Time-Dependent Predictors of Loss to Follow-Up in a Large HIV Treatment Cohort in Nigeria
Author(s) -
Seema Meloni,
Charlotte A. Chang,
Beth Chaplin,
Holly Rawizza,
Oluwatoyin Jolayemi,
Bolanle Banigbe,
Prosper Okonkwo,
Phyllis J. Kanki
Publication year - 2014
Publication title -
open forum infectious diseases
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.546
H-Index - 35
ISSN - 2328-8957
DOI - 10.1093/ofid/ofu055
Subject(s) - medicine , viral load , attrition , psychological intervention , multivariate analysis , cohort , antiretroviral therapy , retrospective cohort study , human immunodeficiency virus (hiv) , lost to follow up , young adult , family medicine , demography , pediatrics , gerontology , nursing , dentistry , sociology
Most evaluations of loss to follow-up (LTFU) in human immunodeficiency virus (HIV) treatment programs focus on baseline predictors, prior to antiretroviral therapy (ART) initiation. As risk of LTFU is a continuous issue, the aim of this evaluation was to augment existing information with further examination of time-dependent predictors of loss.This was a retrospective evaluation of data collected between 2004 and 2012 by the Harvard School of Public Health and the AIDS Prevention Initiative in Nigeria as part of PEPFAR-funded program in Nigeria. We used multivariate modeling methods to examine associations between CD4(+) cell counts, viral load, and early adherence patterns with LTFU, defined as no refills collected for at least 2 months since the last scheduled appointment.Of 51 953 patients initiated on ART between 2004 and 2011, 14 626 (28%) were LTFU by 2012. Factors associated with increased risk for LTFU were young age, having nonincome-generating occupations or no education, being unmarried, World Health Organization (WHO) stage, having a detectable viral load, and lower CD4(+) cell counts. In a subset analysis, adherence patterns during the first 3 months of ART were associated with risk of LTFU by month 12.In settings with limited resources, early adherence patterns, as well as CD4(+) cell counts and unsuppressed viral load, at any time point in treatment are predictive of loss and serve as effective markers for developing targeted interventions to reduce rates of attrition.
Accelerating Research
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom
Address
John Eccles HouseRobert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom