of disability-free survival in healthy older people have not been well established. Data from ASPREE, a bi-national placebo-controlled trial of aspirin with 4.7 years median follow-up, was analysed. At enrolment, participants were healthy and without prior cardiovascular events, dementia or persistent physical disability. Disability-free survival outcome was defined as absence of dementia, persistent disability or death. Selection of potential predictors from amongst 25 biomedical, psychosocial and lifestyle variables including recognized geriatric risk factors, utilizing a machine-learning approach. Separate models were developed for men and women. The selected predictors were evaluated in a multivariable Cox proportional hazards model and validated internally by bootstrapping. We included 19,114 Australian and US participants aged ≥65 years (median 74 years, IQR 71.6–77.7). Common predictors of a worse prognosis in both sexes included higher age, lower Modified Mini-Mental State Examination score, lower gait speed, lower grip strength and abnormal (low or elevated) body mass index. Additional risk factors for men included current smoking, and abnormal eGFR. In women, diabetes and depression were additional predictors. The biased-corrected areas under the receiver operating characteristic curves for the final prognostic models at 5 years were 0.72 for men and 0.75 for women. Final models showed good calibration between the observed and predicted risks. We developed a prediction model in which age, cognitive function and gait speed were the strongest predictors of disability-free survival in healthy older people. Trial registration Clinicaltrials.gov (NCT01038583).
|Original language||English (US)|
|Number of pages||15|
|State||Published - Jun 1 2022|
Bibliographical noteFunding Information:
We thank the ASPREE trial staff, participants and general practitioners. ASPREE investigators and committees International Steering Committee: John McNeil (Chair and Principal Investigator), Anne Murray (Co-Chair and Co-Principal Investigator), Lawrie Beilin, Andrew Chan, Jamehl Demons, Michael Ernst, Sara Espinoza, Matthew Goetz, Colin Johnston, Brenda Kirpach, Danny Liew, Karen Margolis, Frank Meyskens, Mark Nelson, Chris Reid, Raj Shah, Elsdon Storey, Andrew Tonkin, Rory Wolfe, Robyn Woods, John Zalcberg International End Point Adjudication Committees: Mark Nelson (Chair), Diane Ives (Co-Chair), Michael Berk, Wendy Bernstein, Donna Brauer, Christine Burns, Trevor Chong, Geoff Cloud, Jamehl Demons, Geoffrey Donnan, Charles Eaton, Paul Fitzgerald, Peter Gibbs, Andrew Haydon, Michael Jelinek, Finlay Macrae, Suzanne Mahady, Mobin Malik, Karen Margolis, Catriona McLean, Anne Murray, Anne Newman, Luz Rodriguez, Suzanne Satterfield (deceased), Raj Shah, Elsdon Storey, Jeanne Tie, Andrew Tonkin, Gijsberta van Londen, Stephanie Ward, Jeff Williamson, Erica Wood, John Zalcberg Data and Safety Monitoring Board: Jay Mohr (Chair).
Open Access funding enabled and organized by CAUL and its Member Institutions This study was financially supported by the National Institute on Aging and the National Cancer Institute at the National Institutes of Health (grant numbers U01AG029824, U19AG062682); the National Health and Medical Research Council of Australia (grant numbers 334047, 1127060); Monash University; and the Victorian Cancer Agency. J.N. is recipient of a fellowship by the Deutsche Forschungsgemeinschaft (NE 2165/1-1). C.M.R. is supported through a NHMRC Principal Research Fellowship (APP 1136372). JMCN is supported through an NHMRC Leadership Fellowship (IG 1173690).
© 2022, The Author(s).
- Public Health
- Risk prediction