title: Are Centers for Disease Control and Prevention Guidelines for Preexposure Prophylaxis Specific Enough? Formulation of a Personalized HIV Risk Score for Pre-Exposure Prophylaxis Initiation.
abstract: Preexposure prophylaxis (PrEP) has emerged as a human immunodeficiency virus (HIV) prevention tool for populations at highest risk for HIV infection. Current US Centers for Disease Control and Prevention (CDC) guidelines for identifying PrEP candidates may not be specific enough to identify gay, bisexual, and other men who have sex with men (MSM) at the highest risk for HIV infection. We created an HIV risk score for HIV-negative MSM based on Syndemics Theory to develop a more targeted criterion for assessing PrEP candidacy.
  
  
  
  Behavioral risk assessment and HIV testing data were analyzed for HIV-negative MSM attending the Los Angeles LGBT Center between January 2009 and June 2014 (n = 9481). Syndemics Theory informed the selection of variables for a multivariable Cox proportional hazards model. Estimated coefficients were summed to create an HIV risk score, and model fit was compared between our model and CDC guidelines using the Akaike Information Criterion and Bayesian Information Criterion.
  
  
  
  Approximately 51% of MSM were above a cutpoint that we chose as an illustrative risk score to qualify for PrEP, identifying 75% of all seroconverting MSM. Our model demonstrated a better overall fit when compared with the CDC guidelines (Akaike Information Criterion Difference = 68) in addition to identifying a greater proportion of HIV infections.
  
  
  
  Current CDC PrEP guidelines should be expanded to incorporate substance use, partner-level, and other Syndemic variables that have been shown to contribute to HIV acquisition. Deployment of such personalized algorithms may better hone PrEP criteria and allow providers and their patients to make a more informed decision prior to PrEP use.
authors.affiliation: From the *Los Angeles LGBT Center; †Division of Infectious Diseases, David Geffen School of Medicine, ‡Department of Biostatistics, Fielding School of Public Health, §Department of Community Health Sciences, Fielding School of Public Health, ¶Anderson School of Business, and ∥Department of Epidemiology, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA.
authors.forename: Matthew R
authors.initials: MR
authors.lastname: Beymer
authors.forename: Robert E
authors.initials: RE
authors.lastname: Weiss
authors.forename: Catherine A
authors.initials: CA
authors.lastname: Sugar
authors.forename: Linda B
authors.initials: LB
authors.lastname: Bourque
authors.forename: Gilbert C
authors.initials: GC
authors.lastname: Gee
authors.forename: Donald E
authors.initials: DE
authors.lastname: Morisky
authors.forename: Suzanne B
authors.initials: SB
authors.lastname: Shu
authors.forename: Marjan
authors.initials: M
authors.lastname: Javanbakht
authors.forename: Robert K
authors.initials: RK
authors.lastname: Bolan
mesh_terms: D000328:Adult; D001499:Bayes Theorem; D002487:Centers for Disease Control and Prevention, U.S. / Q000592:standards*; D015658:HIV Infections / Q000517:prevention & control*; D006801:Humans; D008297:Male; D017410:Practice Guidelines as Topic; D065129:Pre-Exposure Prophylaxis / Q000592:standards*; D057285:Precision Medicine / Q000379:methods / Q000592:standards*; D016016:Proportional Hazards Models; D018570:Risk Assessment / Q000379:methods / Q000592:standards*; D014481:United States