Age- and Sex-Adjusted Myocardial Flow Reserve Percentiles for Personalized Cardiovascular Risk Assessment

作者：Lee Joseph, Ludovic Trinquart, Diana M. Lopez, S. Brandão, Jenifer M. Brown, S. Divakaran, D. Huck, Brittany Weber, Leanne Barrett Goldstein, J. Hainer, Sylvain L. Carre, M. Lemley, G. Ramirez, Joanna X. Liang, R. Blankstein, S. Dorbala, E. Alexanderson, I. Carvajal-Juarez, W. Acampa, René R. S. Packard, V. Le, S. Mason, S. Knight, P. Chareonthaitawee, S. Wopperer, T. Rosamond, R. Buechel, A. J. Einstein, M. Al-Mallah, L. Slipczuk, M. Travin, Daniel S. Berman, D. Dey, P. Slomka, M. D. Di Carli · 发表于：medRxiv · 年份：2025 · DOI：10.64898/2025.12.30.25343223 · 被引用次数：2 · 研究领域：Medicine

ABSTRACT Introduction Positron emission tomography (PET) myocardial flow reserve (MFR) is a robust indicator of coronary vascular health and a strong predictor of cardiovascular risk. Clinical guidelines typically use fixed MFR thresholds (e.g., <2.0) to stratify risk, yet this approach overlooks individual variation, particularly by age and sex. We aimed to establish age- and sex-adjusted MFR percentiles and to evaluate their prognostic and predictive performance for cardiovascular risk assessment, in comparison with conventional fixed-threshold MFR approach. Methods Using data from the REFINE PET registry (24,820 patients from 12 sites), we measured PET MFR and derived age- and sex-adjusted MFR reference percentiles using quantile regression in patients without known coronary artery disease. All patients were categorized into percentile-based quartile groups. The primary outcome for prognostic and prediction analyses was major adverse cardiovascular events (MACE), defined as all-cause mortality, myocardial infarction, or heart-failure hospitalization. Time-to-event associations were evaluated using covariate-adjusted survival models, with cumulative incidence and hazard ratios (HR) estimated at 1 and 5 years in the derivation dataset, an independent but similar validation dataset A, and a high-risk validation dataset B. Predictive performance for MACE was assessed using discrimination, calibration, and reclassification metrics, comparing percentile-based models with models ...