Richard A Elion1,2, Keri N Althoff3, Jinbing Zhang3, Richard D Moore4, Stephen J Gange3, Mari M Kitahata5, Heidi M Crane5, Daniel R Drozd5, James H Stein6, Marina B Klein7,8, Joseph J Eron9, Michael J Silverberg10, William C Mathews11, Amy C Justice12,13, Timothy R Sterling14, Charles S Rabkin15, Angel M Mayor16, Daniel B Klein17, Michael A Horberg18, Ronald J Bosch19, Oghenowede Eyawo20,21, Frank J Palella22. 1. Department of Medicine, George Washington University School of Medicine, Washington, DC. 2. Department of Infectious Disease, Providence Hospital, Washington, DC. 3. Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD. 4. Department of Medicine, Johns Hopkins School of Medicine, Baltimore, MD. 5. Department of Medicine, University of Washington School of Medicine, Seattle, WA. 6. Department of Medicine, University of Wisconsin School of Medicine and Public Health, Madison, WI. 7. Department of Epidemiology, Biostatistics, and Occupational Health, McGill University, Montreal, QC, Canada. 8. Division of Infectious Diseases and Chronic Viral Illness Service, McGill University Health Centre, Montreal, QC, Canada. 9. Division of Infectious Diseases, Department of Medicine, University of North Carolina School of Medicine, Chapel Hill, NC. 10. Division of Research, Kaiser Permanente Northern California, Oakland, CA. 11. Department of Medicine, University of California San Diego, San Diego, CA. 12. Division of General Internal Medicine, Yale School of Medicine, New Haven, CT. 13. VA Connecticut Healthcare System, West Haven, CT. 14. Department of Medicine, Vanderbilt University School of Medicine, Nashville, TN. 15. Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD. 16. Department of Internal Medicine, Universidad Central del Caribe, School of Medicine, Bayamon, PR. 17. Department of Infectious Diseases, San Leandro Medical Center, Kaiser Permanente Northern California, San Leandro, CA. 18. Mid-Atlantic Permanente Research Institute, Kaiser Permanente Mid-Atlantic States, Rockville, MD. 19. Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA. 20. BC Centre for Excellence in HIV/AIDS, Vancouver, BC. 21. Faculty of Health Sciences, Simon Fraser University, Burnaby, BC. 22. Division of Infectious Diseases, Northwestern University Feinberg School of Medicine, Chicago, IL.
Abstract
BACKGROUND: There is persistent confusion as to whether abacavir (ABC) increases the risk of myocardial infarction (MI), and whether such risk differs by type 1 (T1MI) or 2 (T2MI) MI in adults with HIV. METHODS: Incident MIs in North American Cohort Collaboration on Research and Design participants were identified from 2001 to 2013. Discrete time marginal structural models addressed channeling biases and time-dependent confounding to estimate crude hazard ratio (HR) and adjusted hazard ratio (aHR) and 95% confidence intervals; analyses were performed for T1MI and T2MI separately. A sensitivity analysis evaluated whether Framingham risk score (FRS) modified the effect of ABC on MI occurrence. RESULTS: Eight thousand two hundred sixty-five adults who initiated antiretroviral therapy contributed 29,077 person-years and 123 MI events (65 T1MI and 58 T2MI). Median follow-up time was 2.9 (interquartile range 1.4-5.1) years. ABC initiators were more likely to have a history of injection drug use, hepatitis C virus infection, hypertension, diabetes, impaired kidney function, hyperlipidemia, low (<200 cells/mm) CD4 counts, and a history of AIDS. The risk of the combined MI outcome was greater for persons who used ABC in the previous 6 months [aHR = 1.84 (1.17-2.91)]; and persisted for T1MI (aHR = 1.62 [1.01]) and T2MI [aHR = 2.11 (1.08-4.29)]. FRS did not modify the effect of ABC on MI (P = 0.14) and inclusion of FRS in the MSM did not diminish the effect of recent ABC use on the combined outcome. CONCLUSIONS: Recent ABC use was associated with MI after adjustment for known risk factors and for FRS. However, screening for T1MI risks may not identify all or even most persons at risk of ABC use-associated MIs.
BACKGROUND: There is persistent confusion as to whether abacavir (ABC) increases the risk of myocardial infarction (MI), and whether such risk differs by type 1 (T1MI) or 2 (T2MI) MI in adults with HIV. METHODS: Incident MIs in North American Cohort Collaboration on Research and Design participants were identified from 2001 to 2013. Discrete time marginal structural models addressed channeling biases and time-dependent confounding to estimate crude hazard ratio (HR) and adjusted hazard ratio (aHR) and 95% confidence intervals; analyses were performed for T1MI and T2MI separately. A sensitivity analysis evaluated whether Framingham risk score (FRS) modified the effect of ABC on MI occurrence. RESULTS: Eight thousand two hundred sixty-five adults who initiated antiretroviral therapy contributed 29,077 person-years and 123 MI events (65 T1MI and 58 T2MI). Median follow-up time was 2.9 (interquartile range 1.4-5.1) years. ABC initiators were more likely to have a history of injection drug use, hepatitis C virus infection, hypertension, diabetes, impaired kidney function, hyperlipidemia, low (<200 cells/mm) CD4 counts, and a history of AIDS. The risk of the combined MI outcome was greater for persons who used ABC in the previous 6 months [aHR = 1.84 (1.17-2.91)]; and persisted for T1MI (aHR = 1.62 [1.01]) and T2MI [aHR = 2.11 (1.08-4.29)]. FRS did not modify the effect of ABC on MI (P = 0.14) and inclusion of FRS in the MSM did not diminish the effect of recent ABC use on the combined outcome. CONCLUSIONS: Recent ABC use was associated with MI after adjustment for known risk factors and for FRS. However, screening for T1MI risks may not identify all or even most persons at risk of ABC use-associated MIs.
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