Validation of an algorithm to identify antiretroviral-naive status at time of entry into a large, observational cohort of HIV-infected patients
Authors
Gandhi, Neel R.Tate, Janet P.
Rodriguez-Barradas, Maria C.
Rimland, David
Goetz, Matthew Bidwell
Gibert, Cynthia
Brown, Sheldon T.
Mattocks, Kristin M
Justice, Amy C.
UMass Chan Affiliations
Department of Quantitative Health SciencesDocument Type
Journal ArticlePublication Date
2013-09-01Keywords
*AlgorithmsAnti-Retroviral Agents
Cohort Studies
Female
HIV Infections
Humans
Male
Medical Records
Middle Aged
Observational Study as Topic
Pharmacoepidemiology
Predictive Value of Tests
Questionnaires
Reproducibility of Results
Retrospective Studies
Viral Load
Analytical, Diagnostic and Therapeutic Techniques and Equipment
Immune System Diseases
Metadata
Show full item recordAbstract
PURPOSE: Large, observational HIV cohorts play an important role in answering questions which are difficult to study in randomized trials; however, they often lack detailed information regarding previous antiretroviral treatment (ART). Knowledge of ART treatment history is important when ascertaining the long-term impact of medications, co-morbidities, or adverse reactions on HIV outcomes. METHODS: We performed a retrospective study to validate a prediction algorithm for identifying ART-naive patients using the Veterans Aging Cohort Study's Virtual Cohort-an observational cohort of 40 594 HIV-infected veterans nationwide. Medical records for 3070 HIV-infected patients were reviewed to determine history of combination ART treatment. An algorithm using Virtual Cohort laboratory data was used to predict ART treatment status and compared to medical record review. RESULTS: Among 3070 patients' medical records reviewed, 1223 were eligible for analysis. Of these, 990 (81%) were ART naive at cohort entry based on medical record review. The prediction algorithm's sensitivity was 86%, specificity 47%, positive predictive value (PPV) 87%, and negative predictive value 45%, using a viral load threshold of /ml. Sensitivity analysis revealed that PPV would be maximized by increasing the viral load threshold, whereas sensitivity would be maximized by lowering the viral load threshold. CONCLUSIONS: A prediction algorithm using available laboratory data can be used to accurately identify ART-naive patients in large, observational HIV cohorts. Use of this algorithm will allow investigators to accurately limit analyses to ART-naive patients when studying the contribution of ART to outcomes and adverse events.Source
2013 Jul 9. Link to article on publisher's site
DOI
10.1002/pds.3476Permanent Link to this Item
http://hdl.handle.net/20.500.14038/51019PubMed ID
23836591Related Resources
ae974a485f413a2113503eed53cd6c53
10.1002/pds.3476