Adherence to Drug-Refill Is a Useful Early Warning Indicator of Virologic and Immunologic Failure among HIV Patients on First-Line ART in South Africa
Identifieur interne : 002B55 ( Pmc/Corpus ); précédent : 002B54; suivant : 002B56Adherence to Drug-Refill Is a Useful Early Warning Indicator of Virologic and Immunologic Failure among HIV Patients on First-Line ART in South Africa
Auteurs : Ziad El-Khatib ; David Katzenstein ; Gaetano Marrone ; Fatima Laher ; Lerato Mohapi ; Max Petzold ; Lynn Morris ; Anna Mia EkströmSource :
- PLoS ONE [ 1932-6203 ] ; 2011.
Abstract
Affordable strategies to prevent treatment failure on first-line regimens among HIV patients are essential for the long-term success of antiretroviral therapy (ART) in sub-Saharan Africa. WHO recommends using routinely collected data such as adherence to drug-refill visits as early warning indicators. We examined the association between adherence to drug-refill visits and long-term virologic and immunologic failure among non-nucleoside reverse transcriptase inhibitor (NNRTI) recipients in South Africa.
In 2008, 456 patients on NNRTI-based ART for a median of 44 months (range 12–99 months; 1,510 person-years) were enrolled in a retrospective cohort study in Soweto. Charts were reviewed for clinical characteristics before and during ART. Multivariable logistic regression and Kaplan-Meier survival analysis assessed associations with virologic (two repeated VL>50 copies/ml) and immunologic failure (as defined by WHO).
After a median of 15 months on ART, 19% (n = 88) and 19% (n = 87) had failed virologically and immunologically respectively. A cumulative adherence of <95% to drug-refill visits was significantly associated with both virologic and immunologic failure (p<0.01). In the final multivariable model, risk factors for virologic failure were incomplete adherence (OR 2.8, 95%CI 1.2–6.7), and previous exposure to single-dose nevirapine or any other antiretrovirals (adj. OR 2.1, 95%CI 1.2–3.9), adjusted for age and sex. In Kaplan-Meier analysis, the virologic failure rate by month 48 was 19% vs. 37% among adherent and non-adherent patients respectively (logrank p value = 0.02).
One in five failed virologically after a median of 15 months on ART. Adherence to drug-refill visits works as an early warning indicator for both virologic and immunologic failure.
Url:
DOI: 10.1371/journal.pone.0017518
PubMed: 21408071
PubMed Central: 3052314
Links to Exploration step
PMC:3052314Le document en format XML
<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">Adherence to Drug-Refill Is a Useful Early Warning Indicator of
Virologic and Immunologic Failure among HIV Patients on First-Line ART in South
Africa</title><author><name sortKey="El Khatib, Ziad" sort="El Khatib, Ziad" uniqKey="El Khatib Z" first="Ziad" last="El-Khatib">Ziad El-Khatib</name><affiliation><nlm:aff id="aff1"><addr-line>Division of Global Health (IHCAR), Karolinska Institutet, Stockholm, Sweden</addr-line></nlm:aff></affiliation><affiliation><nlm:aff id="aff2"><addr-line>AIDS Virus Research Unit, National Institute for Communicable Diseases (NICD), Johannesburg, South Africa</addr-line></nlm:aff></affiliation></author><author><name sortKey="Katzenstein, David" sort="Katzenstein, David" uniqKey="Katzenstein D" first="David" last="Katzenstein">David Katzenstein</name><affiliation><nlm:aff id="aff3"><addr-line>Division of Infectious Diseases, Stanford University, Palo Alto, California, United States of America</addr-line></nlm:aff></affiliation></author><author><name sortKey="Marrone, Gaetano" sort="Marrone, Gaetano" uniqKey="Marrone G" first="Gaetano" last="Marrone">Gaetano Marrone</name><affiliation><nlm:aff id="aff1"><addr-line>Division of Global Health (IHCAR), Karolinska Institutet, Stockholm, Sweden</addr-line></nlm:aff></affiliation></author><author><name sortKey="Laher, Fatima" sort="Laher, Fatima" uniqKey="Laher F" first="Fatima" last="Laher">Fatima Laher</name><affiliation><nlm:aff id="aff4"><addr-line>Perinatal HIV Research Unit (PHRU), University of the Witwatersrand, Soweto, South Africa</addr-line></nlm:aff></affiliation></author><author><name sortKey="Mohapi, Lerato" sort="Mohapi, Lerato" uniqKey="Mohapi L" first="Lerato" last="Mohapi">Lerato Mohapi</name><affiliation><nlm:aff id="aff4"><addr-line>Perinatal HIV Research Unit (PHRU), University of the Witwatersrand, Soweto, South Africa</addr-line></nlm:aff></affiliation></author><author><name sortKey="Petzold, Max" sort="Petzold, Max" uniqKey="Petzold M" first="Max" last="Petzold">Max Petzold</name><affiliation><nlm:aff id="aff1"><addr-line>Division of Global Health (IHCAR), Karolinska Institutet, Stockholm, Sweden</addr-line></nlm:aff></affiliation><affiliation><nlm:aff id="aff5"><addr-line>Nordic School of Public Health (NHV), Gothenburg, Sweden</addr-line></nlm:aff></affiliation></author><author><name sortKey="Morris, Lynn" sort="Morris, Lynn" uniqKey="Morris L" first="Lynn" last="Morris">Lynn Morris</name><affiliation><nlm:aff id="aff2"><addr-line>AIDS Virus Research Unit, National Institute for Communicable Diseases (NICD), Johannesburg, South Africa</addr-line></nlm:aff></affiliation></author><author><name sortKey="Ekstrom, Anna Mia" sort="Ekstrom, Anna Mia" uniqKey="Ekstrom A" first="Anna Mia" last="Ekström">Anna Mia Ekström</name><affiliation><nlm:aff id="aff1"><addr-line>Division of Global Health (IHCAR), Karolinska Institutet, Stockholm, Sweden</addr-line></nlm:aff></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">PMC</idno><idno type="pmid">21408071</idno><idno type="pmc">3052314</idno><idno type="url">http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3052314</idno><idno type="RBID">PMC:3052314</idno><idno type="doi">10.1371/journal.pone.0017518</idno><date when="2011">2011</date><idno type="wicri:Area/Pmc/Corpus">002B55</idno><idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Corpus" wicri:corpus="PMC">002B55</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en" level="a" type="main">Adherence to Drug-Refill Is a Useful Early Warning Indicator of
Virologic and Immunologic Failure among HIV Patients on First-Line ART in South
Africa</title><author><name sortKey="El Khatib, Ziad" sort="El Khatib, Ziad" uniqKey="El Khatib Z" first="Ziad" last="El-Khatib">Ziad El-Khatib</name><affiliation><nlm:aff id="aff1"><addr-line>Division of Global Health (IHCAR), Karolinska Institutet, Stockholm, Sweden</addr-line></nlm:aff></affiliation><affiliation><nlm:aff id="aff2"><addr-line>AIDS Virus Research Unit, National Institute for Communicable Diseases (NICD), Johannesburg, South Africa</addr-line></nlm:aff></affiliation></author><author><name sortKey="Katzenstein, David" sort="Katzenstein, David" uniqKey="Katzenstein D" first="David" last="Katzenstein">David Katzenstein</name><affiliation><nlm:aff id="aff3"><addr-line>Division of Infectious Diseases, Stanford University, Palo Alto, California, United States of America</addr-line></nlm:aff></affiliation></author><author><name sortKey="Marrone, Gaetano" sort="Marrone, Gaetano" uniqKey="Marrone G" first="Gaetano" last="Marrone">Gaetano Marrone</name><affiliation><nlm:aff id="aff1"><addr-line>Division of Global Health (IHCAR), Karolinska Institutet, Stockholm, Sweden</addr-line></nlm:aff></affiliation></author><author><name sortKey="Laher, Fatima" sort="Laher, Fatima" uniqKey="Laher F" first="Fatima" last="Laher">Fatima Laher</name><affiliation><nlm:aff id="aff4"><addr-line>Perinatal HIV Research Unit (PHRU), University of the Witwatersrand, Soweto, South Africa</addr-line></nlm:aff></affiliation></author><author><name sortKey="Mohapi, Lerato" sort="Mohapi, Lerato" uniqKey="Mohapi L" first="Lerato" last="Mohapi">Lerato Mohapi</name><affiliation><nlm:aff id="aff4"><addr-line>Perinatal HIV Research Unit (PHRU), University of the Witwatersrand, Soweto, South Africa</addr-line></nlm:aff></affiliation></author><author><name sortKey="Petzold, Max" sort="Petzold, Max" uniqKey="Petzold M" first="Max" last="Petzold">Max Petzold</name><affiliation><nlm:aff id="aff1"><addr-line>Division of Global Health (IHCAR), Karolinska Institutet, Stockholm, Sweden</addr-line></nlm:aff></affiliation><affiliation><nlm:aff id="aff5"><addr-line>Nordic School of Public Health (NHV), Gothenburg, Sweden</addr-line></nlm:aff></affiliation></author><author><name sortKey="Morris, Lynn" sort="Morris, Lynn" uniqKey="Morris L" first="Lynn" last="Morris">Lynn Morris</name><affiliation><nlm:aff id="aff2"><addr-line>AIDS Virus Research Unit, National Institute for Communicable Diseases (NICD), Johannesburg, South Africa</addr-line></nlm:aff></affiliation></author><author><name sortKey="Ekstrom, Anna Mia" sort="Ekstrom, Anna Mia" uniqKey="Ekstrom A" first="Anna Mia" last="Ekström">Anna Mia Ekström</name><affiliation><nlm:aff id="aff1"><addr-line>Division of Global Health (IHCAR), Karolinska Institutet, Stockholm, Sweden</addr-line></nlm:aff></affiliation></author></analytic><series><title level="j">PLoS ONE</title><idno type="eISSN">1932-6203</idno><imprint><date when="2011">2011</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><sec><title>Background</title><p>Affordable strategies to prevent treatment failure on first-line regimens
