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Five HIV Care Trajectories Seen in 15,000-Person
North Carolina Study..... Poor Engagement in Care
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HIV Research for Prevention (HIVR4P), October 17-19, 2016, Chicago
Mark Mascolini
Researchers defined 5 distinct longitudinal patterns of engagement in HIV care in an analysis of more than 15,000 people newly diagnosed with HIV infection across North Carolina [1]. Only one quarter of the study group had consistently high engagement in care, though another one third had improving engagement in care across 8 years of follow-up.
After HIV diagnosis, prompt referral to care and sustained engagement in care are essential to reaping the individual and public health benefits of antiretroviral therapy (ART). Much research in this field tracks HIV-diagnosed individuals across a continuum typically including diagnosis, referral, engagement, ART initiation, and viral suppression. With colleagues at other centers, researchers from the University of North Carolina at Chapel Hill (UNC) aimed to define differences in and predictors of engagement in care--defined as HIV care attendance trajectories--in the North Carolina HIV population.
The UNC collaborators analyzed data from the North Carolina enhanced HIV/AIDS Reporting System for everyone newly diagnosed with HIV in the state from March 2006 through March 2015. The researchers used viral load and CD4 records to indicate an HIV clinic visit. They used group-based trajectory modeling to identify 5 HIV care attendance trajectories: consistently high, early increasing, late increasing, steadily declining, and consistently low. Early increasing meant poor initial attendance but increasing attendance starting after about 2 years of care. Late increasing meant poor initial attendance with increasing attendance starting after about 4 years of care.
The 15,784-person study group had a median age of 34 years at HIV diagnosis. Three quarters of the group were not non-Hispanic white, and 79% were men who have sex with men (MSM). Only 26% of the study group maintained consistently high care across the study period. About 17% fit into the early increasing bracket and 15% into the late increasing bin. While about 16% of the cohort had steadily declining care attendance, 26% had consistently low attendance.
The researchers explored five baseline predictors of early increasing, late increasing, steadily declining, or consistently low HIV care attendance (compared with consistently high attendance): age at diagnosis, male sex, MSM (versus other HIV transmission risks), white non-Hispanic race/ethnicity, and CD4 category (under 200, 200 to 350, 350 to 500, and over 500).
In an adjusted analysis, every additional 5 years of age at diagnosis independently lowered odds of an early increasing trajectory (odds ratio [OR] 0.88, 95% confidence interval [CI] 0.86 to 0.91), a late increasing pattern (OR 0.88, 95% CI 0.85 to 0.91), steadily declining attendance (OR 0.82, 95% CI 0.79 to 0.85), and consistently low attendance (OR 0.81, 95% CI 0.78 to 0.83), compared with consistently high attendance. MSM transmission status lowered the odds of late increasing attendance (OR 0.74, 95% CI 0.62 to 0.90), steadily declining attendance (OR 0.76, 95% CI 0.62 to 0.92), and consistently low attendance (OR 0.60, 95% CI 0.51 to 0.69).
Each higher baseline CD4 bracket independently lowered the odds of early increasing attendance (OR 0.91, 95% CI 0.87 to 0.96) and late increasing attendance (OR 0.88, 95% CI 0.83 to 0.94) but raised chances of consistently low attendance (OR 1.08, 95% CI 1.02 to 1.13). Compared with women, men had almost 40% higher odds of consistently low attendance (OR 1.38, 95% CI 1.17 to 1.64). And compared with other racial/ethnic groups, non-Hispanic whites had 17% higher odds of consistently low attendance (OR 1.17, 95% CI 1.02 to 1.36).
The UNC team stressed that most people newly diagnosed with HIV in North Carolina had a suboptimal care trajectory, though about one third with initial poor clinic attendance were moving in the right direction (early increasing and late increasing attendance). The researchers proposed that this approach "can help to inform the design of HIV epidemic models and the targeting and timing of interventions, with the ultimate goal of improving HIV care engagement and HIV transmission prevention."
Reference
1. Powers K, Samoff K, Weaver M, et al. Understanding longitudinal HIV care trajectories to improve health and reduce HIV transmission in North Carolina. HIV Research for Prevention (HIVR4P 2016), October 17-19, 2016, Chicago. Abstract P09.26LB.
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