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Outcomes Following Virological Failure and Predictors of Switching to Second-line Antiretroviral Therapy in a South African Treatment Program

Johnston, Victoria MBBCh, MSc*; Fielding, Katherine L. PhD*; Charalambous, Salome MBBCh, MSc; Churchyard, Gavin MBBCh, PhD*,†,‡; Phillips, Andrew PhD§; Grant, Alison D. MBBCh, MSc, PhD*

JAIDS Journal of Acquired Immune Deficiency Syndromes: November 1st, 2012 - Volume 61 - Issue 3 - p 370–380
doi: 10.1097/QAI.0b013e318266ee3f
Epidemiology and Prevention

Objectives: Without resistance tests, deciding which patients with virological failure should switch to second-line antiretroviral therapy (ART) is difficult. The factors influencing this decision are poorly understood. We assess predictors of switching regimens after virological failure.

Design: Retrospective cohort study using clinical data from a South African ART program with 6-monthly viral load (VL) monitoring.

Methods: We constructed a dataset of patient visits occurring following first-line virological failure, and used random effects logistic regression (accounting for individual-level and clinic-level clustering) to assess predictors of switching at each visit.

Results: One thousand six hundred sixty-eight patients with virological failure (73% male, mean age 41 years, median CD4 184 cells/mm3, mean log10 VL 4.3) contributed 1922 person-years of viremia. 12 months after failure, the cumulative incidence of switching regimen, viral resuppression, or death was 16.9%, 13.2%, and 4.6%, respectively. In adjusted analysis, switching was more likely at the third or subsequent visit after failure; in visits occurring in 2008 versus 2003 to 2007; and in patients with ART experience pre-programme, current high VL or low CD4 count. Switching was less likely in patients with no clinic contact for 4 months, or declining VL. Switching rates varied between clinics with clinic-level clustering evident in the final model (P <0.001).

Conclusions: Despite 6-monthly virological monitoring and recommendations to switch after adherence interventions and confirmed viremia, patients experienced delayed switching. Individual-level covariates influenced switching but did not account for variable switching rates between clinics, suggesting differences in guideline implementation. In certain circumstances delays may be warranted; however understanding barriers to guideline implementation will limit unnecessary delays.

*London School of Hygiene and Tropical Medicine, Keppel Street, London, United Kingdom

Aurum Institute, Johannesburg, South Africa

Centre for the AIDS Program of Research In South Africa, University of KwaZulu Natal, Durban, South Africa

§Department of Infection and Population Health, University College London, London, United Kingdom.

Correspondence to: Victoria Johnston, MBBCh, MSc, Department of Clinical Research, Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, Keppel Street, London, United Kingdom WC1E 7HT (e-mail:

Supported by funding provided through a Wellcome Trust Research Fellowship (VJ; Grant number 087261/Z/08/Z). The community program was funded by the US President’s Emergency Plan for AIDS Relief (Grant number 5U2GPS000811) and the workplace program by the employers.

The authors have no conflicts of interest to disclose.

Author contributions: V.J.: study design, protocol development, data collection, analysis, and article development; K.L.F.: support with study design, analysis, and review of article; S.C.: support with project implementation and review of article; G.J.C.: support with project implementation and review of article; A.P.: support with study design, analysis, and review of article; A.D.G.: support with study design, project implementation, and article development. All authors have read and approved the final article.

The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the article.

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Received March 2, 2012

Accepted June 27, 2012

© 2012 Lippincott Williams & Wilkins, Inc.