among HIV patients are essential for the long-term success of antiretroviral
therapy (ART) in sub-Saharan Africa. WHO recommends using routinely
collected data such as adherence to drug-refill visits as early warning
indicators. We examined the association between adherence to drug-refill
visits and long-term virologic and immunologic failure among non-nucleoside
reverse transcriptase inhibitor (NNRTI) recipients in South Africa.</p></sec><sec><title>Methods</title><p>In 2008, 456 patients on NNRTI-based ART for a median of 44 months (range
12–99 months; 1,510 person-years) were enrolled in a retrospective
cohort study in Soweto. Charts were reviewed for clinical characteristics
before and during ART. Multivariable logistic regression and Kaplan-Meier
survival analysis assessed associations with virologic (two repeated
VL>50 copies/ml) and immunologic failure (as defined by WHO).</p></sec><sec><title>Results</title><p>After a median of 15 months on ART, 19% (n = 88)
and 19% (n = 87) had failed virologically and
immunologically respectively. A cumulative adherence of <95% to
drug-refill visits was significantly associated with both virologic and
immunologic failure (p<0.01). In the final multivariable model, risk
factors for virologic failure were incomplete adherence (OR 2.8,
95%CI 1.2–6.7), and previous exposure to single-dose nevirapine
or any other antiretrovirals (adj. OR 2.1, 95%CI 1.2–3.9),
adjusted for age and sex. In Kaplan-Meier analysis, the virologic failure
rate by month 48 was 19% vs. 37% among adherent and
non-adherent patients respectively (logrank p
value = 0.02).</p></sec><sec><title>Conclusion</title><p>One in five failed virologically after a median of 15 months on ART.
Adherence to drug-refill visits works as an early warning indicator for both
virologic and immunologic failure.</p></sec></div></front><back><div1 type="bibliography"><listBibl><biblStruct></biblStruct><biblStruct><analytic><author><name sortKey="Harries, Ad" uniqKey="Harries A">AD Harries</name></author><author><name sortKey="Zachariah, R" uniqKey="Zachariah R">R Zachariah</name></author><author><name sortKey="Van Oosterhout, Jj" uniqKey="Van Oosterhout J">JJ van Oosterhout</name></author><author><name sortKey="Reid, Sd" uniqKey="Reid S">SD Reid</name></author><author><name sortKey="Hosseinipour, Mc" uniqKey="Hosseinipour M">MC Hosseinipour</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Simon, V" uniqKey="Simon V">V Simon</name></author><author><name sortKey="Ho, Dd" uniqKey="Ho D">DD Ho</name></author><author><name sortKey="Karim, Qa" uniqKey="Karim Q">QA Karim</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Kuritzkes, Dr" uniqKey="Kuritzkes D">DR 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<front><journal-meta><journal-id journal-id-type="nlm-ta">PLoS One</journal-id><journal-id journal-id-type="publisher-id">plos</journal-id><journal-id journal-id-type="pmc">plosone</journal-id><journal-title-group><journal-title>PLoS ONE</journal-title></journal-title-group><issn pub-type="epub">1932-6203</issn><publisher><publisher-name>Public Library of Science</publisher-name><publisher-loc>San Francisco, USA</publisher-loc></publisher></journal-meta><article-meta><article-id pub-id-type="pmid">21408071</article-id><article-id pub-id-type="pmc">3052314</article-id><article-id pub-id-type="publisher-id">PONE-D-10-05154</article-id><article-id pub-id-type="doi">10.1371/journal.pone.0017518</article-id><article-categories><subj-group subj-group-type="heading"><subject>Research Article</subject></subj-group><subj-group subj-group-type="Discipline-v2"><subject>Biology</subject><subj-group><subject>Microbiology</subject><subj-group><subject>Virology</subject><subj-group><subject>Antivirals</subject></subj-group></subj-group></subj-group></subj-group><subj-group subj-group-type="Discipline-v2"><subject>Medicine</subject><subj-group><subject>Clinical Research Design</subject><subj-group><subject>Cohort Studies</subject><subject>Retrospective Studies</subject></subj-group></subj-group><subj-group><subject>Epidemiology</subject><subj-group><subject>Infectious Disease Epidemiology</subject></subj-group></subj-group><subj-group><subject>Global Health</subject></subj-group><subj-group><subject>Infectious Diseases</subject><subj-group><subject>Sexually Transmitted Diseases</subject><subj-group><subject>AIDS</subject></subj-group></subj-group><subj-group><subject>Viral Diseases</subject><subj-group><subject>HIV</subject><subj-group><subject>HIV diagnosis and management</subject><subject>HIV epidemiology</subject><subject>HIV opportunistic infections</subject><subject>Retrovirology and HIV immunopathogenesis</subject></subj-group></subj-group></subj-group></subj-group><subj-group><subject>Non-Clinical Medicine</subject><subj-group><subject>Health Care Policy</subject><subj-group><subject>Health Risk Analysis</subject></subj-group></subj-group></subj-group></subj-group></article-categories><title-group><article-title>Adherence to Drug-Refill Is a Useful Early Warning Indicator of
Virologic and Immunologic Failure among HIV Patients on First-Line ART in South
Africa</article-title><alt-title alt-title-type="running-head">HIV Viremia & Immunologic Failure in
South Africa</alt-title></title-group><contrib-group><contrib contrib-type="author"><name><surname>El-Khatib</surname><given-names>Ziad</given-names></name><xref ref-type="aff" rid="aff1"><sup>1</sup></xref><xref ref-type="aff" rid="aff2"><sup>2</sup></xref><xref ref-type="corresp" rid="cor1"><sup>*</sup></xref></contrib><contrib contrib-type="author"><name><surname>Katzenstein</surname><given-names>David</given-names></name><xref ref-type="aff" rid="aff3"><sup>3</sup></xref></contrib><contrib contrib-type="author"><name><surname>Marrone</surname><given-names>Gaetano</given-names></name><xref ref-type="aff" rid="aff1"><sup>1</sup></xref></contrib><contrib contrib-type="author"><name><surname>Laher</surname><given-names>Fatima</given-names></name><xref ref-type="aff" rid="aff4"><sup>4</sup></xref></contrib><contrib contrib-type="author"><name><surname>Mohapi</surname><given-names>Lerato</given-names></name><xref ref-type="aff" rid="aff4"><sup>4</sup></xref></contrib><contrib contrib-type="author"><name><surname>Petzold</surname><given-names>Max</given-names></name><xref ref-type="aff" rid="aff1"><sup>1</sup></xref><xref ref-type="aff" rid="aff5"><sup>5</sup></xref></contrib><contrib contrib-type="author"><name><surname>Morris</surname><given-names>Lynn</given-names></name><xref ref-type="aff" rid="aff2"><sup>2</sup></xref></contrib><contrib contrib-type="author"><name><surname>Ekström</surname><given-names>Anna Mia</given-names></name><xref ref-type="aff" rid="aff1"><sup>1</sup></xref></contrib></contrib-group><aff id="aff1"><label>1</label><addr-line>Division of Global Health (IHCAR), Karolinska Institutet, Stockholm, Sweden</addr-line></aff><aff id="aff2"><label>2</label><addr-line>AIDS Virus Research Unit, National Institute for Communicable Diseases (NICD), Johannesburg, South Africa</addr-line></aff><aff id="aff3"><label>3</label><addr-line>Division of Infectious Diseases, Stanford University, Palo Alto, California, United States of America</addr-line></aff><aff id="aff4"><label>4</label><addr-line>Perinatal HIV Research Unit (PHRU), University of the Witwatersrand, Soweto, South Africa</addr-line></aff><aff id="aff5"><label>5</label><addr-line>Nordic School of Public Health (NHV), Gothenburg, Sweden</addr-line></aff><contrib-group><contrib contrib-type="editor"><name><surname>Maartens</surname><given-names>Gary</given-names></name><role>Editor</role><xref ref-type="aff" rid="edit1"></xref></contrib></contrib-group><aff id="edit1">University of Cape Town, South Africa</aff><author-notes><corresp id="cor1">* E-mail: <email>ziad.khatib@gmail.com</email></corresp><fn fn-type="con"><p>Conceived and designed the experiments: ZE-K DK LM MP FL LM AME. Performed
the experiments: ZE-K DK FL MP LM. Analyzed the data: ZE-K DK GM MP AME.
