A Combined Comorbidity Score Predicted Mortality in Elderly Patients Better Than Existing Scores

Overview

Journal J Clin Epidemiol

Publisher Elsevier

Specialty Public Health

Date 2011 Jan 7

PMID 21208778

Citations 488

Authors

Joshua J Gagne

Robert J Glynn

Jerry Avorn

Raisa Levin

Sebastian Schneeweiss

Affiliations

Soon will be listed here.

Abstract

Objective: To develop and validate a single numerical comorbidity score for predicting short- and long-term mortality, by combining conditions in the Charlson and Elixhauser measures.

Study Design And Setting: In a cohort of 120,679 Pennsylvania Medicare enrollees with drug coverage through a pharmacy assistance program, we developed a single numerical comorbidity score for predicting 1-year mortality, by combining the conditions in the Charlson and Elixhauser measures. We externally validated the combined score in a cohort of New Jersey Medicare enrollees, by comparing its performance to that of both component scores in predicting 1-year mortality, as well as 180-, 90-, and 30-day mortality.

Results: C-statistics from logistic regression models including the combined score were higher than corresponding c-statistics from models including either the Romano implementation of the Charlson Index or the single numerical version of the Elixhauser system; c-statistics were 0.860 (95% confidence interval [CI]: 0.854, 0.866), 0.839 (95% CI: 0.836, 0.849), and 0.836 (95% CI: 0.834, 0.847), respectively, for the 30-day mortality outcome. The combined comorbidity score also yielded positive values for two recently proposed measures of reclassification.

Conclusion: In similar populations and data settings, the combined score may offer improvements in comorbidity summarization over existing scores.

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