Shaan Khurshid

Background: The PREVENT-HF equations estimate 10-year risk of overall heart failure (HF), inclusive of both HF with preserved and reduced ejection fraction (HFpEF; HFrEF). Given differential risk factor profiles, pathophysiology, and therapeutic strategies for each HF subtype, we sought to examine the performance of PREVENT-HF for subtype-specific risk assessment. Methods: We included data from five pooled longitudinal cohort studies (baseline exam 1989 to 2013) and two longitudinal primary-care electronic health record-based samples (Beth Israel Deaconess Medical Center [BIDMC], baseline 2004 to 2014; Mass General Brigham [MGB], baseline 2001 to 2018). We assessed the performance of the PREVENT-HF equations in predicting 10-year incident HFrEF and HFpEF, including model discrimination (area under the receiver operating characteristic curve [AUROC]; average precision [AP]/event rate) and calibration (integrated calibration index [ICI]), in adults aged 30-79 years without prevalent cardiovascular disease or HF. Results: The pooled cohort studies included 23,652 (55% women, age 60 ± 13 years), of whom 1,232 developed HF (432 [35%] HFpEF, 522 [42%] HFrEF). The BIDMC sample included 29,815 (55% women, 50 ± 13 years), of whom 259 (1%) developed HF (133 [51%] HFpEF, 101 [39%] HFrEF). MGB included 138,999 (62% women, 52 ± 13 years), of whom 1050 developed HF (586 [56%] HFpEF, 381 [36%] HFrEF). PREVENT-HF demonstrated better discrimination for HFpEF than HFrEF across all samples: in the pooled cohorts, the AUROC for HFpEF was 0.824 (95% CI 0.807, 0.839) versus 0.789 (95% CI 0.770, 0.807) for HFrEF; in BIDMC, the AUROC for HFpEF was 0.897 (95% CI 0.874, 0.918) versus 0.833 (95% CI 0.791, 0.869) for HFrEF; in MGB, the AUROC for HFpEF was 0.864 (95% CI 0.848, 0.880) versus 0.797 (95% CI 0.771, 0.820) for HFrEF. Similar results were reflected in the AP/event rate ratios: 2.92 (95% CI 2.47, 3.54) for HFpEF compared to 2.66 (95% CI 2.33, 3.14) for HFrEF in the pooled cohorts; 8.08 (95% CI 6.12, 12.30) for HFpEF compared to 5.12 (95% CI 3.84, 8.17) for HFrEF in BIDMC; and 6.84 (95% CI 5.66, 8.28) for HFpEF compared to 4.12 (95% CI 3.37, 5.16) for HFrEF in MGB. Calibration was similar for HFpEF and HFrEF across samples. For example, in the pooled cohorts, the ICI for HFpEF was 0.041 (95% CI 0.039, 0.043) and for HFrEF was 0.038 (95% CI 0.036, 0.040). Conclusions: PREVENT-HF demonstrated excellent discrimination for both HF subtypes across community-based cohorts and real-world samples, with consistently better discrimination for HFpEF as compared to HFrEF. Given PREVENT-HF was developed to estimate overall HF risk rather than subtype-specific risk, future studies are needed to establish subtype-specific risk thresholds.