Contributed reagents/materials/analysis tools: ZE-K FL LM MP DK LM AME.
Wrote the paper: ZE-K DK GM LM MP FL LM AME.</p></fn></author-notes><pub-date pub-type="collection"><year>2011</year></pub-date><pub-date pub-type="epub"><day>9</day><month>3</month><year>2011</year></pub-date><volume>6</volume><issue>3</issue><elocation-id>e17518</elocation-id><history><date date-type="received"><day>18</day><month>11</month><year>2010</year></date><date date-type="accepted"><day>4</day><month>2</month><year>2011</year></date></history><permissions><copyright-statement>El-Khatib et al. This is an open-access article distributed under
the terms of the Creative Commons Attribution License, which permits unrestricted
use, distribution, and reproduction in any medium, provided the original author and
source are credited.</copyright-statement></permissions><abstract><sec><title>Background</title><p>Affordable strategies to prevent treatment failure on first-line regimens
among HIV patients are essential for the long-term success of antiretroviral
therapy (ART) in sub-Saharan Africa. WHO recommends using routinely
collected data such as adherence to drug-refill visits as early warning
indicators. We examined the association between adherence to drug-refill
visits and long-term virologic and immunologic failure among non-nucleoside
reverse transcriptase inhibitor (NNRTI) recipients in South Africa.</p></sec><sec><title>Methods</title><p>In 2008, 456 patients on NNRTI-based ART for a median of 44 months (range
12–99 months; 1,510 person-years) were enrolled in a retrospective
cohort study in Soweto. Charts were reviewed for clinical characteristics
before and during ART. Multivariable logistic regression and Kaplan-Meier
survival analysis assessed associations with virologic (two repeated
VL>50 copies/ml) and immunologic failure (as defined by WHO).</p></sec><sec><title>Results</title><p>After a median of 15 months on ART, 19% (n = 88)
and 19% (n = 87) had failed virologically and
immunologically respectively. A cumulative adherence of <95% to
drug-refill visits was significantly associated with both virologic and
immunologic failure (p<0.01). In the final multivariable model, risk
factors for virologic failure were incomplete adherence (OR 2.8,
95%CI 1.2–6.7), and previous exposure to single-dose nevirapine
or any other antiretrovirals (adj. OR 2.1, 95%CI 1.2–3.9),
adjusted for age and sex. In Kaplan-Meier analysis, the virologic failure
rate by month 48 was 19% vs. 37% among adherent and
non-adherent patients respectively (logrank p
value = 0.02).</p></sec><sec><title>Conclusion</title><p>One in five failed virologically after a median of 15 months on ART.
Adherence to drug-refill visits works as an early warning indicator for both
virologic and immunologic failure.</p></sec></abstract><counts><page-count count="10"></page-count></counts></article-meta></front><body><sec id="s1"><title>Introduction</title><p>Antiretroviral treatment (ART) has saved millions of lives by transforming HIV
infection from a fatal into a chronic disease <xref ref-type="bibr" rid="pone.0017518-World1">[1]</xref> and the vast majority
(97%) of patients in sub-Saharan Africa receive a non-nucleoside reverse
transcriptase (NNRTI) based regimen as first-line treatment <xref ref-type="bibr" rid="pone.0017518-Harries1">[2]</xref>. Given the costs associated
with second-line protease inhibitors, the long-term sustainability of ART in many of
low- and some middle-income countries depends on finding feasible ways for early
detection of treatment failure to maintain patients on first-line regimens <xref ref-type="bibr" rid="pone.0017518-Simon1">[3]</xref>, <xref ref-type="bibr" rid="pone.0017518-Kuritzkes1">[4]</xref>.</p><p>Since viral load (VL) monitoring is not currently accessible in most resource-limited
high-endemic contexts <xref ref-type="bibr" rid="pone.0017518-Harries1">[2]</xref>, <xref ref-type="bibr" rid="pone.0017518-Calmy1">[5]</xref>, patients are often continued on first-line ART until the
emergence of clinical symptoms or until any of the World Health Organization (WHO)
criteria for immunologic failure are met. Although virologic failure and drug
resistance usually precede immunologic failure, these measures are not always well
correlated at clinical follow-up <xref ref-type="bibr" rid="pone.0017518-Rewari1">[6]</xref>, <xref ref-type="bibr" rid="pone.0017518-Kantor1">[7]</xref>, <xref ref-type="bibr" rid="pone.0017518-Hosseinipour1">[8]</xref>. To routinely assess the effectiveness of ART at HIV
treatment clinics and to minimize preventable HIV drug resistance (HIVDR), WHO
recommends using available site-based data from medical and pharmacy records, e.g.
on-time adherence to monthly ART drug pick-up and clinic appointment-keeping <xref ref-type="bibr" rid="pone.0017518-World2">[9]</xref>, <xref ref-type="bibr" rid="pone.0017518-Hedt1">[10]</xref>, as an early
warning indicator (EWI) of inconsistent drug exposure. Failure to pick up drugs on
time serves as a proxy for treatment interruption and suboptimal drug
concentrations, which are associated with virologic failure and the evolution of
drug resistance <xref ref-type="bibr" rid="pone.0017518-Nachega1">[11]</xref>, <xref ref-type="bibr" rid="pone.0017518-Cambiano1">[12]</xref>, <xref ref-type="bibr" rid="pone.0017518-Parienti1">[13]</xref>.</p><p>Earlier reports from resource-limited settings have defined virologic failure as a VL
of >400, >1,000 or >5,000 copies/ml at one or two repeated visits <xref ref-type="bibr" rid="pone.0017518-Barth1">[14]</xref>, <xref ref-type="bibr" rid="pone.0017518-ElKhatib1">[15]</xref>. However,
drug resistance mutations can emerge at lower VL levels <xref ref-type="bibr" rid="pone.0017518-Hatano1">[16]</xref> and in high-income countries,
monitoring guidelines recommend using VL >50 copies/ml as an indicator of
virologic failure for patients on ART <xref ref-type="bibr" rid="pone.0017518-Hammer1">[17]</xref>. As more robust, sensitive and
lower cost assays are developed, ART programmes in low- and middle-income may be
able to adopt lower threshold values for virologic failure. Thus, we assessed the
proportion of repeated VL >50 copies/ml, immunologic failure and median CD4 cell
count gains in a cohort of long-term, first-line recipients in Soweto, who had been
on NNTRI-based regimens for up to eight years. We also assessed the relationship
between cumulative adherence to drug-refill visits and treatment failure.</p></sec><sec sec-type="methods" id="s2"><title>Methods</title><sec id="s2a"><title>Setting and study population</title><p>At the time of the study, more than 1,500 patients were receiving ART at this
clinic. Aiming for a precision of +/− 5% for a proportion of
50% using 95% confidence interval, a sample size of 384 patients
was required <xref ref-type="bibr" rid="pone.0017518-Rothman1">[18]</xref>. Adding a margin to the minimum required sample size,
a cohort of 458 participants on long-term ART (range 12 to 99 months) were
enrolled during March-September 2008 <xref ref-type="bibr" rid="pone.0017518-ElKhatib2">[19]</xref> for a cross-sectional
assessment and a retrospective review of their medical charts. The inclusion
criteria were: being on NNRTI-containing regimen for ≥12 months; consent to
an interviewer-mediated questionnaire; medical record review; and withdrawal of
10ml of blood. The study, named South African Virologic Evaluation (SAVE) <xref ref-type="bibr" rid="pone.0017518-ElKhatib1">[15]</xref>, was
performed at the Perinatal HIV Research Unit (PHRU) adult HIV clinic at the
Chris Hani Baragwanath Hospital, in the Soweto township outside Johannesburg,
South Africa. The study site <xref ref-type="bibr" rid="pone.0017518-Martinson1">[20]</xref> and a cross-sectional description of viremia and drug
resistance have been described in depth previously <xref ref-type="bibr" rid="pone.0017518-ElKhatib1">[15]</xref>, <xref ref-type="bibr" rid="pone.0017518-ElKhatib3">[21]</xref>.</p></sec><sec id="s2b"><title>Data collection</title><p>Patients were interviewed at study enrolment to obtain demographics,
socioeconomic characteristics, reasons for missing doses and the strategies used
to remember taking their pills on time. The retrospective review included: year
of HIV diagnosis; pre-ART initiation characteristics (VL, CD4 cell count,
pre-exposure to single-dose nevirapine (sdNVP) or other antiretroviral drugs
(ARVs); current and previous TB therapy; dates for drug refill visits; and
treatment interruptions. VL and CD4 counts had been measured every six months on
average. For two of the patients, medical records were not available and they
were excluded from the longitudinal analysis, leaving 456 patients for data
analyses. A survey form, called Medical Records-SAVE (MR.SAVE©), was
developed, piloted and modified <xref ref-type="bibr" rid="pone.0017518-ElKhatib4">[22]</xref> for data collection.
