Development and Validation of a Health‐Related Quality‐of‐Life Comorbidity Index

Abstract

Objectives: Comorbidity indexes adjust for comorbidity confounding on a specific outcome, but no index is designed specifically for a quality of life (QOL) outcome. The Functional Comorbidity Index was previously designed to predict physical function. The goals of this study: 1) Develop a Quality of Life Comorbidity Index (QOLI) designed specifically to predict QOL (measured using SF-36 component scores) in sleep apnea patients; 2) Compare the ability to predict QOL between the QOLI, the Functional Comorbidity Index, and another commonly used index. Methods: A random sample of 300 subjects, selected from prospectively enrolled sleep apnea patients between 2004-07, was split into a model-development cohort (n=200) and a validation cohort (n=100). Additional comorbidities suspected to impact QOL were selected as candidate variables to add to the Functional Comorbidity Index. Multivariate linear regression using predictive stepwise modeling was applied to determine which candidate variables maximized the ability to predict QOL (adjusted R2). The resultant QOLI was tested in the validation cohort, and the ability to predict QOL was compared to other comorbidity indexes. Results: The QOLI model that best predicted QOL added smoking, illicit drug use, migraine, fibromyalgia, allergies, and sinusitis to the Functional Comorbidity Index. The ability to predict QOL (adjusted R2) was better in the QOLI by 10% compared to the Functional Comorbidity Index and by 18% compared to the Charlson Comorbidity Index. Conclusions: The QOLI is useful to predict quality of life and is a more robust predictor of QOL than other comorbidity indexes in obstructive sleep apnea patients.