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<article xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:mml="http://www.w3.org/1998/Math/MathML" article-type="research-article"><?properties manuscript?><front><journal-meta><journal-id journal-id-type="nlm-journal-id">100892005</journal-id><journal-id journal-id-type="pubmed-jr-id">21821</journal-id><journal-id journal-id-type="nlm-ta">J Acquir Immune Defic Syndr</journal-id><journal-id journal-id-type="iso-abbrev">J Acquir Immune Defic Syndr</journal-id><journal-title-group><journal-title>Journal of acquired immune deficiency syndromes (1999)</journal-title></journal-title-group><issn pub-type="ppub">1525-4135</issn><issn pub-type="epub">1944-7884</issn></journal-meta><article-meta><article-id pub-id-type="pmid">31343455</article-id><article-id pub-id-type="pmc">6854523</article-id><article-id pub-id-type="doi">10.1097/QAI.0000000000002142</article-id><article-id pub-id-type="manuscript">HHSPA1055707</article-id><article-categories><subj-group subj-group-type="heading"><subject>Article</subject></subj-group></article-categories><title-group><article-title>Antiretroviral Adherence Level Necessary for HIV Viral Suppression
Using Real-World Data</article-title></title-group><contrib-group><contrib contrib-type="author"><name><surname>Byrd</surname><given-names>Kathy K.</given-names></name><degrees>MD, MPH</degrees><xref ref-type="aff" rid="A1">a</xref></contrib><contrib contrib-type="author"><name><surname>Hou</surname><given-names>John G.</given-names></name><degrees>PhD</degrees><xref ref-type="aff" rid="A2">b</xref></contrib><contrib contrib-type="author"><name><surname>Hazen</surname><given-names>Ron</given-names></name><degrees>MPH</degrees><xref ref-type="aff" rid="A2">b</xref></contrib><contrib contrib-type="author"><name><surname>Kirkham</surname><given-names>Heather</given-names></name><degrees>PhD, MPH</degrees><xref ref-type="aff" rid="A2">b</xref></contrib><contrib contrib-type="author"><name><surname>Suzuki</surname><given-names>Sumihiro</given-names></name><degrees>PhD</degrees><xref ref-type="aff" rid="A3">c</xref></contrib><contrib contrib-type="author"><name><surname>Clay</surname><given-names>Patrick G.</given-names></name><degrees>PharmD</degrees><xref ref-type="aff" rid="A4">d</xref></contrib><contrib contrib-type="author"><name><surname>Bush</surname><given-names>Tim</given-names></name><degrees>MS</degrees><xref ref-type="aff" rid="A1">a</xref></contrib><contrib contrib-type="author"><name><surname>Camp</surname><given-names>Nasima M.</given-names></name><degrees>MPH</degrees><xref ref-type="aff" rid="A5">e</xref></contrib><contrib contrib-type="author"><name><surname>Weidle</surname><given-names>Paul J.</given-names></name><degrees>PharmD, MPH</degrees><xref ref-type="aff" rid="A1">a</xref></contrib><contrib contrib-type="author"><name><surname>Delpino</surname><given-names>Ambrose</given-names></name><degrees>PharmD</degrees><xref ref-type="aff" rid="A6">f</xref></contrib><on-behalf-of>for the Patient-Centered HIV Care Model Team</on-behalf-of></contrib-group><aff id="A1"><label>a</label>Division of HIV/AIDS Prevention, Centers for Disease
Control and Prevention, Atlanta, GA</aff><aff id="A2"><label>b</label>Health Analytics, Research, and Reporting Department,
Walgreen Co., Deerfield, IL</aff><aff id="A3"><label>c</label>Department of Biostatistics and Epidemiology, University of
North Texas Health Science Center, Fort Worth, TX</aff><aff id="A4"><label>d</label>Department of Pharmacotherapy, University of North Texas
Health Science Center System College of Pharmacy, Fort Worth, TX</aff><aff id="A5"><label>e</label>Department of Health, Research, Informatics, and
Technology, ICF, Atlanta, GA</aff><aff id="A6"><label>f</label>Patient Care and Advocacy Department, Walgreen Co.,
Deerfield, IL.</aff><author-notes><corresp id="CR1">Correspondence to: Kathy K. Byrd, MD, MPH, Division of HIV/AIDS
Prevention, Centers for Disease Control and Prevention, 1600 Clifton Road, MS
E-45, Atlanta, GA 30329 (<email>gdn8@cdc.gov</email>).</corresp></author-notes><pub-date pub-type="nihms-submitted"><day>21</day><month>10</month><year>2019</year></pub-date><pub-date pub-type="ppub"><day>01</day><month>11</month><year>2019</year></pub-date><pub-date pub-type="pmc-release"><day>01</day><month>11</month><year>2020</year></pub-date><volume>82</volume><issue>3</issue><fpage>245</fpage><lpage>251</lpage><!--elocation-id from pubmed: 10.1097/QAI.0000000000002142--><abstract id="ABS1"><sec id="S1"><title>Background:</title><p id="P1">A benchmark of near-perfect adherence (&#x02265;95%) to antiretroviral
therapy (ART) is often cited as necessary for HIV viral suppression.