EpiData <xref ref-type="bibr" rid="pone.0017518-ElKhatib5">[23]</xref>, <xref ref-type="bibr" rid="pone.0017518-EpiData1">[24]</xref> was used for data entry.</p></sec><sec id="s2c"><title>Definitions</title><p>The clinic uses a private diagnostic laboratory service that provides VL measures
with the Versant HIV-1 RNA 3.0 (Siemens Deerfield, IL, USA) based on bDNA
technology, with a lower limit of detection of 50 copies/ml. Virologic failure
was defined as two repeated VL >50 copies/ml at any time after three months
on ART. Immunologic failure was defined according to the WHO guidelines as
having either (i) a CD4 cell count of <100 cells/µl post six months on
ART, (ii) a CD4 cell count of less or equal to CD4 pre-ART after six months on
ART or (iii) >50% reduction from the on-ART peak CD4 cell count <xref ref-type="bibr" rid="pone.0017518-World3">[25]</xref>. Patients
were dispensed ART monthly and at scheduled doctor's visits. They were also
given projected monthly pharmacy refill dates and the date of the next
doctor's appointment. At each refill visit, pharmacy staff dispensed pills
and recorded the date. To estimate adherence, we calculated the total number of
days that the patient was late for the drug-refill visits divided by the total
duration on ART. The formula was: [The number of days late for drug-refill
visit = (Date when the patient came for drug refill -
Date of the pre-scheduled appointment indicated on the patient's medical
record)]. The results were then summarized for repeated refill visits to
obtain the cumulative number of days coming late per client. To estimate
adherence, the following formula was used [The cumulative number of days
coming late ×100)/Total number of days the patient was assumed to be
exposed to ART given the dispensed number of pills]. Appointment dates were
censored after the date of virologic failure.</p><p>Incomplete versus complete adherence was defined as a cumulative adherence to
drug refill visits of < and ≥95% respectively. Treatment
interruption was defined as a reported and/or planned history of stopping and
resuming therapy, identified through chart review.</p></sec><sec id="s2d"><title>Statistical analysis</title><p>Descriptive analyses including median (IQR) for numerical variables, frequencies
and proportions for categorical variables were performed. Bivariate analyses to
assess risk factors for virologic and immunologic failure were performed using
Pearson Chi Square and Fisher's exact tests. Thereafter variables with a
p-value ≤0.10 were added into a multivariate logistic regression model and
those with a p-value <0.05 were considered significant in the final
multivariate model, calculating odds ratios (OR) and 95% confidence
intervals (CIs). However, the variables sex and age were always maintained in
the final multivariate models to account for possible remaining confounders.</p><p>Kaplan Meier survival analysis was done using months as the time unit in order to
assess time to virologic and immunologic failure on ART among all patients.</p><p>Known pre-ART risk factors, exposure to sdNVP <xref ref-type="bibr" rid="pone.0017518-Paredes1">[26]</xref>, <xref ref-type="bibr" rid="pone.0017518-Datay1">[27]</xref>, <xref ref-type="bibr" rid="pone.0017518-Coovadia1">[28]</xref> or any type of ARVs, CD4
cell count and age <xref ref-type="bibr" rid="pone.0017518-Paredes1">[26]</xref>, <xref ref-type="bibr" rid="pone.0017518-Ford1">[29]</xref>, <xref ref-type="bibr" rid="pone.0017518-Boulle1">[30]</xref> were adjusted using Cox regression analysis for
virologic failure. For immunologic failure, Cox regression analysis was done by
adjusting for the same above-mentioned variables and any virologic failure. Due
to collinearity between sex and pre-ART CD4 count, sex was not included in the
final survival model.</p><p>Finally, we assessed the median gain in CD4 cell count during ART on a
six-monthly basis (range +/−3 months) among 1) patients with
incomplete vs. complete cumulative drug-refill adherence, and 2) patients with
virologic failure vs. suppression up to 36 months on ART only, due to data
availability.</p><p>Stata/SE College Station, Texas (version 10.1) <xref ref-type="bibr" rid="pone.0017518-StataCorp1">[31]</xref> and Graphpad Prism
(version 4.0c) <xref ref-type="bibr" rid="pone.0017518-Prism1">[32]</xref> were used for data analysis. In the survival
analysis, the command sts graph in STATA was used. Adjusting for covariates, the
command fits separate Cox regression models for each group, and the separately
calculated baseline survivor was then retrieved.</p><p>Ethical approval for this study was obtained from the research ethics committees
at the University of the Witwatersrand in Johannesburg, South Africa, and the
Regional Medical Ethics Board in Stockholm, Sweden. Written informed consent was
obtained from all patients.</p></sec></sec><sec id="s3"><title>Results and Discussion</title><sec id="s3a"><title>Patients' characteristics</title><p>A total of 456 patient records were reviewed. Most patients (79%) were
diagnosed with HIV between 2001-2004 (median 2003), 14% before 2000 and
the remaining 7% between 2005 and 2008. Pre-ART initiation, 51%
(222/434) had a CD4 cell count of ≤100 cell/µl and 41% (172/421)
had a VL of ≥100 000 copies/ml (<xref ref-type="table" rid="pone-0017518-t001">Table 1</xref>). Overall, the median time on ART was
44 months (IQR 38–48; 1,510 person-years) and 77% (349/456) were
women (<xref ref-type="table" rid="pone-0017518-t001">Table 1</xref>). Eighteen
percent (80/445) had been exposed to ARVs previously; 15% of the women
(52/349) had received sdNVP for the prevention of mother-to-child transmission
(PMTCT) with a median time before ART initiation of 15 months, and 6% of
all patients (28/446) had received ART before starting the current ART regimen.
