Successes and challenges in optimizing the viral load cascade to improve antiretroviral therapy adherence and rationalize second‐line switches in Swaziland. Issue 10 (22nd October 2018)

• Record Type: Journal Article
• Authors: Etoori, David; Ciglenecki, Iza; Ndlangamandla, Mpumelelo; Edwards, Celeste G; Jobanputra, Kiran; Pasipamire, Munyaradzi; Maphalala, Gugu; Yang, Chunfu; Zabsonre, Inoussa; Kabore, Serge M; Goiri, Javier; Teck, Roger; Kerschberger, Bernhard
• Is Part Of: Journal of the International AIDS Society. Volume 21:Issue 10(2018)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2018-10-22
• Subjects: viral load -- ART -- treatment monitoring -- treatment switching -- genotyping; AIDS (Disease) -- Periodicals; HIV infections -- Periodicals; 616.9792005
• DOI: 10.1002/jia2.25194
• Languages: English
• ISSNs: 1758-2652

Abstract

Abstract: Introduction: As antiretroviral therapy (ART) is scaled up, more patients become eligible for routine viral load (VL) monitoring, the most important tool for monitoring ART efficacy. For HIV programmes to become effective, leakages along the VL cascade need to be minimized and treatment switching needs to be optimized. However, many HIV programmes in resource‐constrained settings report significant shortfalls. Methods: From a public sector HIV programme in rural Swaziland, we evaluated the VL cascade of adults (≥18 years) on ART from the time of the first elevated VL (>1000 copies/mL) between January 2013 and June 2014 to treatment switching by December 2015. We additionally described HIV drug resistance for patients with virological failure. We used descriptive statistics and Kaplan–Meier estimates to describe the different steps along the cascade and regression models to determine factors associated with outcomes. Results and Discussion: Of 828 patients with a first elevated VL, 252 (30.4%) did not receive any enhanced adherence counselling (EAC). Six hundred and ninety‐six (84.1%) patients had a follow‐up VL measurement, and the predictors of receiving a follow‐up VL were being a second‐line patient (adjusted hazard ratio (aHR): 0.72; p = 0.051), Hlathikhulu health zone (aHR: 0.79; p = 0.013) and having received two EAC sessions (aHR: 1.31; p = 0.023). Four hundred and ten patients (58.9%) achieved VL re‐suppression. Predictors of re‐suppression were age 50 to 64 (adjusted odds ratio (aOR): 2.02; p = 0.015) compared with age 18 to 34 years, being on second‐line treatment (aOR: 3.29; p = 0.003) and two (aOR: 1.66; p = 0.045) or three (aOR: 1.86; p = 0.003) EAC sessions. Of 278 patients eligible to switch to second‐line therapy, 120 (43.2%) had switched by the end of the study. Finally, of 155 successfully sequenced dried blood spots, 144 (92.9%) were from first‐line patients. Of these, 133 (positive predictive value: 92.4%) had resistance patterns that necessitated treatment switching. Conclusions: Patients on ART with high VLs were more likely to re‐suppress if they received EAC. Failure to re‐suppress after counselling was predictive of genotypically confirmed resistance patterns requiring treatment switching. Delays in switching were significant despite the ability of the WHO algorithm to predict treatment failure. Despite significant progress in recent years, enhanced focus on quality care along the VL cascade in resource‐limited settings is crucial.