However, given newer, more effective ART medications, the threshold for
viral suppression may be lower. We estimated the minimum ART adherence level
necessary to achieve viral suppression.</p></sec><sec id="S2"><title>Settings:</title><p id="P2">The Patient-centered HIV Care Model demonstration project.</p></sec><sec id="S3"><title>Methods:</title><p id="P3">Adherence to ART was calculated using the proportion of days covered
measure for the 365-day period before each viral load test result, and
grouped into 5 categories (&#x0003c;50%, 50% to &#x0003c;80%, 80% to
&#x0003c;85%, 85% to &#x0003c;90%, and &#x02265;90%). Binomial regression
analyses were conducted to determine factors associated with viral
suppression (HIV RNA &#x0003c;200 copies/mL); demographics, proportion of
days covered category, and ART regimen type were explanatory variables.
Generalized estimating equations with an exchangeable working correlation
matrix accounted for correlation within subjects. In addition, probit
regression models were used to estimate adherence levels required to achieve
viral suppression in 90% of HIV viral load tests.</p></sec><sec id="S4"><title>Results:</title><p id="P4">The adjusted odds of viral suppression did not differ between persons
with an adherence level of 80% to &#x0003c;85% or 85% to &#x0003c;90% and
those with an adherence level of &#x02265;90%. In addition, the overall
estimated adherence level necessary to achieve viral suppression in 90% of
viral load tests was 82% and varied by regimen type; integrase inhibitor-
and nonnucleoside reverse transcriptase inhibitor-based regimens achieved
90% viral suppression with adherence levels of 75% and 78%,
respectively.</p></sec><sec id="S5"><title>Conclusions:</title><p id="P5">The ART adherence level necessary to reach HIV viral suppression may
be lower than previously thought and may be regimen-dependent.</p></sec></abstract><kwd-group><kwd>HIV</kwd><kwd>antiretroviral therapy</kwd><kwd>viral suppression</kwd><kwd>sustained virologic response</kwd><kwd>medication adherence</kwd></kwd-group></article-meta></front><body><sec id="S6"><title>INTRODUCTION</title><p id="P6">The ultimate goal of HIV care and treatment is to improve the duration and
quality of life of persons with HIV. These goals are met through suppression of HIV
RNA and restoration of immune function, which in turn decrease morbidity and
mortality.<sup><xref rid="R1" ref-type="bibr">1</xref>&#x02013;<xref rid="R4" ref-type="bibr">4</xref></sup> Viral suppression has population level
benefits as well, in that persons who are virally suppressed have effectively no
risk of sexually transmitting HIV to uninfected partners.<sup><xref rid="R5" ref-type="bibr">5</xref></sup> To become and remain virologically
suppressed, persons with HIV must be adherent to appropriate antiretroviral therapy
(ART) throughout their lifetime. Although adherence is important to the outcomes of
therapy, patients face multiple barriers to consistent adherence including lack of
access, treatment fatigue, stigma, and comorbid conditions.<sup><xref rid="R6" ref-type="bibr">6</xref>,<xref rid="R7" ref-type="bibr">7</xref></sup></p><p id="P7">Given patients&#x02019; adherence barriers, potential history of nonadherence
to therapy, and lifelong need for treatment, having a better understanding of what
ART adherence level is necessary for viral suppression is valuable for clinicians
when determining optimal antiretroviral (ARV) regimens for patients. Researchers
have frequently set a benchmark for adherence at &#x02265;95%. This threshold is
mostly derived from a study conducted between 1997 and 1999, of persons on unboosted
protease inhibitor therapy, which found that persons with adherence levels
&#x02265;95% (measured using a microelectronic monitoring system) had less virologic
failure and increased CD4 lymphocyte count when compared with persons with adherence
&#x0003c;95%.<sup><xref rid="R8" ref-type="bibr">8</xref></sup> Other early
studies showed similar results.<sup><xref rid="R9" ref-type="bibr">9</xref>,<xref rid="R10" ref-type="bibr">10</xref></sup> Although 95% has long been
considered the gold standard of adherence to ART, a lower adherence level of
&#x02265;90% has been set by the Pharmacy Quality Alliance.<sup><xref rid="R11" ref-type="bibr">11</xref></sup> Given the enhanced pharmacokinetic profiles
of newer ARV medications, even the lower adherence level of &#x02265;90% may not be
necessary to achieve HIV viral suppression.<sup><xref rid="R12" ref-type="bibr">12</xref></sup> As such, we used data from a national demonstration project
to estimate the minimum adherence level required for HIV viral suppression.</p></sec><sec id="S7"><title>METHODS</title><sec id="S8"><title>Project Design and Participants</title><p id="P8">Data used for this analysis are from the Patient-centered HIV Care Model
(PCHCM) demonstration project. This was a secondary analysis; the results are
unrelated to the goals of the demonstration project. The PCHCM is described in
detail elsewhere.<sup><xref rid="R13" ref-type="bibr">13</xref></sup> In short,
the PCHCM project partnered community-based HIV-specialty pharmacists with HIV
medical providers and required the partnered pharmacists and medical providers
to share patient clinical information, identify therapy-related problems, and
develop therapy-related action plans. The project provided services to 765
adults with HIV at 10 project sites (made up of &#x02265;1 medical clinic and
&#x02265;1 HIV-specialty retail pharmacy) throughout the United States from
August 2014 to September 2016. Data collected for the PCHCM included, but were
not limited to, prescription fulfillment data, HIV viral load test results, and
participant demographics. Between 12 and 48 months of data were collected on
each participant.</p></sec><sec id="S9"><title>Independent Variable&#x02014;Adherence to ART</title><p id="P9">Adherence to ART was calculated as the proportion of days covered (PDC).