Approximately half (48%, 199/414) had been treated for tuberculosis (TB)
before ART initiation. At the time of study enrolment, the patients spent a
median of 40 minutes (IQR 30–60) travelling to the clinic by mini-van
(90%), walking (5%) and using their own car (4%).</p><table-wrap id="pone-0017518-t001" position="float"><object-id pub-id-type="doi">10.1371/journal.pone.0017518.t001</object-id><label>Table 1</label><caption><title>Demographics, socioeconomic and clinical characteristics and
bivariate analysis for the association with a) virologic and b)
immunologic failure among 456 patients on ART in Soweto, South
Africa.</title></caption><alternatives><graphic id="pone-0017518-t001-1" xlink:href="pone.0017518.t001"></graphic><table frame="hsides" rules="groups"><colgroup span="1"><col align="left" span="1"></col><col align="center" span="1"></col><col align="center" span="1"></col><col align="center" span="1"></col><col align="center" span="1"></col><col align="center" span="1"></col></colgroup><thead><tr><td colspan="2" align="left" rowspan="1">Demographics and socio-economic
characteristics</td><td colspan="2" align="left" rowspan="1">a) Virologic failure∧</td><td colspan="2" align="left" rowspan="1">b) Immunologic failure∧∧</td></tr><tr><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1">N = 456<xref ref-type="table-fn" rid="nt103">#</xref> (% of
total)</td><td align="left" rowspan="1" colspan="1">N = 88/456 (% row)</td><td align="left" rowspan="1" colspan="1">Bivariate p-value</td><td align="left" rowspan="1" colspan="1">N = 87/456<xref ref-type="table-fn" rid="nt103">#</xref> (% row)</td><td align="left" rowspan="1" colspan="1">Bivariate p-value</td></tr></thead><tbody><tr><td align="left" rowspan="1" colspan="1"><bold>Sex</bold></td><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1"></td></tr><tr><td align="left" rowspan="1" colspan="1">Women</td><td align="left" rowspan="1" colspan="1">349 (77%)</td><td align="left" rowspan="1" colspan="1">68 (19%)</td><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1">59 (17%)</td><td align="left" rowspan="1" colspan="1"></td></tr><tr><td align="left" rowspan="1" colspan="1">Men</td><td align="left" rowspan="1" colspan="1">107 (23%)</td><td align="left" rowspan="1" colspan="1">20 (19%)</td><td align="left" rowspan="1" colspan="1">0.87</td><td align="left" rowspan="1" colspan="1">28 (26%)</td><td align="left" rowspan="1" colspan="1">0.03</td></tr><tr><td align="left" rowspan="1" colspan="1"><bold>Age</bold></td><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1"></td></tr><tr><td align="left" rowspan="1" colspan="1">18–24</td><td align="left" rowspan="1" colspan="1">21 (5%)</td><td align="left" rowspan="1" colspan="1">5 (24%)</td><td align="left" rowspan="1" colspan="1">0.42</td><td align="left" rowspan="1" colspan="1">3 (14%)</td><td align="left" rowspan="1" colspan="1">0.62</td></tr><tr><td align="left" rowspan="1" colspan="1">25–34</td><td align="left" rowspan="1" colspan="1">235 (51%)</td><td align="left" rowspan="1" colspan="1">45 (19%)</td><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1">46 (20%)</td><td align="left" rowspan="1" colspan="1"></td></tr><tr><td align="left" rowspan="1" colspan="1">35–44</td><td align="left" rowspan="1" colspan="1">147 (32%)</td><td align="left" rowspan="1" colspan="1">24 (16%)</td><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1">25 (17%)</td><td align="left" rowspan="1" colspan="1"></td></tr><tr><td align="left" rowspan="1" colspan="1">≥45</td><td align="left" rowspan="1" colspan="1">53 (12%)</td><td align="left" rowspan="1" colspan="1">14 (26%)</td><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1">13 (24%)</td><td align="left" rowspan="1" colspan="1"></td></tr><tr><td align="left" rowspan="1" colspan="1"><bold>Marital status</bold></td><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1"></td></tr><tr><td align="left" rowspan="1" colspan="1">Have partner</td><td align="left" rowspan="1" colspan="1">265 (58%)</td><td align="left" rowspan="1" colspan="1">49 (18%)</td><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1">50 (19%)</td><td align="left" rowspan="1" colspan="1"></td></tr><tr><td align="left" rowspan="1" colspan="1">Single/no partner at all</td><td align="left" rowspan="1" colspan="1">191 (42%)</td><td align="left" rowspan="1" colspan="1">39 (20%)</td><td align="left" rowspan="1" colspan="1">0.61</td><td align="left" rowspan="1" colspan="1">37 (19%)</td><td align="left" rowspan="1" colspan="1">0.89</td></tr><tr><td align="left" rowspan="1" colspan="1"><bold>Born in South Africa</bold></td><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1"></td></tr><tr><td align="left" rowspan="1" colspan="1">No</td><td align="left" rowspan="1" colspan="1">17 (4%)</td><td align="left" rowspan="1" colspan="1">4 (23%)</td><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1">2 (12%)</td><td align="left" rowspan="1" colspan="1"></td></tr><tr><td align="left" rowspan="1" colspan="1">Yes</td><td align="left" rowspan="1" colspan="1">439 (96%)</td><td align="left" rowspan="1" colspan="1">84 (19%)</td><td align="left" rowspan="1" colspan="1">0.65</td><td align="left" rowspan="1" colspan="1">85 (19%)</td><td align="left" rowspan="1" colspan="1">0.43</td></tr><tr><td align="left" rowspan="1" colspan="1"><bold>Education level</bold></td><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1"></td></tr><tr><td align="left" rowspan="1" colspan="1">No education or primary schooling</td><td align="left" rowspan="1" colspan="1">50 (11%)</td><td align="left" rowspan="1" colspan="1">11 (20%)</td><td align="left" rowspan="1" colspan="1">0.61</td><td align="left" rowspan="1" colspan="1">4 (8%)</td><td align="left" rowspan="1" colspan="1"></td></tr><tr><td align="left" rowspan="1" colspan="1">Secondary or tertiary education level</td><td align="left" rowspan="1" colspan="1">406 (89%)</td><td align="left" rowspan="1" colspan="1">77 (19%)</td><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1">83 (20%)</td><td align="left" rowspan="1" colspan="1">0.03<xref ref-type="table-fn" rid="nt101">*</xref></td></tr><tr><td align="left" rowspan="1" colspan="1"><bold>Year diagnosed with HIV</bold></td><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1"></td></tr><tr><td align="left" rowspan="1" colspan="1">≤2000</td><td align="left" rowspan="1" colspan="1">63 (14%)</td><td align="left" rowspan="1" colspan="1">10 (16%)</td><td align="left" rowspan="1" colspan="1">0.79</td><td align="left" rowspan="1" colspan="1">10 (16%)</td><td align="left" rowspan="1" colspan="1">0.66</td></tr><tr><td align="left" rowspan="1" colspan="1">2001–2004</td><td align="left" rowspan="1" colspan="1">348 (79%)</td><td align="left" rowspan="1" colspan="1">68 (20%)</td><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1">70 (20%)</td><td align="left" rowspan="1" colspan="1"></td></tr><tr><td align="left" rowspan="1" colspan="1">2005–2008</td><td align="left" rowspan="1" colspan="1">31 (7%)</td><td align="left" rowspan="1" colspan="1">6 (19%)</td><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1">5 (16%)</td><td align="left" rowspan="1" colspan="1"></td></tr><tr><td align="left" rowspan="1" colspan="1"><bold>Any type of work</bold></td><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1"></td></tr><tr><td align="left" rowspan="1" colspan="1">No</td><td align="left" rowspan="1" colspan="1">283 (65%)</td><td align="left" rowspan="1" colspan="1">59 (21%)</td><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1">60 (21%)</td><td align="left" rowspan="1" colspan="1"></td></tr><tr><td align="left" rowspan="1" colspan="1">Yes</td><td align="left" rowspan="1" colspan="1">154 (35%)</td><td align="left" rowspan="1" colspan="1">28 (18%)</td><td align="left" rowspan="1" colspan="1">0.51</td><td align="left" rowspan="1" colspan="1">23 (15%)</td><td align="left" rowspan="1" colspan="1">0.11</td></tr><tr><td align="left" rowspan="1" colspan="1"><bold>Clinical characteristics</bold><xref ref-type="table-fn" rid="nt102">**</xref></td><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1"></td></tr><tr><td align="left" rowspan="1" colspan="1"><bold>CD4 cell count – pre-ART</bold></td><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1"></td></tr><tr><td align="left" rowspan="1" colspan="1">≤50</td><td align="left" rowspan="1" colspan="1">122 (28%)</td><td align="left" rowspan="1" colspan="1">21 (17%)</td><td align="left" rowspan="1" colspan="1">0.59</td><td align="left" rowspan="1" colspan="1">26 (21%)</td><td align="left" rowspan="1" colspan="1">0.52</td></tr><tr><td align="left" rowspan="1" colspan="1">51–100</td><td align="left" rowspan="1" colspan="1">100 (23%)</td><td align="left" rowspan="1" colspan="1">24 (24%)</td><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1">21 (16%)</td><td align="left" rowspan="1" colspan="1"></td></tr><tr><td align="left" rowspan="1" colspan="1">101–249</td><td align="left" rowspan="1" colspan="1">199 (46%)</td><td align="left" rowspan="1" colspan="1">37 (19%)</td><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1">31 (16%)</td><td align="left" rowspan="1" colspan="1"></td></tr><tr><td align="left" rowspan="1" colspan="1">≥250</td><td align="left" rowspan="1" colspan="1">13 (3%)</td><td align="left" rowspan="1" colspan="1">2 (15%)</td><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1">3 (23%)</td><td align="left" rowspan="1" colspan="1"></td></tr><tr><td align="left" rowspan="1" colspan="1"><bold>Viral load level – pre-ART (RNA
