The data-collection on adverse effects of anti-HIV drugs (D:A:D) model for predicting cardiovascular events: External validation in a diverse cohort of people living with HIVShow full item record
|Title||The data-collection on adverse effects of anti-HIV drugs (D:A:D) model for predicting cardiovascular events: External validation in a diverse cohort of people living with HIV|
|Author||Anikpo, Ifedioranma; Agovi, Afiba Manza-A.; Cvitanovich, Matthew J.; Lonergan, Frank; Johnson, Marc; Ojha, Rohit P.|
|Abstract||Objectives Little is known about the external validity of the Data-collection on Adverse Effects of Anti-HIV Drugs (D:A:D) model for predicting cardiovascular disease (CVD) risk among people living with HIV (PLWH). We aimed to evaluate the performance of the updated D:A:D model for 5-year CVD risk in a diverse group of PLWH engaged in HIV care. Methods We used data from an institutional HIV registry, which includes PLWH engaged in care at a safety-net HIV clinic. Eligible individuals had a baseline clinical encounter between 1 January 2013 and 31 December 2014, with follow-up through to 31 December 2019. We estimated 5-year predicted risks of CVD as a function of the prognostic index and baseline survival of the D:A:D model, which were used to assess model discrimination (C-index), calibration and net benefit. Results Our evaluable population comprised 1029 PLWH, of whom 30% were female, 50% were non-Hispanic black, and median age was 45 years. The C-index was 0.70 [95% confidence limits (CL): 0.64-0.75]. The predicted 5-year CVD risk was 3.0% and the observed 5-year risk was 8.9% (expected/observed ratio = 0.33, 95% CL: 0.26-0.54). The model had a greater net benefit than treating all or treating none at a risk threshold of 10%. Conclusions The D:A:D model was miscalibrated for CVD risk among PLWH engaged in HIV care at an urban safety-net HIV clinic, which may be related to differences in case-mix and baseline CVD risk. Nevertheless, the HIV D:A:D model may be useful for decisions about CVD intervention for high-risk patients.|
|Department||Burnett School of Medicine|
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