The PDC is a pharmacy claims-based metric that reflects the proportion of days
for which a person has medication available during a measurement period. The ART
PDC is calculated by dividing the number of days of ART coverage during the
measurement period by the length of the measurement period; adjustments are made
for fill days&#x02019; supply and for days with overlapping medication
supply.<sup><xref rid="R14" ref-type="bibr">14</xref></sup> ART coverage
was defined as at least 3 ARV medication components (excluding cobicistat). Data
were extracted from PCHCM pharmacy fulfillment records.</p><p id="P10">Adherence to ART was calculated for the 365-day period before each viral
load test result, and was grouped into one of 5 PDC categories (&#x0003c;50%, 50%
to &#x0003c;80%, 80% to &#x0003c;85%, 85% to &#x0003c;90%, and &#x02265;90%).
Adherence was calculated overall and by ARV regiment type. ARV regimens were
grouped into 4 categories: (1) integrase inhibitor (INSTI)-based, (2)
nonnucleoside reverse transcriptase inhibitor (NNRTI)-based, (3) protease
inhibitor (PI)-based (included both boosted and nonboosted regimens), and (4)
&#x0201c;all other types&#x0201d; (all regimens not categorized as an INSTI-,
NNRTI- or PI-based (eg, INSTI-two-NRTI-PI). The INSTI-, NNRTI-, and PI-based
regimens each included one medication of the main component (eg, one INSTI
medication) and 2 nucleoside reverse transcriptase inhibitors (NRTI) as the
&#x0201c;backbone&#x0201d; of the therapy. Because a person could be on more than
one regimen during the 365-day adherence measurement period, a primary regimen
type was identified as the regimen that was used for the plurality of the
measurement period.</p></sec><sec id="S10"><title>Outcome Variable&#x02014;HIV Viral Suppression</title><p id="P11">The dependent variable for the analysis was a dichotomous indicator of
HIV viral suppression, defined as an HIV viral load of &#x0003c;200 HIV RNA
copies/mL.<sup><xref rid="R15" ref-type="bibr">15</xref></sup> The
suppression value of &#x0003c;200 copies/mL was based on the U.S. Department of
Health and Human Services recommended definition of virologic failure.<sup><xref rid="R1" ref-type="bibr">1</xref></sup> Each viral load test result was
included in the analysis if the test had a corresponding 365 days of ART
fulfillment data before the test result (so that each viral load would have a
corresponding PDC value). Each viral load test result with a corresponding PDC
value was included in the analysis even when multiple viral load test results
for the same participant had overlapping adherence windows (ie, a person had
more than one viral load test within a 365-day adherence measurement period).
Laboratory test result data were abstracted from project clinic records.</p></sec><sec id="S11"><title>Statistical Analysis</title><p id="P12">Bivariate and multivariable binomial regression analyses were used to
determine factors associated with viral suppression. Generalized estimating
equations with an exchangeable working correlation matrix were used to account
for correlation within subjects. Odds ratios with 95% confidence intervals (CI)
were calculated, separately, for each demographic factor (age, sex,
race/ethnicity, and insurance type), categorical PDC level, and ARV regimen
type. All demographic variables were considered for inclusion in the final
multivariable model. The final model was determined using forward stepwise
variable selection, and included all factors that were significant at the 0.05
level. In addition, probit regression models were used to create dose-response
curves and to estimate the adherence level required to achieve viral suppression
in 90% of HIV viral load tests, overall and by regimen category. All data were
analyzed using SAS version 9.4 (SAS Institute, Cary, NC).</p></sec></sec><sec id="S12"><title>RESULTS</title><p id="P13">Of the 765 participants, 570 had &#x02265;1 HIV viral load test result with a
corresponding PDC value and were, therefore, eligible for the analysis. More than
half of these individuals were aged &#x02265;50 years (53%), non-black or of unknown
race/ ethnicity (59%), men (78%), and nonprivately insured (85%) (<xref rid="T1" ref-type="table">Table 1</xref>). Each person&#x02019;s record contributed a
median of 4 viral load test results (interquartile range [IQR]: 2&#x02013;6) to the
analysis. More than half (67%) of the 2427 viral load test results, included in the
analysis, coincided with a PDC &#x02265;90% in the previous 365 days and most (90%)
were &#x0003c;200 copies/mL. The primary regimen types were: INSTI-based (31%),
&#x0201c;all other&#x0201d; (30%), NNRTI-based (21%), and PI-based (18%) (<xref rid="T1" ref-type="table">Table 1</xref>).</p><sec id="S13"><title>Bivariate and Multivariable Binomial Regression</title><p id="P14">Results from the bivariate and multivariable analyses are shown in <xref rid="T2" ref-type="table">Table 2</xref>. After adjusting for all covariates
and within person correlations, persons aged &#x02265;50 years (adjusted odds
ratio [aOR] 2.33; 95% CI: 1.70 to 3.21), men (aOR 1.49; 1.07, 2.08), and
privately insured persons (aOR 1.77; 1.04, 3.00) had greater odds of being
virally suppressed compared with persons aged &#x0003c;50 years, women, and
nonprivately insured persons, respectively. Non-Hispanic black persons had lower
odds of suppression (aOR 0.46; 0.33, 0.64) compared with all other races and
ethnicities combined (including persons with unknown race/ethnicity).</p><p id="P15">There were no significant differences in the adjusted odds of viral
suppression for persons with a PDC of 80% to &#x0003c;85% or 85% to &#x0003c;90%
compared with that of persons with a PDC of &#x02265;90%. Persons within the
&#x0201c;all other&#x0201d; regimen category had lower adjusted odds (aOR 0.51;
0.34, 0.77) of suppression when compared with persons on PI-based regimens.
