MOAD0304
Share
 
Title
Presenter
Authors
Institutions

Background: Retention in care is a major challenge in HIV pre-exposure prophylaxis (PrEP) implementation programs. PrEP has been offered free of charge in the Brazilian public health system since December 2017. We aimed to describe the profile of discontinued PrEP users as well as the rates and predictors of discontinuation before the first follow-up visit in the Brazilian PrEP program.
Methods: We used secondary data from the Ministry of Health of Brazil (MoH-B), including individuals admitted in the national daily dosing PrEP program, between January and December 2018. Discontinuity was defined as failing to attend the follow-up visit, with a delay (in days) of more than 40% of the expected time difference between the first consultation and the scheduled follow-up visit. Multivariable logistic regression model was used to assess the likelihood of PrEP discontinuation considering demographic and behavioral predictors.
Results: Among the 8,097 enrolled PrEP users, 821 (10%) did not attend their first follow-up visit. Median age of discontinued users was 29 years old (IQR 24-36). Young users (18 to 24 years old) were 109% more likely to discontinue PrEP (aOR 2.087, 95%CI: 1.710-2.548) and sex workers were 52% more likely to do so (aOR 1.522, 95%CI: 1.215-1.905). Compared to MSM, the odds of discontinuing PrEP was 2.233 (95%CI: 1.776-2.807) among cis women, and 1.772 (95%CI: 1.258-2.497) among transwomen. Other factors positively associated with PrEP discontinuation were living in Brazil''s North or Southeast region, compared to the South; lower education level; and clinic or NGO referral, rather than self-referral.
Conclusions: Understanding characteristics of users who are most-likely to discontinue PrEP is crucial to help health services to deliver strategies that are tailored to specific barriers to care. Enhancing education, motivation and social/psychological support during early PrEP visits may increase continuation in care and strengthen PrEP as public health policy.


Multivariable logistic regression model results for interrupting PrEP before first follow-up visit
[Multivariable logistic regression model results for interrupting PrEP before first follow-up visit]