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. 2017 Mar 1;72(3):410-416.
doi: 10.1093/gerona/glw166.

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

Claudia Kimie Suemoto  1   2 , Peter Ueda  1 , Hiram Beltrán-Sánchez  3 , Maria Lucia Lebrão  4 , Yeda Aparecida Duarte  5 , Rebeca Wong  6 , Goodarz Danaei  1   7
Affiliations

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

Claudia Kimie Suemoto et al. J Gerontol A Biol Sci Med Sci. .

Erratum in

  • Corrigendum.
    [No authors listed] [No authors listed] J Gerontol A Biol Sci Med Sci. 2017 May 1;72(5):731. doi: 10.1093/gerona/glw345. J Gerontol A Biol Sci Med Sci. 2017. PMID: 28329076 Free PMC article. No abstract available.

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.

Keywords: Mortality; Older adults; Prediction models; Prevention.

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Figures

Figure 1.
Figure 1.
Flowchart of participant selection for the pooled data sets.
Figure 2.
Figure 2.
Scatter plot and linear regression line of observed and predicted 10-year risk of death in the testing data set (n = 11,752).
See this image and copyright information in PMC

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References

    1. WHO. Global Health and Aging. National Institute of Aging. National Institute of Health. US Department of Health and Human Services; 2011.
    1. Lassman D, Hartman M, Washington B, Andrews K, Catlin A. US health spending trends by age and gender: selected years 2002–10. Health Affairs. 2014;33:815–822. doi:10.1377/hlthaff.2013.1224 - PubMed
    1. Qaseem A, Denberg TD, Hopkins RH, Jr, et al. Screening for colorectal cancer: a guidance statement from the American College of Physicians. Ann Intern Med. 2012;156: 378–386. doi:10.7326/0003-4819-156-5-201203060-00010 - PubMed
    1. Qaseem A, Barry MJ, Denberg TD, Owens DK, Shekelle P. Screening for prostate cancer: a guidance statement from the Clinical Guidelines Committee of the American College of Physicians. Ann Intern Med. 2013;158:761–769. doi:10.7326/0003-4819-158-10-201305210-00633 - PubMed
    1. American Diabetes Association. Standards of medical care in diabetes—2014. Diabetes Care. 2014;37(suppl 1):S14–S80. doi:10.2337/dc14-S014 - PubMed

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