Persons on INSTI- or NNRTI-based regimens did not have significantly different
adjusted odds of suppression when compared with persons on PI-based
regimens.</p></sec><sec id="S14"><title>Probit Regression</title><p id="P16">Results from the probit regression model are presented in <xref rid="F1" ref-type="fig">Figure 1</xref>. Among all regimen types, the adherence level
required to achieve viral suppression in 90% of HIV viral load tests was 82%
(<xref rid="F1" ref-type="fig">Fig. 1A</xref>). The adherence level required
to achieve viral suppression in 90% of tests varied depending on ARV regimen
type: 75% for INSTI-based, 78% for NNRTI-based, 87% for PI-based, and 99% for
&#x0201c;all other&#x0201d; regimen types (<xref rid="F1" ref-type="fig">Fig.
1B</xref>).</p></sec></sec><sec id="S15"><title>DISCUSSION</title><p id="P17">After adjusting for demographic factors, within-person correlation, and ARV
regimen type, we found that the odds of viral suppression did not differ
significantly between persons with adherence levels between 80% and &#x0003c;85% or
85% to &#x0003c;90% and those with the Pharmacy Quality Alliance recommended
adherence level of &#x02265;90%. In addition, the overall estimated adherence level
necessary to achieve viral suppression in 90% of HIV viral load tests was 82% and
varied by regimen type; 90% of viral load tests associated with INSTI-based and
NNRTI-based regimens were virally suppressed at adherence levels of 75% and 78%,
respectively. These results indicate that the adherence level necessary to reach
viral suppression may be lower than previously believed and may be more in line with
the 80% adherence threshold often applied for other chronic diseases (eg,
hypertension, hypercholesterolemia).<sup><xref rid="R16" ref-type="bibr">16</xref></sup></p><p id="P18">Previous studies on the adherence threshold required for viral suppression
are heterogeneous and often differ in the outcome of interest (eg, HIV RNA level of
&#x0003c;50, &#x0003c;200, or &#x0003c;400 copies/mL), the adherence measure (eg,
self-report, pill counts, medication possession ratios, and proportion of days
covered), and the threshold for failure (eg, 10% or 20% of persons not suppressed)
which makes comparisons between this and other studies somewhat difficult.<sup><xref rid="R17" ref-type="bibr">17</xref>&#x02013;<xref rid="R22" ref-type="bibr">22</xref></sup> However, our finding of no significant difference in the
adjusted odds of viral suppression with adherence between 80% and &#x0003c;85% or 85%
to &#x0003c;90% and &#x02265;90% is consistent with like studies.<sup><xref rid="R17" ref-type="bibr">17</xref>&#x02013;<xref rid="R23" ref-type="bibr">23</xref></sup> For example, a meta-analysis of 43 studies which evaluated
adherence thresholds and virologic outcomes, found no significant difference in the
pooled odds of virologic failure at adherence levels of &#x02265;95% or
&#x02265;98%&#x02013;100% and adherence levels of &#x02265;80%&#x02013;90%.<sup><xref rid="R21" ref-type="bibr">21</xref></sup> Similarly, using adherence
self-report from a cohort study of men who have sex with men, Viswanathan et
al<sup><xref rid="R17" ref-type="bibr">17</xref></sup> found that
&#x02265;80% of persons were virally suppressed (&#x0003c;50 copies/mL) at adherence
levels between 80% and 84%.</p><p id="P19">Although the adjusted odds of suppression were not statistically different
between either INSTI-based or NNRTI-based regimens when compared with PI-based
regimens, PI-based regimens required a higher adherence level to achieve viral
suppression. Although this analysis was not powered to evaluate differences between
regimen types, the higher adherence threshold we observed for PI-based regimens, is
similar to other studies.<sup><xref rid="R18" ref-type="bibr">18</xref>,<xref rid="R20" ref-type="bibr">20</xref>,<xref rid="R22" ref-type="bibr">22</xref>,<xref rid="R24" ref-type="bibr">24</xref>,<xref rid="R25" ref-type="bibr">25</xref></sup> However, our analysis did not distinguish
between boosted and unboosted PI-based regimens, which might have accounted for some
of the threshold differences. Regimens categorized as &#x0201c;all other&#x0201d; had
lower adjusted odds of suppression and the highest adherence level necessary for
viral suppression. The higher adherence level required for viral suppression with
&#x0201c;all other&#x0201d; regimen types is not surprising given that this category
includes regimens not considered adequate by treatment guidelines and because this
category may represent non-standard or salvage regimens for persons who had
previously failed therapy.<sup><xref rid="R1" ref-type="bibr">1</xref></sup></p><p id="P20">When examining the study&#x02019;s &#x0201c;All regimen types&#x0201d;
dose-response curve, high proportions of viral load tests were suppressed even with
adherence levels around 60%. This result is similar to that of Gordon et
al<sup><xref rid="R19" ref-type="bibr">19</xref></sup> who found a virologic
failure rate (defined as 2 consecutive viral loads test results &#x02265;200
copies/mL) for 3 first-line ARV regimens of approximately 20% at adherence levels of