copies/ml)</bold></td><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1"></td></tr><tr><td align="left" rowspan="1" colspan="1"><5,000</td><td align="left" rowspan="1" colspan="1">22 (5%)</td><td align="left" rowspan="1" colspan="1">2 (9%)</td><td align="left" rowspan="1" colspan="1">0.54</td><td align="left" rowspan="1" colspan="1">1 (5%)</td><td align="left" rowspan="1" colspan="1">0.26</td></tr><tr><td align="left" rowspan="1" colspan="1">5,000–29,999</td><td align="left" rowspan="1" colspan="1">110 (26%)</td><td align="left" rowspan="1" colspan="1">23 (21%)</td><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1">24 (22%)</td><td align="left" rowspan="1" colspan="1"></td></tr><tr><td align="left" rowspan="1" colspan="1">30,000–99,999</td><td align="left" rowspan="1" colspan="1">117 (28%)</td><td align="left" rowspan="1" colspan="1">20 (17%)</td><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1">24 (21%)</td><td align="left" rowspan="1" colspan="1"></td></tr><tr><td align="left" rowspan="1" colspan="1">≥100,000</td><td align="left" rowspan="1" colspan="1">172 (41%)</td><td align="left" rowspan="1" colspan="1">35 (20%)</td><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1">30 (17%)</td><td align="left" rowspan="1" colspan="1"></td></tr><tr><td align="left" rowspan="1" colspan="1"><bold>Pre-exposure to sdNVP or other type of
ARVs</bold></td><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1"></td></tr><tr><td align="left" rowspan="1" colspan="1">Treatment naïve</td><td align="left" rowspan="1" colspan="1">365 (82%)</td><td align="left" rowspan="1" colspan="1">64 (18%)</td><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1">72 (20%)</td><td align="left" rowspan="1" colspan="1"></td></tr><tr><td align="left" rowspan="1" colspan="1">Single dose-nevirapine (sdNVP)</td><td align="left" rowspan="1" colspan="1">52 (12%)</td><td align="left" rowspan="1" colspan="1">13 (25%)</td><td align="left" rowspan="1" colspan="1">0.19</td><td align="left" rowspan="1" colspan="1">7 (13%)</td><td align="left" rowspan="1" colspan="1">0.28</td></tr><tr><td align="left" rowspan="1" colspan="1">Had any ARVs pre-ART initiation<xref ref-type="table-fn" rid="nt106">##</xref></td><td align="left" rowspan="1" colspan="1">28 (6%)</td><td align="left" rowspan="1" colspan="1">9 (32%)</td><td align="left" rowspan="1" colspan="1">0.06</td><td align="left" rowspan="1" colspan="1">6 (21%)</td><td align="left" rowspan="1" colspan="1">0.83</td></tr><tr><td align="left" rowspan="1" colspan="1"><bold>Treatment experienced (sdNVP or any
ARVs)</bold></td><td align="left" rowspan="1" colspan="1">80 (18%)</td><td align="left" rowspan="1" colspan="1">22 (28%)</td><td align="left" rowspan="1" colspan="1">0.04</td><td align="left" rowspan="1" colspan="1">13 (16%)</td><td align="left" rowspan="1" colspan="1">0.47</td></tr><tr><td align="left" rowspan="1" colspan="1"><bold>TB therapy</bold></td><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1"></td></tr><tr><td align="left" rowspan="1" colspan="1">Not treated before ART</td><td align="left" rowspan="1" colspan="1">215 (52%)</td><td align="left" rowspan="1" colspan="1">36 (17%)</td><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1">38 (18%)</td><td align="left" rowspan="1" colspan="1"></td></tr><tr><td align="left" rowspan="1" colspan="1">Treated before ART</td><td align="left" rowspan="1" colspan="1">137 (33%)</td><td align="left" rowspan="1" colspan="1">27 (20%)</td><td align="left" rowspan="1" colspan="1">0.48</td><td align="left" rowspan="1" colspan="1">33 (24%)</td><td align="left" rowspan="1" colspan="1">0.14</td></tr><tr><td align="left" rowspan="1" colspan="1">Was on TB therapy when started on ART</td><td align="left" rowspan="1" colspan="1">62 (15%)</td><td align="left" rowspan="1" colspan="1">11 (18%)</td><td align="left" rowspan="1" colspan="1">0.85</td><td align="left" rowspan="1" colspan="1">10 (16%)</td><td align="left" rowspan="1" colspan="1">0.78</td></tr><tr><td align="left" rowspan="1" colspan="1"><bold>Disclosed HIV status pre-ART</bold></td><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1"></td></tr><tr><td align="left" rowspan="1" colspan="1">No</td><td align="left" rowspan="1" colspan="1">35 (8%)</td><td align="left" rowspan="1" colspan="1">4 (11%)</td><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1">8 (23%)</td><td align="left" rowspan="1" colspan="1"></td></tr><tr><td align="left" rowspan="1" colspan="1">Yes</td><td align="left" rowspan="1" colspan="1">400 (92%)</td><td align="left" rowspan="1" colspan="1">80 (20%)</td><td align="left" rowspan="1" colspan="1">0.22</td><td align="left" rowspan="1" colspan="1">77 (19%)</td><td align="left" rowspan="1" colspan="1">0.61</td></tr><tr><td align="left" rowspan="1" colspan="1"><bold>Cumulative adherence to on-time drug
refill</bold></td><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1"></td></tr><tr><td align="left" rowspan="1" colspan="1">95-100%</td><td align="left" rowspan="1" colspan="1">430 (94%)</td><td align="left" rowspan="1" colspan="1">79 (18%)</td><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1">78 (18%)</td><td align="left" rowspan="1" colspan="1"></td></tr><tr><td align="left" rowspan="1" colspan="1"><95%</td><td align="left" rowspan="1" colspan="1">26 (6%)</td><td align="left" rowspan="1" colspan="1">9 (35%)</td><td align="left" rowspan="1" colspan="1">0.04</td><td align="left" rowspan="1" colspan="1">9 (35%)</td><td align="left" rowspan="1" colspan="1">0.04</td></tr><tr><td align="left" rowspan="1" colspan="1"><bold>Any treatment interruption</bold></td><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1"></td></tr><tr><td align="left" rowspan="1" colspan="1">No</td><td align="left" rowspan="1" colspan="1">324 (71%)</td><td align="left" rowspan="1" colspan="1">66 (20%)</td><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1">58 (18%)</td><td align="left" rowspan="1" colspan="1"></td></tr><tr><td align="left" rowspan="1" colspan="1">Yes<xref ref-type="table-fn" rid="nt107">$</xref></td><td align="left" rowspan="1" colspan="1">132 (29%)</td><td align="left" rowspan="1" colspan="1">22 (17%)</td><td align="left" rowspan="1" colspan="1">0.36</td><td align="left" rowspan="1" colspan="1">29 (22%)</td><td align="left" rowspan="1" colspan="1">0.32</td></tr></tbody></table></alternatives><table-wrap-foot><fn id="nt101"><label></label><p>*2-sided Fisher exact test;</p></fn><fn id="nt102"><label></label><p>**All patients were initiated on an NNRTI-based regimen (the
majority had efavirenz);</p></fn><fn id="nt103"><label>#</label><p>Two patients (2/458) were excluded due to missing longitudinal
data;</p></fn><fn id="nt104"><label></label><p>∧Two repeated VL >50 copies/ml post-three months on ART;</p></fn><fn id="nt105"><label></label><p>∧∧WHO criteria for immunologic failure;</p></fn><fn id="nt106"><label>##</label><p>Two patients were exposed to sdNVP and ART, pre-ART initiation, but
virologically suppressed.</p></fn><fn id="nt107"><label>$</label><p>Treatment interruption: once for 129 patients and twice for 3
patients.</p></fn></table-wrap-foot></table-wrap></sec><sec id="s3b"><title>Virologic failure</title><p>Overall, 19% (88/456) met the criteria for virologic failure. In bivariate
analysis, being exposed to any type of ARVs including sdNVP prior to ART
initiation or incomplete adherence was significantly associated with virologic
failure (p = 0.04) (<xref ref-type="table" rid="pone-0017518-t001">Table 1a</xref>). These two factors remained
significant after adjustment for confounding by age and sex in the multivariable
analysis model. The odds ratio of virologic failure among patients with
incomplete adherence almost tripled (adjusted OR 2.8, 95%CI
1.2–6.7) and doubled among those exposed to any type of ARVs prior to ART
initiation (adj. OR 2.1, 95%CI 1.2–3.9). However, exposure to sdNVP
alone did not reach statistical significance. Neither the level of CD4 cell
count nor VL at pre-ART initiation was significantly associated with subsequent
virologic failure on ART in bivariate analyses, and therefore was not included
in the multivariable model.</p><p>In a separate analysis, there was no significant association between incomplete
