Back to Search
Start Over
Beyond Chronological Age: A Multidimensional Approach to Survival Prediction in Older Adults.
- Source :
-
The journals of gerontology. Series A, Biological sciences and medical sciences [J Gerontol A Biol Sci Med Sci] 2023 Jan 26; Vol. 78 (1), pp. 158-166. - Publication Year :
- 2023
-
Abstract
- Background: There is a growing interest in generating precise predictions of survival to improve the assessment of health and life-improving interventions. We aimed to (a) test if observable characteristics may provide a survival prediction independent of chronological age; (b) identify the most relevant predictors of survival; and (c) build a metric of multidimensional age.<br />Methods: Data from 3 095 individuals aged ≥60 from the Swedish National Study on Aging and Care in Kungsholmen. Eighty-three variables covering 5 domains (diseases, risk factors, sociodemographics, functional status, and blood tests) were tested in penalized Cox regressions to predict 18-year mortality.<br />Results: The best prediction of mortality at different follow-ups (area under the receiver operating characteristic curves [AUROCs] 0.878-0.909) was obtained when 15 variables from all 5 domains were tested simultaneously in a penalized Cox regression. Significant prediction improvements were observed when chronological age was included as a covariate for 15- but not for 5- and 10-year survival. When comparing individual domains, we find that a combination of functional characteristics (ie, gait speed, cognition) gave the most accurate prediction, with estimates similar to chronological age for 5- (AUROC 0.836) and 10-year (AUROC 0.830) survival. Finally, we built a multidimensional measure of age by regressing the predicted mortality risk on chronological age, which displayed a stronger correlation with time to death (R = -0.760) than chronological age (R = -0.660) and predicted mortality better than widely used geriatric indices.<br />Conclusions: Combining easily accessible characteristics can help in building highly accurate survival models and multidimensional age metrics with potentially broad geriatric and biomedical applications.<br /> (© The Author(s) 2022. Published by Oxford University Press on behalf of The Gerontological Society of America.)
- Subjects :
- Aged
Humans
Risk Factors
Sweden epidemiology
Geriatric Assessment methods
Aging
Subjects
Details
- Language :
- English
- ISSN :
- 1758-535X
- Volume :
- 78
- Issue :
- 1
- Database :
- MEDLINE
- Journal :
- The journals of gerontology. Series A, Biological sciences and medical sciences
- Publication Type :
- Academic Journal
- Accession number :
- 36075209
- Full Text :
- https://doi.org/10.1093/gerona/glac186