Comparison of comorbidity classification methods for predicting outcomes in a population-based cohort of adults with human immunodeficiency virus infection

Purpose: We compared the John's Hopkins' Aggregated Diagnosis Groups (ADGs), which are derived using inpatient and outpatient records, with the hospital record-derived Charlson and Elixhauser comorbidity indices for predicting outcomes in human immunodeficiency virus (HIV)-infected patients. Methods: We used a validated algorithm to identify HIV-infected adults (n = 14,313) in Ontario, Canada, and randomly divided the sample into derivation and validation samples 100 times. The primary outcome was all-cause mortality within 1 year, and secondary outcomes included hospital admission and all-cause mortality within 1-2 years. Results: The ADG, Elixhauser, and Charlson methods had comparable discriminative performance for predicting 1-year mortality, with median c-statistics of 0.785, 0.767, and 0.788, respectively, across the 100 validation samples. All methods had lower predictive accuracy for all-cause mortality within 1-2 years. For hospital admission, the ADG method had greater discriminative performance than either the Elixhauser or Charlson methods, with median c-statistics of 0.727, 0.678, and 0.668, respectively. All models displayed poor calibration for each outcome. Conclusions: In patients with HIV, the ADG, Charlson, and Elixhauser methods are comparable for predicting 1-year mortality. However, poor calibration limits the use of these methods for provider profiling and clinical application. (C) 2014 Elsevier Inc. All rights reserved.