roughly 60%. The modest adherence levels necessary for viral suppression, seen in
this analysis, is reflective of the improved potency and efficacy of newer ARV
medications.<sup><xref rid="R12" ref-type="bibr">12</xref></sup></p><p id="P21">Non-Hispanic black persons, younger persons and women had lower odds of
viral suppression even after adjustment for adherence level and regimen category;
the reasons for this are unclear. However, achieving viral suppression is dependent
on factors additional to adherence such as underlying drug resistance and
drug&#x02013;drug or drug&#x02013;food interactions, which can affect effectiveness of
therapy.<sup><xref rid="R26" ref-type="bibr">26</xref>&#x02013;<xref rid="R28" ref-type="bibr">28</xref></sup> This analysis was unable to
account for these other determinants of viral suppression in any demographic
group.</p><p id="P22">Although we estimate that an overall adherence level of 82% is necessary for
viral suppression in 90% of viral load tests, with lower thresholds for INSTI- and
NNRTI-based regimens, these results should be used with caution. In addition to the
risk of virologic rebound, poor adherence is associated with development of drug
resistance (which can potentially reduce future treatment options), systemic
inflammation, and higher health care use and costs.<sup><xref rid="R21" ref-type="bibr">21</xref>,<xref rid="R22" ref-type="bibr">22</xref>,<xref rid="R29" ref-type="bibr">29</xref>&#x02013;<xref rid="R34" ref-type="bibr">34</xref></sup> In particular, drug resistance is more common with
NNRTI-based regimens in the absence of viral suppression.<sup><xref rid="R29" ref-type="bibr">29</xref></sup> Clinicians&#x02019; message to patients
should, therefore, remain &#x0201c;every dose every day&#x0201d; and be accompanied by
continuous adherence counseling and support.<sup><xref rid="R35" ref-type="bibr">35</xref></sup> These results may be useful when considering
patients&#x02019; adherence barriers and optimal ARV regimens for these patients. In
addition, a PDC of &#x02265;82% may be sufficient to indicate adequate adherence when
measuring PDC levels in pharmacy claims or fulfillment data not linked to viral load
test results.</p><p id="P23">The study results should be viewed in light of its limitations. First, the
PDC is a proxy for adherence. The PDC measures the amount of time a person has
medication available, not actual pill-taking behavior; therefore, adherence was
likely overestimated. In addition, the PDC does not measure 2 other important facets
of adherence: whether a person takes their medication according to the
prescriber&#x02019;s instruction or on the prescribed schedule. However, using
pharmacy fulfillment data to calculate adherence has an advantage over some other
methods (eg, self-report, pill counts, and electronic monitoring) that are
potentially confounded by social desirability and recall bias or expense.<sup><xref rid="R36" ref-type="bibr">36</xref></sup> For this analysis, accurate PDC
measurement required a closed pharmacy system; adherence would be underestimated if
persons filled ARV prescriptions outside of the project pharmacy network. This
analysis did not take into account the amount of time a person was virally
suppressed; therefore, the analysis did not account for the decreased risk of
virologic failure after prolonged periods of viral suppression.<sup><xref rid="R37" ref-type="bibr">37</xref></sup> In addition, the analysis did not account
for time since treatment initiation. The analysis, therefore, did not account for
potentially higher adherence needed to achieve viral suppression in the first year
after treatment initiation. Finally, participants in the PCHCM demonstration project
represented a convenience sample which limits generalizability.</p><p id="P24">These data indicate that overall HIV viral suppression can be achieved for
90% of HIV viral load tests with an estimated ART adherence level of 82%, which is
similar to that applied to other chronic diseases. The adherence threshold varied by
regimen type with both INSTI-based and NNRTI-based regimens achieving viral
suppression with even lower adherence levels (75% and 78%, respectively), suggesting
that some regimen types may be more forgiving of missed doses than others. These
results are reflective of the improved potency and efficacy of newer ARV
medications. Although this analysis found an adherence level necessary for viral
suppression that was lower than the conventionally reported values of &#x02265;90% or
&#x02265;95%, clinicians should be encouraged to continue to advise patients to take
all of their medications, as prescribed, to identify and address adherence barriers
and to offer continuous adherence support.</p></sec></body><back><ack id="S16"><p id="P25">Supported by the U.S. Department of Health and Human Services
Secretary&#x02019;s Minority AIDS Initiative fund and the Centers for Disease Control
and Prevention through a co-operative agreement [grant number NU65PS004275] with the
University of North Texas Health Science Center System College of Pharmacy. Walgreen
Co., provided all services in-kind.</p><p id="P26">The findings and conclusions of this analysis are those of the authors and
