Association of CD4+ cell count and HIV viral load with risk of non-AIDS-defining cancers

Author:

Ma Yunqing1,Zhang Jiajia12,Yang Xueying23,Chen Shujie1,Weissman Sharon24,Olatosi Bankole25,Alberg Anthony1,Li Xiaoming23

Affiliation:

1. Department of Epidemiology and Biostatistics

2. South Carolina SmatState Center for Healthcare Quality

3. Department of Health Promotion, Education and Behavior

4. Department of Internal Medicine, School of Medicine

5. Department of Health Services Policy and Management, Arnold School of Public Health, University of South Carolina, Columbia, South Carolina, USA.

Abstract

Objectives: HIV-induced immunodeficiency contributes to an increased risk of non-AIDS-defining cancers (NADC). This study aims to identify the most predictive viral load (VL) or CD4+ measures of NADC risk among people with HIV (PWH). Design: Extracted from South Carolina electronic HIV reporting system, we studied adult PWH who were cancer-free at baseline and had at least 6 months of follow-up since HIV diagnosis between January 2005 and December 2020. Methods: Using multiple proportional hazards models, risk of NADC was investigated in relation to 12 measures of VL and CD4+ cell count at three different time intervals before NADC diagnosis. The best VL/CD4+ predictor(s) and final model were determined using Akaike's information criterion. Results: Among 10 413 eligible PWH, 449 (4.31%) developed at least one type of NADC. After adjusting for potential confounders, the best predictors of NADC were the proportion of days with viral suppression (hazard ratio [HR]: 0.47 (>25% and ≤50% vs. 0), 95% confidence interval [CI]: [0.28, 0.79]) and proportion of days with low CD4+ cell count (AIC = 7201.35) (HR: 12.28 (>75% vs. = 0), 95% CI: [9.29, 16.23]). Conclusions: VL and CD4+ measures are strongly associated with risk of NADC. In analyses examining three time windows, proportion of days with low CD4+ cell count was the best CD4+ predictor for each time window. However, the best VL predictor varied across time windows. Thus, using the best combination of VL and CD4+ measures for a specific time window should be considered when predicting NADC risk.

Publisher

Ovid Technologies (Wolters Kluwer Health)

Subject

Infectious Diseases,Immunology,Immunology and Allergy

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