adherence and any of the patients' demographic, socioeconomic or clinical
data (not shown).</p><p>Planned treatment interruptions were not part of the clinical guidelines at this
clinic. Of the 456 patients, 132 (29%) had a reported history of
treatment interruption registered in their medical charts, 98% of these
(129/132) only once. Three patients were reported to have experienced treatment
interruption twice but were not found to fail virologically during the study
period. The median duration of treatment interruption was longer among patients
with, compared to those without, virologic failure; 45 days (IQR 27–97)
vs. 36 days (IQR 19–63) respectively, although this difference was not
statistically significant (p = 0.12).</p><p>Analysing the risk of virologic failure over time using Kaplan Meier survival
analysis, the virologic failure rate was 23% up until month 99 (<xref ref-type="fig" rid="pone-0017518-g001">Figure 1a</xref>). There was a
significant difference in time to virologic failure between patients with
complete vs. incomplete adherence. By month 12 on ART, the failure rate was
similar (7% vs 8% among patients with complete and incomplete
adherence respectively) but by month 48, the difference in failure rates had
reached statistical significance between the groups, 19% vs. 37%
respectively (logrank p value = 0.02) (<xref ref-type="fig" rid="pone-0017518-g001">Figure 1a</xref>). Following adjustment for CD4 cell
count, age and exposure to any ARVs pre-ART initiation in a Cox regression
analysis, there was a significant difference in virologic failure rates already
at month 12 on ART; 2% vs 11%, and at month 48. This difference
was even more pronounced, 18% vs. 43%, among patients with
complete vs incomplete adherence respectively (logrank p value <0.01) (<xref ref-type="fig" rid="pone-0017518-g001">Figure 1b</xref>).</p><fig id="pone-0017518-g001" position="float"><object-id pub-id-type="doi">10.1371/journal.pone.0017518.g001</object-id><label>Figure 1</label><caption><title>(a) Kaplan-Meier survival analysis for time to virologic failure by
level of cumulative adherence to drug refill visits.</title><p>(b) Cox regression analysis after adjustment for confounding by CD4 cell
count, age and being exposed to sdNVP or any ART pre-ART initiation.</p></caption><graphic xlink:href="pone.0017518.g001"></graphic></fig></sec><sec id="s3c"><title>Immunologic failure</title><p>Overall, 87/456 (19%) of the patients met one or more of the definitions
of immunologic failure based on CD4 cell count <xref ref-type="bibr" rid="pone.0017518-World4">[33]</xref>. In bivariate analysis,
immunologic failure was associated with incomplete adherence
(p = 0.04), gender (p = 0.03), and low
education level (p = 0.03) (<xref ref-type="table" rid="pone-0017518-t001">Table 1</xref>). However, none of these variables
remained significant in the final multivariate logistic regression model. More
than one third (37%; 32/87) of patients failing immunologically were also
found to be viremic. Among those with immunologic failure, there was no
significant difference in CD4 cell count or VL, pre-ART initiation, between the
32 viremic and 55 non-viremic patients (data not shown).</p><p>Kaplan Meier survival analysis demonstrated an overall immunologic failure rate
of 27% by month 48 (<xref ref-type="fig" rid="pone-0017518-g002">Figure
2a</xref>). The risk of immunologic failure was 41% vs 19%
among those with incomplete and complete adherence respectively after 48 months
on ART (logrank p value = 0.02). After adjustment for CD4
cell count, age and exposure to any ARVs pre-ART initiation and for virologic
failure in the Cox regression analysis, patients with incomplete adherence had
an immunologic failure rate of 90% at month 48, while the corresponding
figure among patients with complete adherence was only 11% (<xref ref-type="fig" rid="pone-0017518-g002">Figure 2b</xref>) (logrank p
value<0.01).</p><fig id="pone-0017518-g002" position="float"><object-id pub-id-type="doi">10.1371/journal.pone.0017518.g002</object-id><label>Figure 2</label><caption><title>(a) Kaplan-Meier survival analysis for time to immunologic failure,
by level of cumulative adherence to drug refill visits.</title><p>(b) Cox regression analysis, adjusted for confounding by virologic
failure, CD4 cell count, age and being exposed to sdNVP or any ART
pre-ART initiation</p></caption><graphic xlink:href="pone.0017518.g002"></graphic></fig></sec><sec id="s3d"><title>Immunologic response to ART</title><p>There was a significant difference in CD4 cell count gain during ART between
patients with complete vs incomplete adherence at almost all of the clinical
visits (p≤0.04) (<xref ref-type="fig" rid="pone-0017518-g003">Figure
3</xref>). As expected, patients initiating ART with a CD4 cell count of >100
cells/µl had a significantly higher median CD4 cell count in comparison to
patients started on ART at a CD4 cell count of ≤100 cells/µl throughout
the follow-up period (<xref ref-type="fig" rid="pone-0017518-g004">Figure
4</xref>). The median CD4 cell count was also significantly higher among
patients with continuous virologic suppression patients as compared to those
with virologic rebound up to at least three years on ART (months 18, 24, 30 and
36, p≤0.03) (<xref ref-type="fig" rid="pone-0017518-g005">Figure
5</xref>).</p><fig id="pone-0017518-g003" position="float"><object-id pub-id-type="doi">10.1371/journal.pone.0017518.g003</object-id><label>Figure 3</label><caption><title>Median CD4 (IQR) for patients initiated on ART, by adherence < or
≥95% based on drug-refill visits.</title></caption><graphic xlink:href="pone.0017518.g003"></graphic></fig><fig id="pone-0017518-g004" position="float"><object-id pub-id-type="doi">10.1371/journal.pone.0017518.g004</object-id><label>Figure 4</label><caption><title>Median CD4 (IQR) for patients initiated on ART, with CD4 ≤ or
>100 cells/µl.</title></caption><graphic xlink:href="pone.0017518.g004"></graphic></fig><fig id="pone-0017518-g005" position="float"><object-id pub-id-type="doi">10.1371/journal.pone.0017518.g005</object-id><label>Figure 5</label><caption><title>Median CD4 (IQR) for patients who showed virologic failure vs. those
who remained suppressed.</title></caption><graphic xlink:href="pone.0017518.g005"></graphic></fig></sec><sec id="s3e"><title>Barriers and facilitators for adherence</title><p>When all patients were asked about the reasons for missing pills, the three main
reasons stated were: being away from home (32%); simply forgetting
(20%); and being busy with other things (10%) (<xref ref-type="fig" rid="pone-0017518-g006">Figure 6</xref>). Eleven other
reasons were reported but all with a prevalence of ≤6%.</p><fig id="pone-0017518-g006" position="float"><object-id pub-id-type="doi">10.1371/journal.pone.0017518.g006</object-id><label>Figure 6</label><caption><title>Proportion of patients (%) with self-reported reasons for not
taking any of their pills in general at study enrolment
(N = 458).</title></caption><graphic xlink:href="pone.0017518.g006"></graphic></fig><p>Patients used a combination of methods to remember their medication; mobile phone
alarms (49%), relying on their own memory (49%), a close
friend/relative (20%) or a partner (8%) to remind them, or
pill-boxes (1%).</p><p>All interviewees denied any intentional non-adherence in order to maintain
eligibility for disability support. This was despite 39% of the patients
reporting that their primary source of financial support was the social welfare
disability grant provided in South Africa for HIV-infected patients with a CD4
cell count below 200 cells/µl.</p><p>Antiretroviral therapy is a life-long undertaking and finding feasible and
affordable means for early detection of treatment failure is crucial to sustain
first-line therapy effectiveness. Our study found that the estimated proportion
of patients failing virologically was 2–3 times higher among patients who
were late for their drug-refill visits compared to those with an adherence to
drug refill above 95%. This provides evidence that failure to collect ART
may serve as a proxy for reduced drug exposure over time.</p><p>According to WHO <xref ref-type="bibr" rid="pone.0017518-World2">[9]</xref>, <xref ref-type="bibr" rid="pone.0017518-Hedt1">[10]</xref>, monitoring the extent to which ART sites function
through EWIs such as adherence to on-time drug refills is of high priority in
order to minimize preventable HIVDR. The usefulness and importance of the
on-time drug refill indicator became most obvious in the Cox regression analysis
over time. It showed a significant difference in first-year failure rates
(2% vs 11%) among patients with complete adherence vs incomplete
adherence to drug refill already after 12 months on treatment. This difference
became even more visible after 4 years on ART (18% vs 43%
virologic failure rate respectively) adjusting for CD4 cell count at ART
