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Objectives: To report predictors of outcomes of second-line ART for HIV treatment in a resource-limited setting.Methods: All adult ART-naïve patients who initiated standard first-line treatment between April 2004 and February 2012 at four public-sector health facilities in Johannesburg, South Africa, experienced virologic failure and initiated standard second-line therapy were included. We assessed predictors of attrition (death and loss to follow-up [≥3 months late for a scheduled visit]) using Cox proportional hazards regression and predictors of virologic suppression (viral load <400 copies/ml ≥3 months after switch) using modified Poisson regression with robust error estimation at 1 year and ever after second-line ART initiation.Results: A total of 1236 patients switched to second-line treatment in a median (IQR) of 1.9 (0.9-4.6) months after first-line virologic failure. Approximately 13% and 45% of patients were no longer in care at 1 year and at the end of follow-up, respectively. Patients with low CD4 counts (<50 vs. ≥200, aHR: 1.85; 95% CI: 1.03-3.32) at second-line switch were at greater risk for attrition by the end of follow-up. About 75% of patients suppressed by 1 year, and 85% had ever suppressed by the end of follow-up.Conclusions: Patients with poor immune status at switch to second-line ART were at greater risk of attrition and were less likely to suppress. Additional adherence support after switch may improve outcomes. [ABSTRACT FROM AUTHOR]

Introduction: Several studies from resource-limited settings have demonstrated that clinical and immunologic criteria are poor predictors of virologic failure, confirming the need for viral load monitoring or at least an algorithm to target viral load testing. We used data from an electronic patient management system to develop an algorithm to identify patients at risk of viral failure using a combination of accessible and inexpensive markers.Methods: We analyzed data from HIV-positive adults initiated on antiretroviral therapy (ART) in Johannesburg, South Africa, between April 2004 and February 2010. Viral failure was defined as ≥2 consecutive HIV-RNA viral loads >400 copies/ml following suppression ≤400 copies/ml. We used Cox-proportional hazards models to calculate hazard ratios (HR) and 95% confidence intervals (CI). Weights for each predictor associated with virologic failure were created as the sum of the natural logarithm of the adjusted HR and dichotomized with the optimal cut-off at the point with the highest sensitivity and specificity (i.e. ≤4 vs. >4). We assessed the diagnostic accuracy of predictor scores cut-offs, with and without CD4 criteria (CD4 <100 cells/mm3; CD4 < baseline; >30% drop in CD4), by calculating the proportion with the outcome and the observed sensitivity, specificity, positive and negative predictive value of the predictor score compared to the gold standard of virologic failure.Results: We matched 919 patients with virologic failure (1:3) to 2756 patients without. Our predictor score included variables at ART initiation (i.e. gender, age, CD4 count <100 cells/mm3, WHO stage III/IV and albumin) and laboratory and clinical follow-up data (drop in haemoglobin, mean cell volume (MCV) <100 fl, CD4 count <200 cells/mm3, new or recurrent WHO stage III/IV condition, diagnosis of new condition or symptom and regimen change). Overall, 51.4% had a score 51.4% had a score ≥4 and 48.6% had a score <4. A predictor score including CD4 criteria performed better than a score without CD4 criteria and better than WHO clinico-immunological criteria or WHO clinical staging to predict virologic failure (sensitivity 57.1% vs. 40.9%, 25.2% and 20.9%, respectively).Conclusions:Predictor scores or risk categories, with CD4 criteria, could be used to identify patients at risk of virologic failure in resource-limited settings so that these patients may be targeted for focused interventions to improve HIV treatment outcomes. [ABSTRACT FROM AUTHOR]

Objective: In resource-limited settings, where genotypic drug resistance testing is rarely performed and poor adherence is the most common reason for treatment failure, programmatic approaches to handling treatment failure are essential. This study was performed to describe one such approach to adherence optimisation.Methods: This was a single-arm study of patients on second-line protease inhibitor (PI)-based antiretroviral therapy (ART) with a HIV-1 RNA ≥400 copies/ml in Johannesburg, South Africa, between 1 March 2012 and 1 December 2013. Patients underwent enhanced adherence counselling. Those with improved adherence and a repeat viral load of >1000 copies/ml underwent HIV-1 drug resistance testing. We describe results using simple proportions and 95% confidence intervals.Results: Of the 400 patients who underwent targeted adherence counselling after an elevated viral load on second-line ART, 388 (97%) underwent repeat viral load testing. Most of these (n = 249; 64%, 95% CI 59-69) resuppressed (<400 copies/ml) on second line. By the end of follow-up (1 March 2014), among the 139 (36%, 95% CI: 31-41%), who did not initially resuppress after being targeted, 106 had a viral load >400 copies/ml, 11 switched to third line, 5 were awaiting third line, 4 had died and 13 were lost to follow-up. Among the unsuppressed, 48 successfully underwent resistance testing with some resistance detected in most (41/48).Conclusions: Most (64%) second-line treatment failure in this clinic is related to adherence and can be overcome with careful adherence support. Controlled interventions are needed to determine what the optimal approach is to improving second-line outcomes and reducing the need for third-line ART. [ABSTRACT FROM AUTHOR]