Comparison of comorbidity classification methods for predicting outcomes in a population-based cohort of adults with HIV 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 co-morbidity indices for predicting outcomes in 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 one year, and secondary outcomes included hospital admission and all-cause mortality within one to two years.

Results — The ADG, Elixhauser and Charlson methods had comparable discriminative performance for predicting one-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 one to two 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 one-year mortality. However, poor calibration limits the use of these methods for provider profiling and clinical application.