994. Risk for Viral Rebound in the Era of U=U; A CNICS Analysis

BACKGROUND: The “Undetectable equals Untransmittable (U=U)” HIV prevention campaign is a cornerstone of HIV prevention. However, there are few recommendations to guide patients and providers in U=U implementation and limited data on risk factors for viral rebound among persons eligible for U=U. METHODS: We conducted a retrospective multi-center study using data from the CNICS HIV research network to identify risk factors for viral rebound among persons with established viral suppression [two viral loads (VL) and all VLs of < 200 copies/ul within a one-year period (U=U eligible)]. Demographics, patient-reported outcomes, and longitudinal clinical data from 21,359 persons with HIV were analyzed. To include missing data in the analysis, they were treated as a separate category. The primary outcome of viral rebound was defined as any VL > 200 copies/ul within two years after U=U eligibility. A univariable logistic regression model was conducted to identify predictors of viral rebound. Significant variables (p< 0.05) were included in a multivariable logistic regression model. Predictive values of individual variables were captured by adjusted odds ratios (aORs). RESULTS: From 2011-2019, 12,150 patients met criteria for U=U eligibility and had two years of follow up data. The median age was 46 (IQR: 38-53); 68% male; 51% were white, 39% black. 1544 (13%) experienced viral rebound during follow-up. Forest plot summaries of univariable and multivariable logistic regression models are in Figures 1&2. In multivariable analysis, Black race (aOR=1.56, p< 0.001); MSM-IDU risk (aOR=1.38, p=0.006); lower QoL score (aOR=1.49, p=0.005); poorer ART adherence (aOR=1.84, p< 0.001); duration of lifetime ART [aOR=1.47 (10+yrs), = 1.37 (5-10 yrs); and = 1.28 (2-5 yrs), p< 0.001]; use of InSTIs after eligibility (aOR=1.60, p< 0.001); current smoker (aOR=1.49, p< 0.001), current amphetamine (aOR=1.83, p< 0.001) or cocaine use (aOR=1.46, p=0.012), were associated with viral rebound. In both analyses, older age was protective against viral rebound. Figure 1. Summary of Univariate Logistic Regression Model [Image: see text] Figure 2. Summary of Multivariable Logistic Regression Model [Image: see text] CONCLUSION: We identified multiple risk factors for viral rebound among PWH with viral suppression. Further research is needed to identify synergistic risk factors that increase probability of viral rebound to inform optimal implementation of U=U. DISCLOSURES: Edward Cachay, MD, MAS, Gilead (Consultant, Grant/Research Support)Merck Sciences (Grant/Research Support) Heidi Crane, MD, MPH, ViiV (Grant/Research Support) Benigno Rodriguez, MD, Gilead (Speaker’s Bureau)ViiV (Speaker’s Bureau)