CROI 2020 Abstract eBook

Abstract eBook

Poster Abstracts

650 MYOCARDIAL INFARCTION BY ATHEROSCLEROTIC CARDIOVASCULAR DISEASE (ASCVD) RISK SCORE Keri N. Althoff 1 , Todd T.Brown 2 , Greer Burkholder 3 , Heidi M. Crane 4 , Joseph Delaney 4 , Richard A.Elion 5 , Karla I. Galaviz 6 , Stephen J. Gange 1 , Michael A. Horberg 7 , Frank J. Palella 8 , Michael J. Silverberg 9 , Janet Tate 10 , Richard D.Moore 2 , for the NA-ACCORD of IeDEA 1 Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA, 2 Johns Hopkins University School of Medicine, Baltimore, MD, USA, 3 University of Alabama at Birmingham, Birmingham, AL, USA, 4 University of Washington, Seattle, WA, USA, 5 George Washington University, Washington, DC, USA, 6 Emory University, Atlanta, GA, USA, 7 Kaiser Permanente Mid-Atlantic States, Rockville, MD, USA, 8 Northwestern University, Chicago, IL, USA, 9 Kaiser Permanente, Oakland, CA, USA, 10 VA Connecticut Healthcare System, West Haven, CT, USA Background: Physicians who care for people with HIV (PWH) need to know the person’s risk for myocardial infarction (MI) to initiate discussions about preventive interventions. We aimed to estimate the absolute rate and cumulative incidence of MI by AHA/ACC 10-year atherosclerotic cardiovascular disease (ASCVD) risk score (which includes sex, age, race, cholesterol, blood pressure, and history of diabetes, smoking, and hypertension treatment) among PWH in North America. Methods: PWH from NA-ACCORD cohorts that validated type 1 MIs (induced by plaque rupture with thrombus) were included. Study entry began as the later date of NA-ACCORD enrollment, age 40, ART initiation date, 1 Jan 2000, or the cohort start date of MI observation. Study exit was defined as the earliest of MI date, death date, loss to follow up (2 years with no HIV RNA or CD4 measurements), age 80, 31 Dec 2015, or the cohort start date of MI observation. 10-year AHA/ACC ASCVD risk score was calculated at study entry and categorized <5%, 5-<10%, 10-<15%, 15-<25%, ≥25% risk. Cumulative incidence of MI from the time of study entry up to 10 years were estimated using Kaplan-Meier methods and compared using log-rank tests. MI incidence rates (per 1000 person years) with 95% confidence intervals [,] were estimated using Poisson regression models. Results: 20,675 adults (17,247 men and 3,428 women) contributed 282 MIs and 140,543 person years. Median age at study entry was 44.4 (interquartile range [IQR] 40.0, 50.5) years, median CD4 was 381 (IQR 203, 597) cells/mm 3 , and median follow-up was 6.0 (IQR 3.0, 10.1) years. Log-rank tests indicated significant heterogeneity by ASCVD score (p<0.001). Individuals with an ASCVD risk score ≥25% (n=7,698) attained a cumulative incidence of 25% at 4 years after study entry, and 50% at 7 years (Figure 1a). Those with an ASCVD risk score 15-<25% (n=6,674) and 10-<15% (n=3,216) attained a cumulative incidence of 25% by year 6 and 8 after study entry, respectively. The incidence rates increased with increasing ASCVD risk score in men, with women having lower risk and a plateau after an ASCVD risk score of 15% (Figure 1b). Conclusion: The 10-year ASCVD risk score underestimated the cumulative incidence of MI among those with risk >10%. For PWH who have an ASCVD risk score >10%, aggressive cardiovascular prevention efforts should be initiated immediately, including smoking cessation, lipid control, and blood sugar control.

649 PHENOTYPIC CLUSTERING OF HIV-ASSOCIATED ATHEROSCLEROSIS AND AGE-RELATED OUTCOMES David B. Hanna 1 , Jee-Young Moon 1 , Bryan Lau 2 , Kathryn Anastos 3 , Russell Tracy 4 , Sabina A. Haberlen 2 , Caitlin A. Moran 5 , Todd T. Brown 6 , Leah H. Rubin 6 , Lawrence Kingsley 7 , Stephen J. Gange 2 , Wendy Post 6 , Robert C. Kaplan 1 , Howard Hodis 8 , for the MACS/WIHS Combined Cohort Study 1 Albert Einstein College of Medicine, Bronx, NY, USA, 2 Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA, 3 Montefiore Medical Center, Bronx, NY, USA, 4 University of Vermont, Burlington, VT, USA, 5 Emory University, Atlanta, GA, USA, 6 Johns Hopkins University School of Medicine, Baltimore, MD, USA, 7 University of Pittsburgh, Pittsburgh, PA, USA, 8 University of Southern California, Los Angeles, CA, USA Background: People with HIV (PWH) have increased cardiovascular disease risk, but the underlying mechanisms are not fully elucidated. We used machine learning to develop phenotypic profiles of individuals with subclinical carotid atherosclerosis that incorporate multiple risk factor interactions, and determined whether these profiles differentially associate with age-related disease. Methods: The MACS/WIHS CCS prospectively follows people with and without HIV at 14 sites. 2,796 participants had non-invasive B-mode ultrasound of the right carotid artery in 2004-2006, and 528 (30%women) were identified with plaque (focal IMT >1.5 mm). We used random forests and hierarchical clustering on 76 demographic, behavioral and clinical markers assessed near the time of the scan to classify individuals into phenotypically similar clusters among those with plaque. Over 13 years of follow-up, we assessed the association of each cluster with all-cause mortality, and in women, hospitalization rates and cognitive decline. Results: Our approach identified 4 distinct clusters that differed by age and hypertension history (Figure). Clusters C and D (mean age 56-57) were on average 14 years older than A and B, and B and D were much more likely to be hypertensive than A and C (all p<0.001). Even though C and D were of similar age, C had less carotid disease (fewer plaques, less stiffness) than D (p<0.001), but similar levels as B. Compared with D, C also was significantly less likely to smoke (34% vs 43%) or be diabetic (12% vs 21%), more likely to be treated for hypertension (among hypertensives, 92% vs 52%), and had lower BMI (mean 25 vs 27 kg/m 2 ) and higher bilirubin (mean 0.85 vs 0.69 mg/dL). Among PWH, C was more likely to be on ART (73% vs 65%) than D and more likely to have history of AIDS (36% vs 25%) and lower CD4+ count (mean 478 vs 523 cells/uL). Over time, C had better survival (HR 0.56, 95% CI 0.36-0.88), fewer hospitalizations (RR 0.79, 95% CI 0.48-1.29), and less decline in processing speed (difference in Z-score for Trail Making Test A 0.03, 95% CI 0.001-0.05) than D. Outcomes for C were similar to A and B despite older age. Conclusion: Our current analysis identified a profile of individuals with subclinical atherosclerosis who, as they entered their 6th decade, seemed to represent more of a "healthy aging" phenotype than others of the same age. Future work should further characterize this group and identify mechanisms underlying their apparent resiliency.

Poster Abstracts

CROI 2020 236