Preexposure prophylaxis guidelines have low sensitivity for identifying seroconverters in a sample of young Black MSM in Chicago. (28th January 2018) - Lancki, Nicola; Almirol, Ellen; Alon, Leigh; McNulty, Moira; Schneider, John A.
Abstract : Background: Identification of clients at greatest risk of acquiring HIV is critical for preexposure prophylaxi (PrEP) implementation. Young black MSM (YBMSM) have high incidence of HIV. We examined published guidelines in identifying eligible PrEP candidates, including seroconverters, in a representative cohort of YBMSM. Methods: The uConnect cohort included YBMSM aged 16–29 years during PrEP roll-out in Chicago from 2013 and 2016. YBMSM with indications for PrEP were determined using Center for Disease Control and Prevention (CDC) guidelines, the HIV incidence risk index for MSM (HIRI-MSM) scoring tool, and Gilead recommendations with calculation of sensitivities, specificities, and area under the curve (AUC) for HIV seroconversion over 18 months. Incidence rate ratios (IRRs) using Poisson regression were modeled to compare individual and network factors associated with seroconversion. Results: In the study cohort, 300 HIV uninfected YBMSM contributed 390.4 person-years of follow-up [mean age (SD), 22.3 years (3.07)]. HIV incidence was 8.5 cases per 100 person-years (95% confidence interval, 6.0–11.9). One network factor was associated with seroconversion: having partners more than 10 years older (IRR = 4.4, 95% confidence interval, 1.6–11.8). Overall, 49% of the cohort had an indication for PrEP using CDC guidelines; 72% using HIRI-MSM, and 86% using Gilead recommendations. HIV seroconverters ( n = 33) were identified as PrEP eligible prior to seroconversion with sensitivities/AUCs for CDC (52%/0.51), HIRI-MSM (85%/0.57), and Gilead guidelines (94%/0.54). Conclusion: Low sensitivity of CDC guidelines and limited AUC of HIRI-MSM and Gilead screening tools are of concern for PrEP implementation among most at risk populations such as YBMSM. Consideration of demographics, local epidemiology, and network factors may better guide identification of clients who could benefit most from PrEP. Abstract : Supplemental Digital Content is available in the text