Incorporating Frailty Into the Pooled Cohort Equations to Predict Cardiovascular Disease Among Persons With HIV. (1st July 2021) - Kelly, Sean G.; Wu, Kunling; Tassiopoulos, Katherine; Erlandson, Kristine M.; Koletar, Susan L.; Palella, Frank J.
Abstract : Background: The 2013 Pooled Cohort Equations (PCEs) have underestimated cardiovascular disease (CVD) events among persons with HIV (PWH). We evaluate whether the addition of frailty improves PCE's ability to estimate CVD risk among aging PWH. Setting: Multicenter study. Methods: We assessed baseline frailty and 5-year atherosclerotic CVD risk using PCEs for participants in the AIDS Clinical Trials Group A5322 observational study. The primary outcome was incident CVD. We fit Cox proportional hazards regression models for incident CVD with (1) PCEs alone and (2) PCEs and frailty together (which included separate models for frailty score, frailty status, slow gait speed, and weak grip strength). We evaluated discrimination ability for the models with and without frailty by comparing their areas under receiver operating characteristic curve (AUCs) and Uno C-statistics, as well as by calculating the net reclassification improvement and integrated discrimination improvement. Results: The analysis included 944 A5322 participants (759 men, 185 women, median age 50 years, 47% White non-Hispanic). Thirty-nine participants experienced incident CVD during the study period. PCEs predicted 5-year CVD risk in all models. With frailty score, frailty status, slow gait speed, or weak grip strength added, the AUC and C-statistics were relatively unchanged, and the NRI and integrated discrimination improvement indicated little improvement in model discrimination. However, frailty score independently predicted CVD risk [frailty score: hazard ratio = 1.30, 95% confidence interval (CI) = 1.00 to 1.70, P = 0.05]. Conclusions: Frailty did not improve the predictive ability of PCEs. Baseline PCEs and frailty score independently predicted CVD. Incorporation of frailty assessment into clinical practice may provide corroborative and independent CVD risk estimation.