Raúl U Hernández-Ramírez1, Li Qin2, Haiqun Lin3, Wendy Leyden4, Romain S Neugebauer4, Keri N Althoff5, Nancy A Hessol6, Chad J Achenbach7, John T Brooks8, M John Gill9, Surbhi Grover10, Michael A Horberg11, Jun Li12, W Christopher Mathews13, Angel M Mayor14, Pragna Patel8, Charles S Rabkin15, Anita Rachlis16, Amy C Justice2,17,18, Richard D Moore19, Eric A Engels15, Michael J Silverberg4, Robert Dubrow20. 1. Department of Chronic Disease Epidemiology, Yale School of Public Health, Yale School of Medicine, New Haven, Connecticut. 2. Department of Internal Medicine, Yale School of Medicine, New Haven, Connecticut. 3. Department of Biostatistics, Yale School of Public Health, Yale School of Medicine, New Haven, Connecticut. 4. Division of Research, Kaiser Permanente Northern California, Oakland. 5. Department of Epidemiology, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland. 6. Department of Clinical Pharmacy, University of California, San Francisco. 7. Division of Infectious Diseases, Northwestern University Feinberg School of Medicine, Chicago, Illinois. 8. Division of HIV/AIDS Prevention, Centers for Disease Control and Prevention, Atlanta, Georgia. 9. Department of Medicine, University of Calgary, Alberta, Canada. 10. Department of Radiation Oncology, University of Pennsylvania Perelman School of Medicine, Philadelphia. 11. Mid-Atlantic Permanente Research Institute, Kaiser Permanente Mid-Atlantic States, Rockville, Maryland. 12. Epidemiology Branch, Division of HIV/AIDS Prevention, Centers for Disease Control and Prevention, Atlanta, Georgia. 13. Department of Medicine, University of California, San Diego. 14. Retrovirus Research Center, Department of Medicine, Universidad Central del Caribe School of Medicine, Bayamon, Puerto Rico. 15. Infections and Immunoepidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, Maryland. 16. Sunnybrook Health Sciences Centre and Department of Medicine, University of Toronto, Ontario, Canada. 17. Department of Health Policy and Management, Yale School of Public Health, Yale School of Medicine, New Haven, Connecticut. 18. Research Service, Veterans Affairs Connecticut Healthcare System, West Haven. 19. Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland. 20. Department of Environmental Health Sciences, Yale School of Public Health, Yale School of Medicine, New Haven, Connecticut.
Abstract
BACKGROUND: People living with human immunodeficiency virus (HIV; PLWH) have a markedly elevated anal cancer risk, largely due to loss of immunoregulatory control of oncogenic human papillomavirus infection. To better understand anal cancer development and prevention, we determined whether recent, past, cumulative, or nadir/peak CD4+ T-cell count (CD4) and/or HIV-1 RNA level (HIV RNA) best predict anal cancer risk. METHODS: We studied 102 777 PLWH during 1996-2014 from 21 cohorts participating in the North American AIDS Cohort Collaboration on Research and Design. Using demographics-adjusted, cohort-stratified Cox models, we assessed associations between anal cancer risk and various time-updated CD4 and HIV RNA measures, including cumulative and nadir/peak measures during prespecified moving time windows. We compared models using the Akaike information criterion. RESULTS: Cumulative and nadir/peak CD4 or HIV RNA measures from approximately 8.5 to 4.5 years in the past were generally better predictors for anal cancer risk than their corresponding more recent measures. However, the best model included CD4 nadir (ie, the lowest CD4) from approximately 8.5 years to 6 months in the past (hazard ratio [HR] for <50 vs ≥500 cells/µL, 13.4; 95% confidence interval [CI], 3.5-51.0) and proportion of time CD4 <200 cells/µL from approximately 8.5 to 4.5 years in the past (a cumulative measure; HR for 100% vs 0%, 3.1; 95% CI, 1.5-6.6). CONCLUSIONS: Our results are consistent with anal cancer promotion by severe, prolonged HIV-induced immunosuppression. Nadir and cumulative CD4 may represent useful markers for identifying PLWH at higher anal cancer risk.
BACKGROUND:People living with human immunodeficiency virus (HIV; PLWH) have a markedly elevated anal cancer risk, largely due to loss of immunoregulatory control of oncogenic human papillomavirus infection. To better understand anal cancer development and prevention, we determined whether recent, past, cumulative, or nadir/peak CD4+ T-cell count (CD4) and/or HIV-1 RNA level (HIV RNA) best predict anal cancer risk. METHODS: We studied 102 777 PLWH during 1996-2014 from 21 cohorts participating in the North American AIDS Cohort Collaboration on Research and Design. Using demographics-adjusted, cohort-stratified Cox models, we assessed associations between anal cancer risk and various time-updated CD4 and HIV RNA measures, including cumulative and nadir/peak measures during prespecified moving time windows. We compared models using the Akaike information criterion. RESULTS: Cumulative and nadir/peak CD4 or HIV RNA measures from approximately 8.5 to 4.5 years in the past were generally better predictors for anal cancer risk than their corresponding more recent measures. However, the best model included CD4 nadir (ie, the lowest CD4) from approximately 8.5 years to 6 months in the past (hazard ratio [HR] for <50 vs ≥500 cells/µL, 13.4; 95% confidence interval [CI], 3.5-51.0) and proportion of time CD4 <200 cells/µL from approximately 8.5 to 4.5 years in the past (a cumulative measure; HR for 100% vs 0%, 3.1; 95% CI, 1.5-6.6). CONCLUSIONS: Our results are consistent with anal cancer promotion by severe, prolonged HIV-induced immunosuppression. Nadir and cumulative CD4 may represent useful markers for identifying PLWH at higher anal cancer risk.
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