dc.contributor.author |
Rohr, Julia K.
|
|
dc.contributor.author |
Ive, Prudence
|
|
dc.contributor.author |
Horsburgh, C. Robert
|
|
dc.contributor.author |
Berhanu, Rebecca
|
|
dc.contributor.author |
Shearer, Kate
|
|
dc.contributor.author |
Maskew, Mhairi
|
|
dc.contributor.author |
Long, Lawrence
|
|
dc.contributor.author |
Sanne, Ian
|
|
dc.contributor.author |
Bassett, Jean
|
|
dc.contributor.author |
Ebrahim, Osman
|
|
dc.contributor.author |
Fox, Matthew P.
|
|
dc.date.accessioned |
2016-09-21T06:03:53Z |
|
dc.date.available |
2016-09-21T06:03:53Z |
|
dc.date.issued |
2016-08-22 |
|
dc.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. |
en_ZA |
dc.description |
S1 Table. Alternative stratifications for adjusted marginal structural models for hazard
ratios of death after first-line failure. |
en_ZA |
dc.description |
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). |
en_ZA |
dc.description |
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. |
en_ZA |
dc.description |
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. |
en_ZA |
dc.description.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. |
en_ZA |
dc.description.department |
Medical Microbiology |
en_ZA |
dc.description.librarian |
am2016 |
en_ZA |
dc.description.sponsorship |
JKR, 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.uri |
http://www.plosone.org |
en_ZA |
dc.identifier.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. |
en_ZA |
dc.identifier.issn |
1932-6203 |
|
dc.identifier.other |
10.1371/journal.pone.0161469 |
|
dc.identifier.uri |
http://hdl.handle.net/2263/56766 |
|
dc.language.iso |
en |
en_ZA |
dc.publisher |
Public Library of Science |
en_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.subject |
Patients |
en_ZA |
dc.subject |
CD4 Counts |
en_ZA |
dc.subject |
South African clinics |
en_ZA |
dc.subject |
Treatment |
en_ZA |
dc.subject |
Antiretroviral therapy (ART) |
en_ZA |
dc.subject |
Human immunodeficiency virus (HIV) |
en_ZA |
dc.title |
Marginal structural models to assess delays in second-line HIV treatment initiation in South Africa |
en_ZA |
dc.type |
Article |
en_ZA |