do not necessarily represent the official position of the Centers for Disease
Control and Prevention.</p></ack><fn-group><fn fn-type="COI-statement" id="FN1"><p id="P28">J.G.H., R.H., H.K., and A.D. report that they were employees of Walgreen
Co., during the conduct of this study. The remaining authors have no conflicts
of interest to disclose.</p></fn><fn id="FN2"><p id="P29">Members of Patient-Centered HIV Care Model Team are listed in <xref rid="APP1" ref-type="app">Appendix1</xref>.</p></fn></fn-group><app-group><app id="APP1"><label>APPENDIX 1.</label><title>The Patient-centered HIV Care Model Team</title><p id="P27">Michael Aguirre, Osayi Akinbosoye, David M. Bamberger, Ben Bluml, Katura
Bullock, Diane C. Burrell, Tim Bush, Clifton Bush, Kathy K. Byrd, Chad Cadwell,
Nasima M. Camp, Roberto Cardarelli, Terri Clark, Patrick Clay, Andrew Crim,
Angela Cure, Kristin Darin, Traci Dean, W. Ambrose Delpino, Michael DeMayo,
Shara Elrod, Ashley L. Eschmann, David Farmer, Rose Farnan, Heather Free, Andrew
Gudzelak, Andrew Halbur, Felicia Hardnett, Ronald Hazen, Heidi Hilker, John Hou,
Brian Hujdich, Lisa Johnson, Heather Kirkham, James Lecounte, Sayuri Lio,
Guanzhong Lo, Sondra Middleton, Brittany Mills, Stacy Muckelroy, Christopher M.
Nguyen, Linda Ortiz, Glen Pietrandoni, Kim Scarsi, Jon Schommer, Michael D.
Shankle, Ram Shrestha, Daron Smith, Sumihiro Suzuki, Michael S. Taitel, Gebeyehu
N. Teferi, Vikas Tomer, Louis Terres, Paul J. Weidle, Carmelita Whitfield, and
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distribution function for the standard normal distribution; &#x02021;INSTI,
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suppression and the dotted vertical lines represent the PDC level at which 90%
of HIV viral load tests were suppressed (HIV RNA &#x0003c;200 copies/mL).</p></caption><graphic xlink:href="nihms-1055707-f0001"/></fig><table-wrap id="T1" position="float" orientation="portrait"><label>TABLE 1.</label><caption><p id="P31">Characteristics of Patients and Viral Load Tests Included in the
Analysis, Patient-Centered HIV Care Model, 2014&#x02013;2016, United States</p></caption><table frame="hsides" rules="groups"><colgroup span="1"><col align="left" valign="middle" span="1"/><col align="left" valign="middle" span="1"/></colgroup><thead><tr><th align="left" valign="top" rowspan="1" colspan="1">Characteristic</th><th align="center" valign="top" rowspan="1" colspan="1">Total</th></tr></thead><tbody><tr><td align="left" valign="top" rowspan="1" colspan="1">Patient characteristics, n = 570</td><td align="center" valign="top" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Median age (years [IQR])</td><td align="center" valign="top" rowspan="1" colspan="1">49 (40&#x02013;57)</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Median no. of viral load tests (IQR)</td><td align="center" valign="top" rowspan="1" colspan="1">4 (2&#x02013;6)</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Characteristic, n (%)</td><td align="center" valign="top" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Age (yrs)</td><td align="center" valign="top" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">&#x02003;&#x0003c;50</td><td align="center" valign="top" rowspan="1" colspan="1">268 (47)</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">&#x02003;&#x02265;50</td><td align="center" valign="top" rowspan="1" colspan="1">302 (53)</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Race/Ethnicity</td><td align="center" valign="top" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">&#x02003;Black, non-Hispanic</td><td align="center" valign="top" rowspan="1" colspan="1">231 (41)</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">&#x02003;All other/unknown</td><td align="center" valign="top" rowspan="1" colspan="1">339 (59)</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Sex</td><td align="center" valign="top" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">&#x02003;Male</td><td align="center" valign="top" rowspan="1" colspan="1">444 (78)</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">&#x02003;Female</td><td align="center" valign="top" rowspan="1" colspan="1">126 (22)</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Medical insurance</td><td align="center" valign="top" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">&#x02003;Private insurance</td><td align="center" valign="top" rowspan="1" colspan="1">83 (15)</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">&#x02003;Nonprivate insurance</td><td align="center" valign="top" rowspan="1" colspan="1">487 (85)</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Viral load test characteristics, n = 2427<xref rid="TFN1" ref-type="table-fn">*</xref></td><td align="center" valign="top" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">PDC category, n (%)</td><td align="center" valign="top" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">&#x02003;&#x0003c;50%</td><td align="center" valign="top" rowspan="1" colspan="1">202 (8)</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">&#x02003;50% to &#x0003c;80%</td><td align="center" valign="top" rowspan="1" colspan="1">277 (11)</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">&#x02003;80% to &#x0003c;85%</td><td align="center" valign="top" rowspan="1" colspan="1">162 (7)</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">&#x02003;85% to &#x0003c;90%</td><td align="center" valign="top" rowspan="1" colspan="1">173 (7)</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">&#x02003;&#x02265;90%</td><td align="center" valign="top" rowspan="1" colspan="1">1613 (67)</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Viral load test results, n (%)</td><td align="center" valign="top" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">&#x02003;&#x0003c;200 copies/mL</td><td align="center" valign="top" rowspan="1" colspan="1">2180 (90)</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">&#x02003;&#x02265;200 copies/mL</td><td align="center" valign="top" rowspan="1" colspan="1">247 (10)</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">ARV regimen category, n (%)<xref rid="TFN2" ref-type="table-fn">&#x02020;</xref></td><td align="center" valign="top" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">&#x02003;INSTI-based</td><td align="center" valign="top" rowspan="1" colspan="1">756 (31)</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">&#x02003;NNRTI-based</td><td align="center" valign="top" rowspan="1" colspan="1">513 (21)</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">&#x02003;PI-Based</td><td align="center" valign="top" rowspan="1" colspan="1">427 (18)</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">&#x02003;All other<xref rid="TFN3" ref-type="table-fn">&#x02021;</xref></td><td align="center" valign="top" rowspan="1" colspan="1">731 (30)</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">&#x02003;&#x02003;INSTI-NRTI(2)-PI<xref rid="TFN4" ref-type="table-fn">&#x000a7;</xref></td><td align="center" valign="top" rowspan="1" colspan="1">122 (17)</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">&#x02003;&#x02003;INSTI -NNRTI-PI<xref rid="TFN4" ref-type="table-fn">&#x000a7;</xref></td><td align="center" valign="top" rowspan="1" colspan="1">79 (11)</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">&#x02003;&#x02003;INSTI -PI<xref rid="TFN4" ref-type="table-fn">&#x000a7;</xref></td><td align="center" valign="top" rowspan="1" colspan="1">65 (9)</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">&#x02003;&#x02003;INSTI -NNRTI-NRTI(2)<xref rid="TFN4" ref-type="table-fn">&#x000a7;</xref></td><td align="center" valign="top" rowspan="1" colspan="1">53 (7)</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">&#x02003;&#x02003;NRTI(2)-PI(2)<xref rid="TFN4" ref-type="table-fn">&#x000a7;</xref></td><td align="center" valign="top" rowspan="1" colspan="1">43 (6)</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">&#x02003;&#x02003;NNRTI-NRTI(2)-PI<xref rid="TFN4" ref-type="table-fn">&#x000a7;</xref></td><td align="center" valign="top" rowspan="1" colspan="1">41 (6)</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">&#x02003;&#x02003;INSTI -NNRTI-NRTI<xref rid="TFN4" ref-type="table-fn">&#x000a7;</xref></td><td align="center" valign="top" rowspan="1" colspan="1">40 (6)</td></tr></tbody></table><table-wrap-foot><fn id="TFN1"><label>*</label><p id="P32">Viral load tests with PDC values and included in the analysis,
including the coinciding PDC category, viral load test value, and the
coinciding primary ARV regimen.</p></fn><fn id="TFN2"><label>&#x02020;</label><p id="P33">INSTI-, NNRTI-, and PI-based regimens each included one medication
of the main component and 2 nucleoside reverse transcriptase inhibitors
(NRTI) as the &#x0201c;backbone&#x0201d; of the therapy.</p></fn><fn id="TFN3"><label>&#x02021;</label><p id="P34">&#x0201c;All other&#x0201d; category includes all regimens not
categorized as an INSTI-, NNRTI-, or PI-based regimen.</p></fn><fn id="TFN4"><label>&#x000a7;</label><p id="P35">The most common regimens within the &#x0201c;all other&#x0201d;
category. The parentheses indicate the number of medication types within the
regimen.</p></fn></table-wrap-foot></table-wrap><table-wrap id="T2" position="float" orientation="portrait"><label>TABLE 2.</label><caption><p id="P36">Factors Associated With HIV Viral Suppression (HIV RNA Levels
&#x0003c;200 Copies/mL), Patient-centered HIV Care Model, 2014&#x02013;2016,
United States</p></caption><table frame="hsides" rules="groups"><colgroup span="1"><col align="left" valign="middle" span="1"/><col align="left" valign="middle" span="1"/><col align="left" valign="middle" span="1"/><col align="left" valign="middle" span="1"/><col align="left" valign="middle" span="1"/></colgroup><thead><tr><th align="left" valign="top" rowspan="1" colspan="1"/><th colspan="4" align="center" valign="top" rowspan="1">HIV RNA &#x0003c;200 copies/mL (n
