Development and internal validation of a new life expectancy estimator for multimorbid older adults.

Background As populations are aging, the number of older patients with multiple chronic diseases demanding complex care increases. Although clinical guidelines recommend care to be personalized accounting for life expectancy, there are no tools to estimate life expectancy among multimorbid patients. Our objective was therefore to develop and internally validate a life expectancy estimator specifically for older multimorbid adults.Methods We analyzed data from the OPERAM (OPtimising thERapy to prevent avoidable hospital admissions in multimorbid older people) study in Bern, Switzerland. Participants aged 70 years old or more with multimorbidity (3 or more chronic medical conditions) and polypharmacy (use of 5 drugs or more for > 30 days) were included. All-cause mortality was assessed during 3 years of follow-up. We built a 3-year mortality prognostic index and transformed this index into a life expectancy estimator. Mortality risk candidate predictors included demographic variables (age, sex), clinical characteristics (metastatic cancer, number of drugs, body mass index, weight loss), smoking, functional status variables (Barthel-Index, falls, nursing home residence), and hospitalization. We internally validated and optimism corrected the model using bootstrapping techniques. We transformed the mortality prognostic index into a life expectancy estimator using the Gompertz survival function.Results Eight hundred five participants were included in the analysis. During 3 years of follow-up, 292 participants (36%) died. Age, metastatic cancer, number of drugs, lower body mass index, weight loss, number of hospitalizations, and lower Barthel-Index (functional impairment) were selected as predictors in the final multivariable model. Our model showed moderate discrimination with an optimism-corrected C statistic of 0.70. The optimism-corrected calibration slope was 0.96. The Gompertz-predicted mean life expectancy in our sample was 5.4 years (standard deviation 3.5 years). Categorization into three life expectancy groups led to visually good separation in Kaplan-Meier curves. We also developed a web application that calculates an individual's life expectancy estimation.Conclusion A life expectancy estimator for multimorbid older adults based on an internally validated 3-year mortality risk index was developed. Further validation of the score among various populations of multimorbid patients is needed before its implementation into practice.Trial Registration ClinicalTrials.gov NCT02986425. First submitted 21/10/2016. First posted 08/12/2016.

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Open Access CRIS of the University of Bern
Published
2025-03-04
DOI
https://doi.org/10.48620/86865
Primary Topic
Chronic Disease Management Strategies
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article
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article

Development and internal validation of a new life expectancy estimator for multimorbid older adults.

Open Access CRIS of the University of Bern
Chronic Disease Management Strategies
article

Development and internal validation of a new life expectancy estimator for multimorbid older adults.

article en

Abstract

Background As populations are aging, the number of older patients with multiple chronic diseases demanding complex care increases. Although clinical guidelines recommend care to be personalized accounting for life expectancy, there are no tools to estimate life expectancy among multimorbid patients. Our objective was therefore to develop and internally validate a life expectancy estimator specifically for older multimorbid adults.Methods We analyzed data from the OPERAM (OPtimising thERapy to prevent avoidable hospital admissions in multimorbid older people) study in Bern, Switzerland. Participants aged 70 years old or more with multimorbidity (3 or more chronic medical conditions) and polypharmacy (use of 5 drugs or more for > 30 days) were included. All-cause mortality was assessed during 3 years of follow-up. We built a 3-year mortality prognostic index and transformed this index into a life expectancy estimator. Mortality risk candidate predictors included demographic variables (age, sex), clinical characteristics (metastatic cancer, number of drugs, body mass index, weight loss), smoking, functional status variables (Barthel-Index, falls, nursing home residence), and hospitalization. We internally validated and optimism corrected the model using bootstrapping techniques. We transformed the mortality prognostic index into a life expectancy estimator using the Gompertz survival function.Results Eight hundred five participants were included in the analysis. During 3 years of follow-up, 292 participants (36%) died. Age, metastatic cancer, number of drugs, lower body mass index, weight loss, number of hospitalizations, and lower Barthel-Index (functional impairment) were selected as predictors in the final multivariable model. Our model showed moderate discrimination with an optimism-corrected C statistic of 0.70. The optimism-corrected calibration slope was 0.96. The Gompertz-predicted mean life expectancy in our sample was 5.4 years (standard deviation 3.5 years). Categorization into three life expectancy groups led to visually good separation in Kaplan-Meier curves. We also developed a web application that calculates an individual's life expectancy estimation.Conclusion A life expectancy estimator for multimorbid older adults based on an internally validated 3-year mortality risk index was developed. Further validation of the score among various populations of multimorbid patients is needed before its implementation into practice.Trial Registration ClinicalTrials.gov NCT02986425. First submitted 21/10/2016. First posted 08/12/2016.

Open Access CRIS of the University of Bern
General Department of Preventive Medicine (VN), Primary Health Care (QA), Kollegium für Hausarztmedizin (CH)
Openalex Percentile: Top 45%
Chronic Disease Management Strategies
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