Cutaneous melanoma incidence may be modestly elevated in people with HIV (PWH) vs. people without HIV. However, little is known about the relationship of immunosuppression, HIV replication, and antiretroviral therapy (ART) with melanoma risk.
PWH of white race in the North American AIDS Cohort Collaboration on Research and Design were included. A standardized incidence ratio was calculated comparing risk with the white general population, standardizing by age, sex, and calendar period. Associations between melanoma incidence and current, lagged, and cumulative measures of CD4 count, HIV RNA level, and ART use were estimated with Cox regression, adjusting for established risk factors such as age and annual residential ultraviolet B (UVB) exposure.
Eighty melanomas were diagnosed among 33,934 white PWH (incidence = 40.75 per 100,000 person-years). Incidence was not elevated compared with the general population [standardized incidence ratio = 1.15, 95% confidence interval (95% CI) = 0.91 to 1.43]. Higher melanoma incidence was associated with older age [adjusted hazard ratio (aHR) per decade increase = 1.50, 95% CI = 1.20 to 1.89] and higher UVB exposure (aHR for exposure ≥35 vs. <35 mW/m2 = 1.62, 95% CI = 0.99 to 2.65). Current, lagged, and cumulative CD4 and HIV RNA were not associated with melanoma incidence. Melanoma incidence was higher among people ART-treated for a larger proportion of time in the previous 720 days (aHR per 10% increase = 1.16, 95% CI = 1.03 to 1.30).
These results suggest that HIV-induced immune dysfunction does not influence melanoma development. The association between ART and melanoma risk may be due to increased skin surveillance among PWH engaged in clinical care. Associations with age and UVB confirmed those established in the general population.
*Department of Orthopedic Surgery, Washington University School of Medicine, St. Louis, MO;
†Division of Public Health Sciences, Department of Surgery, Washington University School of Medicine, St. Louis, MO;
‡Department of Chronic Disease Epidemiology, Yale School of Public Health, New Haven, CT;
Internal Medicine, Center for Outcomes Research and Evaluation, Yale School of Medicine, New Haven, CT;
║Department of Biostatistics, Yale School of Public Health, New Haven, CT;
¶Division of Research, Kaiser Permanente Northern California, Oakland, CA;
# Mid-Atlantic Permanente Research Institute, Kaiser Permanente Mid-Atlantic, Rockville, MD;
**Department of General Internal Medicine, Johns Hopkins University, Baltimore, MD;
††Department of Medicine, University of California San Diego, San Diego, MD;
‡‡Department of Internal Medicine, Yale School of Medicine, New Haven, CT;
§§Department of Health Policy and Management, Yale School of Public Health, New Haven, CT;
║║Departments of Clinical Pharmacy and Medicine, University of California San Francisco, San Francisco, CA;
¶¶Department of Internal Medicine, Universidad Central del Caribe, Bayamon, Puerto Rico;
##Department of Medicine, University of Calgary, Calgary, Alberta, Canada;
***Division of HIV/AIDS Prevention, Centers for Disease Control and Prevention, Atlanta, GA;
†††Department of Epidemiology, Johns Hopkins School of Public Health, Baltimore, MD;
‡‡‡Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD; and
§§§Department of Environmental Health Sciences, Yale School of Public Health, New Haven, CT.
Correspondence to: Elizabeth L. Yanik, PhD, ScM, 660 South Euclid Avenue, Campus Box 8233, St. Louis, MO 63110 (e-mail: firstname.lastname@example.org).
Supported by the Intramural Research Program of the National Cancer Institute; National Institutes of Health grants U01AI069918, F31DA037788, G12MD007583, K01AI093197, K23EY013707, K24AI065298, K24AI118591, K24DA000432, KL2TR000421, M01RR000052, N01CP01004, N02CP055504, N02CP91027, P30AI027757, P30AI027763, P30AI027767, P30AI036219, P30AI050410, P30AI094189, P30AI110527, P30MH62246, R01AA016893, R01CA165937, R01DA011602, R01DA012568, R01AG053100, R24AI067039, U01AA013566, U01AA020790, U01AI031834, U01AI034989, U01AI034993, U01AI034994, U01AI035004, U01AI035039, U01AI035040, U01AI035041, U01AI035042, U01AI037613, U01AI037984, U01AI038855, U01AI038858, U01AI042590, U01AI068634, U01AI068636, U01AI069432, U01AI069434, U01AI103390, U01AI103397, U01AI103401, U01AI103408, U01DA03629, U01DA036935, U01HD032632, U10EY008057, U10EY008052, U10EY008067, U24AA020794, U54MD007587, UL1RR024131, UL1TR000004, UL1TR000083, UL1TR000454, UM1AI035043, Z01CP010214, and Z01CP010176; contracts CDC-200-2006-18797 and CDC-200-2015-63931 from the Centers for Disease Control and Prevention, USA; contract 90047713 from the Agency for Healthcare Research and Quality, USA; contract 90051652 from the Health Resources and Services Administration, USA; grants CBR-86906, CBR-94036, HCP-97105, and TGF-96118 from the Canadian Institutes of Health Research, Canada; Ontario Ministry of Health and Long Term Care, Canada; and the Government of Alberta, Canada. Additional support was provided by the National Cancer Institute, National Institute for Mental Health, and National Institute on Drug Abuse. The content is soley the responsibility of the authors and does not neccessarily represent the official views of the National Institutes of Health.
The authors have no conflicts of interest to disclose.
NA-ACCORD Collaborating Cohorts and Representatives are listed in Appendix 1.
Received February 12, 2018
Accepted April 20, 2018