Development and Validation of a 10-Year Mortality Prediction Model: Meta-Analysis of Individual Participant Data From Five Cohorts of Older Adults in Developed and Developing Countries.

TitleDevelopment and Validation of a 10-Year Mortality Prediction Model: Meta-Analysis of Individual Participant Data From Five Cohorts of Older Adults in Developed and Developing Countries.
Publication TypeJournal Article
Year of Publication2017
AuthorsSuemoto, CKimie, Ueda, H, Beltrán-Sánchez, H, Lebrão, MLucia, Duarte, YAparecida, Wong, R, Danaei, G
JournalJ Gerontol A Biol Sci Med Sci
Volume72
Issue3
Pagination410-416
Date Published2017 03 01
ISSN Number1758-535X
KeywordsAged, Aged, 80 and over, Developed Countries, Developing Countries, Female, Humans, Male, Meta-Analysis as Topic, Middle Aged, Models, Statistical, Mortality, Prognosis, Time Factors
Abstract

Background: Existing mortality prediction models for older adults have been each developed using a single study from the United States or Western Europe. We aimed to develop and validate a 10-year mortality prediction model for older adults using data from developed and developing countries.

Methods: We used data from five cohorts, including data from 16 developed and developing countries: ELSA (English Longitudinal Study of Aging), HRS (Health and Retirement Study), MHAS (Mexican Health and Aging Study), SABE-Sao Paulo (The Health, Well-being and Aging), and SHARE (Survey on Health, Ageing and Retirement in Europe). 35,367 older adults were split into training (two thirds) and test (one third) data sets. Baseline predictors included age, sex, comorbidities, and functional and cognitive measures. We performed an individual participant data meta-analysis using a sex-stratified Cox proportional hazards model, with time to death as the time scale. We validated the model using Harrell's C statistic (discrimination) and the estimated slope between observed and predicted 10-year mortality risk across deciles of risk (calibration).

Results: During a median of 8.6 years, 8,325 participants died. The final model included age, sex, diabetes, heart disease, lung disease, cancer, smoking, alcohol use, body mass index, physical activity, self-reported health, difficulty with bathing, walking several blocks, and reporting date correctly. The model showed good discrimination (Harrell's C = 0.76) and calibration (slope = 1.005). Models for developed versus developing country cohorts performed equally well when applied to data from developing countries.

Conclusion: A parsimonious mortality prediction model using data from multiple cohorts in developed and developing countries can be used to predict mortality in older adults in both settings.

URLhttp://biomedgerontology.oxfordjournals.org/cgi/pmidlookup?view=long&pmid=27522061
DOI10.1093/gerona/glw166
User Guide Notes

http://www.ncbi.nlm.nih.gov/pubmed/27522061?dopt=Abstract

Alternate JournalJ. Gerontol. A Biol. Sci. Med. Sci.
Citation Key8582
PubMed ID27522061
PubMed Central IDPMC6075520
Grant ListR01 AG018016 / AG / NIA NIH HHS / United States
U01 AG009740 / AG / NIA NIH HHS / United States
U01 AG009740 / AG / NIA NIH HHS / United States
P01 AG005842 / AG / NIA NIH HHS / United States
R21 AG025169 / AG / NIA NIH HHS / United States
R01 AG030153 / AG / NIA NIH HHS / United States
RC2 AG036619 / AG / NIA NIH HHS / United States