initiation, age and exposure to any ARVs pre-ART initiation.</p><p>The cumulative proportion with virologic failure in our study is comparable to
similar cohorts of long-term ART-recipients in urban South African townships
including other studies from an urban site in Johannesburg <xref ref-type="bibr" rid="pone.0017518-Sanne1">[34]</xref>, and from Khayelitsha <xref ref-type="bibr" rid="pone.0017518-Boulle1">[30]</xref>. Similarly
high failure rates have also been reported from Switzerland <xref ref-type="bibr" rid="pone.0017518-Keiser1">[35]</xref>, England
<xref ref-type="bibr" rid="pone.0017518-Lampe1">[36]</xref>, <xref ref-type="bibr" rid="pone.0017518-Lampe2">[37]</xref>, France,
Spain, Germany and Canada <xref ref-type="bibr" rid="pone.0017518-Lampe2">[37]</xref>.</p><p>Apart from <95% adherence to drug refills, previous exposure to other
ARVs was the only significant risk factor associated with an increased risk of
virologic failure in our multivariable analysis, supporting ample existing
evidence that sdNVP <xref ref-type="bibr" rid="pone.0017518-Phillips1">[38]</xref>, <xref ref-type="bibr" rid="pone.0017518-Datay2">[39]</xref>, <xref ref-type="bibr" rid="pone.0017518-Jackson1">[40]</xref>, <xref ref-type="bibr" rid="pone.0017518-Eshleman1">[41]</xref> or other ARVs <xref ref-type="bibr" rid="pone.0017518-Madge1">[42]</xref> may predispose to virologic
failure and the emergence of HIVDR mutations among women treated with
NNRTI-based ARVs.</p><p>During the first year on ART, CD4 T-cell restoration can be slow <xref ref-type="bibr" rid="pone.0017518-Taiwo1">[43]</xref>, but we
found that the rate of CD4 cell count gain up to 36 months on ART was the same
regardless of the initial level of CD4. Thus, patients starting ART with
advanced immuno-suppression and very low CD4 cell counts (<100
cells/µl) maintained a significantly lower CD4 cell count level throughout
the study period. This put them at risk of increased morbidity for a number of
years post-ART initiation <xref ref-type="bibr" rid="pone.0017518-Boulle1">[30]</xref>, <xref ref-type="bibr" rid="pone.0017518-Egger1">[44]</xref>, and provides further justification to initiate ART
earlier, as embodied in the recent WHO recommendations <xref ref-type="bibr" rid="pone.0017518-World4">[33]</xref>. The gain in CD4 cell count
was significantly dependent on high adherence to drug refill and viral
suppression supporting the findings by Bisson and co-workers <xref ref-type="bibr" rid="pone.0017518-Bisson1">[45]</xref>. However,
in our study, nearly two thirds of patients failing immunologically were
virologically suppressed at clinical assessment. Thus CD4 cell count is a poor
predictor of virologic outcomes <xref ref-type="bibr" rid="pone.0017518-Rewari1">[6]</xref>, <xref ref-type="bibr" rid="pone.0017518-Kantor1">[7]</xref>, <xref ref-type="bibr" rid="pone.0017518-Mee1">[46]</xref>, <xref ref-type="bibr" rid="pone.0017518-Badri1">[47]</xref> and the use of immunological criteria only for
monitoring treatment responses may jeopardize clinical management.</p><p>All study participants in this study had been on ART for at least 12 months, and
over 90% had achieved a CD4 cell count of >200 cells/µl. There
is an ongoing debate in South Africa where some have suggested that HIV patients
may keep their CD4 counts at <200 cells/µl by intentionally missing
doses <xref ref-type="bibr" rid="pone.0017518-Kagee1">[48]</xref>,
<xref ref-type="bibr" rid="pone.0017518-Nattrass1">[49]</xref> to
retain eligibility for disability grants. However, this was firmly denied by our
participants, who rather ascribed missing doses to being away from home or
simply forgetting to take their pills. The interesting fact that half of our
patients used their mobile phones as a medication reminder opens up future
opportunities of systematic adherence support through text reminders since cell
phone access and usage are rapidly increasing throughout sub-Saharan Africa
<xref ref-type="bibr" rid="pone.0017518-Richard1">[50]</xref>.
Additionally, dispensing ART for more than 30 days at a time may also reduce the
risk of missed doses.</p><p>VL measurements are rarely available in most resource-limited settings and where
measured, virologic failure has often been defined as VL >400, >1,000 or
even >5,000 copies/ml <xref ref-type="bibr" rid="pone.0017518-ElKhatib1">[15]</xref>, <xref ref-type="bibr" rid="pone.0017518-Ford1">[29]</xref>, <xref ref-type="bibr" rid="pone.0017518-Boulle1">[30]</xref>. In this study, a more sensitive and conservative
definition for virologic failure was used, >50 copies/ml. While the fact that
some patients with intermittent viremia (blips) were included may cause some
concern, 85% (75/88) were confirmed viremic in two sequential assessments
>50 copies/ml. In this study, we used <95% as a conservative
cut-off point for incomplete adherence. In early adherence studies, including
unboosted protease inhibitors (PIs), a 95% adherence level was shown to
be associated with high virologic suppression <xref ref-type="bibr" rid="pone.0017518-Paterson1">[51]</xref>, a greater increase in
CD4 cell count, and lower hospitalization rates <xref ref-type="bibr" rid="pone.0017518-LowBeer1">[52]</xref>, <xref ref-type="bibr" rid="pone.0017518-Nachega2">[53]</xref>. More recent studies have
indicated that moderate adherence levels (70–90%) may be enough to
achieve acceptable virologic suppression with antiretroviral regimens containing
boosted PIs or NNRTIs. However, at the 95% level we can be quite certain
that a very small proportion of individuals on NNRTI are likely to fail
virologically <xref ref-type="bibr" rid="pone.0017518-Shuter1">[54]</xref>, <xref ref-type="bibr" rid="pone.0017518-Nachega3">[55]</xref>, <xref ref-type="bibr" rid="pone.0017518-Martin1">[56]</xref>. The aim of the current study was to look at
treatment failure among long-term recipients of ART, i.e. excluded those with
<12 months of ART <xref ref-type="bibr" rid="pone.0017518-ElKhatib1">[15]</xref>. However, our retrospective assessment of medical
charts went back and traced all virologic failures, including the first year on
treatment, enabling us to assess the risk of failure from treatment start-up to
a maximum follow-up of over 8 years. However, with this design, we missed those
who first failed virologically and then dropped out of the programme before
reaching 12 months on treatment. Given that a substantial proportion of patients
enrolled in ART in similar urban settings are expected to drop out early <xref ref-type="bibr" rid="pone.0017518-Unge1">[57]</xref>, this would
lead to an underestimation of the true virologic failure rate among NNRTI
recipients in the current assessment.</p><p>Finally, the lack of a significant association between longer documented
treatment interruptions and virologic failure is likely due to incomplete
clinical data since we only had access to reported interruptions recorded in the
medical charts.</p><p>In summary, there was a strong association between cumulative reduced adherence
to drug-refill visits and both virologic and immunologic failure. One in five
failed virologically, the majority within the first two years on ART. On-time
ART pick-up appears to be a feasible tool to identify individuals at risk, and
if followed by prompt and targeted interventions, it could be used to reduce the
rate of virologic failure.</p></sec></sec></body><back><ack><p>We would like to thank Ms. Albertina Dambuza, Belinda Dambuza and Johanna Ledwaba for
assisting in reviewing medical records; Ms Ntshebo Mirriam Moeketsi and Alina
Malebye for conducting interviews, and Noreen Boikanyo, Rebecca Phofa, Catherine
Lephoto, Agnes Ramashiga and Fikile Mbatha for study logistics. We are grateful to
all patients for sharing their experiences with us.</p></ack><fn-group><fn fn-type="conflict"><p><bold>Competing Interests: </bold>The authors have declared that no competing interests exist.</p></fn><fn fn-type="financial-disclosure"><p><bold>Funding: </bold>This study was funded by the Swedish International Development Cooperation Agency
to National Institute for Communicable Diseases (NICD) and Karolinska
Institutet; The Karolinska Institutet (PhD student grant to ZEK and senior
research grant to AME); Sven Gard's Fund for Virology Research, African
Programme for Training in HIV/TB Research Fogarty International Center/NIH 2 U2R
TW006878 and the Freeman-Spogli Institute at Stanford University to ZEK. The
funders had no role in study design, data collection and analysis, decision to
publish, or preparation of the manuscript.</p></fn></fn-group><ref-list><title>References</title><ref id="pone.0017518-World1"><label>1</label><element-citation publication-type="book"><collab>World Health Organization (WHO), Joint United Nations Programme on
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