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

dc.contributor.authorRohr, Julia K.
dc.contributor.authorIve, Prudence
dc.contributor.authorHorsburgh, C. Robert
dc.contributor.authorBerhanu, Rebecca
dc.contributor.authorShearer, Kate
dc.contributor.authorMaskew, Mhairi
dc.contributor.authorLong, Lawrence
dc.contributor.authorSanne, Ian
dc.contributor.authorBassett, Jean
dc.contributor.authorEbrahim, Osman
dc.contributor.authorFox, Matthew P.
dc.date.accessioned2016-09-21T06:03:53Z
dc.date.available2016-09-21T06:03:53Z
dc.date.issued2016-08-22
dc.descriptionS1 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.en_ZA
dc.descriptionS1 Table. Alternative stratifications for adjusted marginal structural models for hazard ratios of death after first-line failure.en_ZA
dc.descriptionS2 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).en_ZA
dc.descriptionS3 Table. Adjusted Cox proportional hazards ratios for alternative virologic outcomes on second-line ART, stratified by peak CD4 count prior to first-line failure.en_ZA
dc.descriptionS4 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.en_ZA
dc.description.abstractBACKGROUND 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.en_ZA
dc.description.departmentMedical Microbiologyen_ZA
dc.description.librarianam2016en_ZA
dc.description.sponsorshipJKR, KS, MM, LL and MPF were funded for this work by United States Agency for International Development (USAID) through the following agreement: 674-A-12-00029. Additional support to KS was provided by the National Institutes of Health (NIH) (T32AI102623).en_ZA
dc.description.urihttp://www.plosone.orgen_ZA
dc.identifier.citationRohr 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.en_ZA
dc.identifier.issn1932-6203
dc.identifier.other10.1371/journal.pone.0161469
dc.identifier.urihttp://hdl.handle.net/2263/56766
dc.language.isoenen_ZA
dc.publisherPublic Library of Scienceen_ZA
dc.rights© 2016 Rohr et al. This is an open access article distributed under the terms of the Creative Commons Attribution License.en_ZA
dc.subjectPatientsen_ZA
dc.subjectCD4 Countsen_ZA
dc.subjectSouth African clinicsen_ZA
dc.subjectTreatmenten_ZA
dc.subjectAntiretroviral therapy (ART)en_ZA
dc.subjectHuman immunodeficiency virus (HIV)en_ZA
dc.titleMarginal structural models to assess delays in second-line HIV treatment initiation in South Africaen_ZA
dc.typeArticleen_ZA

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