Identifying and predicting longitudinal trajectories of care for people newly diagnosed with HIV in South Africa

Abstract

Background: Predicting long-term care trajectories at the time of HIV diagnosis may allow targeted interventions. Our objective was to uncover distinct CD4-based trajectories and determine baseline demographic, clinical, and contextual factors associated with trajectory membership.

Methods: We used data from the Sizanani trial (NCT01188941), in which adults were enrolled prior to HIV testing in Durban, South Africa from August 2010-January 2013. We ascertained CD4 counts from the National Health Laboratory Service over 5y follow-up. We used group-based statistical modeling to identify groups with similar CD4 count trajectories and Bayesian information criteria to determine distinct CD4 trajectories. We evaluated baseline factors that predict membership in specific trajectories using multinomial logistic regression. We examined calendar year of participant enrollment, age, gender, cohabitation, TB positivity, self-identified barriers to care, and ART initiation within 3 months of diagnosis.

Results: 688 participants had longitudinal data available. Group-based trajectory modeling identified four distinct trajectories: one with consistently low CD4 counts (21%), one with low CD4 counts that increased over time (22%), one with moderate CD4 counts that remained stable (41%), and one with high CD4 counts that increased over time (16%). Those with higher CD4 counts at diagnosis were younger, less likely to have TB, and less likely to identify barriers to care. Those in the least favorable trajectory (consistently low CD4 count) were least likely to start ART within 3 months.

Conclusions: One-fifth of people newly-diagnosed with HIV presented with low CD4 counts that failed to rise over time. Less than 40% were in a trajectory characterized by increasing CD4 counts. Patients in more favorable trajectories were younger, less likely to have TB, and less likely to report barriers to healthcare. Better understanding barriers to early care engagement and ART initiation will be necessary to improve long-term clinical outcomes.

Fig 1. Trajectories of square root CD4 values for five years from study enrollment, as defined by group-statistical modeling. Group percentages reflect average posterior probabilities.