Marginal structural models to assess delays in second-line HIV treatment initiation in South Africa

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Authors

Rohr, Julia K.
Ive, Prudence
Horsburgh, C. Robert
Berhanu, Rebecca
Shearer, Kate
Maskew, Mhairi
Long, Lawrence
Sanne, Ian
Bassett, Jean
Ebrahim, Osman

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Publisher

Public Library of Science

Abstract

BACKGROUND South African HIV treatment guidelines call for patients who fail first-line antiretroviral therapy (ART) to be switched to second-line ART, yet logistical issues, clinician decisions and patient preferences make delay in switching to second-line likely. We explore the impact of delaying second-line ART after first-line treatment failure on rates of death and virologic failure. METHODS We include patients with documented virologic failure on first-line ART from an observational cohort of 9 South African clinics. We explored predictors of delayed second-line switch and used marginal structural models to analyze rates of death following first-line failure by categorical time to switch to second-line. Cox proportional hazards models were used to examine virologic failure on second-line ART among patients who switched to second- line. RESULTS 5895 patients failed first-line ART, and 63% switched to second-line. Among patients who switched, median time to switch was 3.4 months (IQR: 1.1–8.7 months). Longer time to switch was associated with higher CD4 counts, lower viral loads and more missed visits prior to first-line failure. Worse outcomes were associated with delay in second-line switch among patients with a peak CD4 count on first-line treatment 100 cells/mm3. Among these patients, marginal structural models showed increased risk of death (adjusted HR for switch in 6–12 months vs. 0–1.5 months = 1.47 (95% CI: 0.94–2.29), and Cox models showed increased rates of second-line virologic failure despite the presence of survivor bias (adjusted HR for switch in 3–6 months vs. 0–1.5 months = 2.13 (95% CI: 1.01–4.47)). CONCLUSIONS Even small delays in switch to second-line ART were associated with increased death and second-line failure among patients with low CD4 counts on first-line. There is opportunity for healthcare providers to switch patients to second-line more quickly.

Description

S1 Fig. Illustration of allocation of person time in marginal structural models. Hypothetical person time contributed to each of the 6 exposure groups in marginal structural models.
S1 Table. Alternative stratifications for adjusted marginal structural models for hazard ratios of death after first-line failure.
S2 Table. Adjusted marginal structural model hazard ratios for death after first-line failure, limiting to patients with 2 weeks to <8 months between failing viral loads on first-line (n = 4908).
S3 Table. Adjusted Cox proportional hazards ratios for alternative virologic outcomes on second-line ART, stratified by peak CD4 count prior to first-line failure.
S4 Table. Adjusted marginal structural models for hazard ratios of death after first-line failure (a) and adjusted Cox proportional hazards ratios for confirmed failure on second-line ART (b), with weighting by inverse probability of censoring after second-line switch to account for loss to follow-up.

Keywords

Patients, CD4 Counts, South African clinics, Treatment, Antiretroviral therapy (ART), Human immunodeficiency virus (HIV)

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Citation

Rohr JK, Ive P, Horsburgh CR, Berhanu R, Shearer K, Maskew M, et al. (2016) Marginal Structural Models to Assess Delays in Second-Line HIV Treatment Initiation in South Africa. PLoS ONE 11(8): e0161469. DOI: 10.1371/journal.pone.0161469.