Validation of a 5-Year Mortality Prediction Model among U.S. Medicare Beneficiaries.
Medicare
mortality
older adults
predictive model
validation
Journal
Journal of the American Geriatrics Society
ISSN: 1532-5415
Titre abrégé: J Am Geriatr Soc
Pays: United States
ID NLM: 7503062
Informations de publication
Date de publication:
12 2020
12 2020
Historique:
received:
18
05
2020
revised:
21
07
2020
accepted:
11
08
2020
pubmed:
6
9
2020
medline:
19
3
2021
entrez:
5
9
2020
Statut:
ppublish
Résumé
A claims-based model predicting 5-year mortality (Lund-Lewis) was developed in a 2008 cohort of North Carolina (NC) Medicare beneficiaries and included indicators of comorbid conditions, frailty, disability, and functional impairment. The objective of this study was to validate the Lund-Lewis model externally within a nationwide sample of Medicare beneficiaries. Retrospective validation study. U.S. Medicare population. From a random sample of Medicare beneficiaries, we created four annual cohorts from 2008 to 2011 of individuals aged 66 and older with an office visit in that year. The annual cohorts ranged from 1.13 to 1.18 million beneficiaries. The outcome was 5-year all-cause mortality. We assessed clinical indicators in the 12 months before the qualifying office visit and estimated predicted 5-year mortality for each beneficiary in the nationwide sample by applying estimates derived in the original NC cohort. Model performance was assessed by quantifying discrimination, calibration, and reclassification metrics compared with a model fit on a comorbidity score. Across the annual cohorts, 5-year mortality ranged from 24.4% to 25.5%. The model had strong discrimination (C-statistics ranged across cohorts from .823 to .826). Reclassification measures showed improvement over a comorbidity score model for beneficiaries who died but reduced performance among beneficiaries who survived. The calibration slope ranged from .83 to .86; the model generally predicted a higher risk than observed. The Lund-Lewis model showed strong and consistent discrimination in a national U.S. Medicare sample, although calibration indicated slight overfitting. Future work should investigate methods for improving model calibration and evaluating performance within specific disease settings.
Sections du résumé
BACKGROUND/OBJECTIVES
A claims-based model predicting 5-year mortality (Lund-Lewis) was developed in a 2008 cohort of North Carolina (NC) Medicare beneficiaries and included indicators of comorbid conditions, frailty, disability, and functional impairment. The objective of this study was to validate the Lund-Lewis model externally within a nationwide sample of Medicare beneficiaries.
DESIGN
Retrospective validation study.
SETTING
U.S. Medicare population.
PARTICIPANTS
From a random sample of Medicare beneficiaries, we created four annual cohorts from 2008 to 2011 of individuals aged 66 and older with an office visit in that year. The annual cohorts ranged from 1.13 to 1.18 million beneficiaries.
MEASUREMENTS
The outcome was 5-year all-cause mortality. We assessed clinical indicators in the 12 months before the qualifying office visit and estimated predicted 5-year mortality for each beneficiary in the nationwide sample by applying estimates derived in the original NC cohort. Model performance was assessed by quantifying discrimination, calibration, and reclassification metrics compared with a model fit on a comorbidity score.
RESULTS
Across the annual cohorts, 5-year mortality ranged from 24.4% to 25.5%. The model had strong discrimination (C-statistics ranged across cohorts from .823 to .826). Reclassification measures showed improvement over a comorbidity score model for beneficiaries who died but reduced performance among beneficiaries who survived. The calibration slope ranged from .83 to .86; the model generally predicted a higher risk than observed.
CONCLUSION
The Lund-Lewis model showed strong and consistent discrimination in a national U.S. Medicare sample, although calibration indicated slight overfitting. Future work should investigate methods for improving model calibration and evaluating performance within specific disease settings.
Identifiants
pubmed: 32889756
doi: 10.1111/jgs.16816
pmc: PMC7781164
mid: NIHMS1645437
doi:
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Validation Study
Langues
eng
Sous-ensembles de citation
IM
Pagination
2898-2902Subventions
Organisme : NIA NIH HHS
ID : R01 AG056479
Pays : United States
Organisme : NCI NIH HHS
ID : R21 CA191454
Pays : United States
Organisme : NCATS NIH HHS
ID : UL1 TR001111
Pays : United States
Informations de copyright
© 2020 The American Geriatrics Society.
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