Comparison of comorbidity classification methods for predicting outcomes in a population-based cohort of adults with human immunodeficiency virus infection.
OBJECTIVE
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.
Department of Family and Community Medicine, St. Michael's Hospital, Toronto, Ontario, Canada; The Li Ka Shing Knowledge Institute, St. Michael's Hospital, Toronto, Ontario, Canada; Department of Family and Community Medicine, University of Toronto, Toronto, Ontario, Canada; Institute for Clinical Evaluative Sciences, Toronto, Ontario, Canada. Electronic address: tantoniou@smh.ca.
Tony
T
Antoniou
Institute for Clinical Evaluative Sciences, Toronto, Ontario, Canada.
Ryan
R
Ng
Department of Family and Community Medicine, St. Michael's Hospital, Toronto, Ontario, Canada; The Li Ka Shing Knowledge Institute, St. Michael's Hospital, Toronto, Ontario, Canada; Department of Family and Community Medicine, University of Toronto, Toronto, Ontario, Canada; Institute for Clinical Evaluative Sciences, Toronto, Ontario, Canada; Centre for Research on Inner City Health, St. Michael's Hospital, Toronto, Ontario, Canada; Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Ontario, Canada; Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada.
Richard H
RH
Glazier
Institute for Clinical Evaluative Sciences, Toronto, Ontario, Canada.
Alexander
A
Kopp
Institute for Clinical Evaluative Sciences, Toronto, Ontario, Canada; Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Ontario, Canada.
Peter C
PC
Austin
D000293:Adolescent; D000328:Adult; D000368:Aged; D002170:Canada / Q000453:epidemiology; D002423:Cause of Death; D015897:Comorbidity; D016208:Databases, Factual; D003953:Diagnosis-Related Groups; D005260:Female; D015658:HIV Infections / Q000175:diagnosis* / Q000401:mortality; D017052:Hospital Mortality; D006801:Humans; D016015:Logistic Models; D008875:Middle Aged; D009864:Ontario; D011237:Predictive Value of Tests; D012372:ROC Curve; D012111:Residence Characteristics; D018570:Risk Assessment / Q000379:methods / Q000592:standards*; D013997:Time Factors; D055815:Young Adult
Comorbidity; Databases; Diagnosis-related groups; Factual; HIV; Logistic models; Predictive value of tests; ROC curve; Risk adjustment