= 2427)<hr/></th></tr><tr><th align="center" valign="top" rowspan="1" colspan="1"/><th align="center" valign="top" rowspan="1" colspan="1">Bivariate OR (95% CI)</th><th align="center" valign="bottom" rowspan="1" colspan="1"><italic>P</italic></th><th align="center" valign="top" rowspan="1" colspan="1">Multivariable aOR (95% CI)</th><th align="center" valign="bottom" rowspan="1" colspan="1"><italic>P</italic></th></tr></thead><tbody><tr><td align="left" valign="top" rowspan="1" colspan="1">Age &#x02265;50 yrs<xref rid="TFN5" ref-type="table-fn">*</xref></td><td align="center" valign="top" rowspan="1" colspan="1">3.16 (2.09 to 4.78)</td><td align="center" valign="top" rowspan="1" colspan="1">&#x0003c;0.0001</td><td align="center" valign="top" rowspan="1" colspan="1">2.33 (1.70 to 3.21)</td><td align="center" valign="top" rowspan="1" colspan="1">&#x0003c;0.0001</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Black, non-Hispanic<xref rid="TFN6" ref-type="table-fn">&#x02020;</xref></td><td align="center" valign="top" rowspan="1" colspan="1">0.30 (0.20 to 0.44)</td><td align="center" valign="top" rowspan="1" colspan="1">&#x0003c;0.0001</td><td align="center" valign="top" rowspan="1" colspan="1">0.46 (0.33 to 0.64)</td><td align="center" valign="top" rowspan="1" colspan="1">&#x0003c;0.0001</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Males</td><td align="center" valign="top" rowspan="1" colspan="1">2.51 (1.64 to 3.84)</td><td align="center" valign="top" rowspan="1" colspan="1">&#x0003c;0.0001</td><td align="center" valign="top" rowspan="1" colspan="1">1.49 (1.07 to 2.08)</td><td align="center" valign="top" rowspan="1" colspan="1">0.0174</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Private insurance<xref rid="TFN7" ref-type="table-fn">&#x02021;</xref></td><td align="center" valign="top" rowspan="1" colspan="1">2.08 (1.05 to 4.15)</td><td align="center" valign="top" rowspan="1" colspan="1">0.0364</td><td align="center" valign="top" rowspan="1" colspan="1">1.77 (1.04 to 3.00)</td><td align="center" valign="top" rowspan="1" colspan="1">0.0344</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">PDC level</td><td align="center" valign="top" rowspan="1" colspan="1"/><td align="center" valign="top" rowspan="1" colspan="1"/><td align="center" valign="top" rowspan="1" colspan="1"/><td align="center" valign="top" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">&#x02003;&#x0003c;50%</td><td align="center" valign="top" rowspan="1" colspan="1">0.16 (0.10 to 0.25)</td><td align="center" valign="top" rowspan="1" colspan="1">&#x0003c;0.0001</td><td align="center" valign="top" rowspan="1" colspan="1">0.16 (0.11 to 0.23)</td><td align="center" valign="top" rowspan="1" colspan="1">&#x0003c;0.0001</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">&#x02003;50% to &#x0003c;80%</td><td align="center" valign="top" rowspan="1" colspan="1">0.29 (0.20 to 0.43)</td><td align="center" valign="top" rowspan="1" colspan="1">&#x0003c;0.0001</td><td align="center" valign="top" rowspan="1" colspan="1">0.30 (0.19 to 0.47)</td><td align="center" valign="top" rowspan="1" colspan="1">&#x0003c;0.0001</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">&#x02003;80% to &#x0003c;85%</td><td align="center" valign="top" rowspan="1" colspan="1">0.50 (0.32 to 0.76)</td><td align="center" valign="top" rowspan="1" colspan="1">0.0013</td><td align="center" valign="top" rowspan="1" colspan="1">0.49 (0.23 to 1.04)</td><td align="center" valign="top" rowspan="1" colspan="1">0.0627</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">&#x02003;85% to &#x0003c;90%</td><td align="center" valign="top" rowspan="1" colspan="1">0.59 (0.37 to 0.93)</td><td align="center" valign="top" rowspan="1" colspan="1">0.0228</td><td align="center" valign="top" rowspan="1" colspan="1">0.96 (0.49 to 1.90)</td><td align="center" valign="top" rowspan="1" colspan="1">0.9138</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">&#x02003;&#x02265;90%</td><td align="center" valign="top" rowspan="1" colspan="1">REF</td><td align="center" valign="top" rowspan="1" colspan="1">&#x02014;</td><td align="center" valign="top" rowspan="1" colspan="1">REF</td><td align="center" valign="top" rowspan="1" colspan="1">&#x02014;</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">ARV regimen category<xref rid="TFN8" ref-type="table-fn">&#x000a7;</xref></td><td align="center" valign="top" rowspan="1" colspan="1"/><td align="center" valign="top" rowspan="1" colspan="1"/><td align="center" valign="top" rowspan="1" colspan="1"/><td align="center" valign="top" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">&#x02003;INSTI-based</td><td align="center" valign="top" rowspan="1" colspan="1">1.55 (0.94 to 2.54)</td><td align="center" valign="top" rowspan="1" colspan="1">0.0832</td><td align="center" valign="top" rowspan="1" colspan="1">1.38 (0.90 to 2.13)</td><td align="center" valign="top" rowspan="1" colspan="1">0.1391</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">&#x02003;NNRTI-based</td><td align="center" valign="top" rowspan="1" colspan="1">1.52 (0.88 to 2.65)</td><td align="center" valign="top" rowspan="1" colspan="1">0.1367</td><td align="center" valign="top" rowspan="1" colspan="1">1.21 (0.75 to 1.94)</td><td align="center" valign="top" rowspan="1" colspan="1">0.4342</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">&#x02003;PI-Based</td><td align="center" valign="top" rowspan="1" colspan="1">REF</td><td align="center" valign="top" rowspan="1" colspan="1">&#x02014;</td><td align="center" valign="top" rowspan="1" colspan="1">REF</td><td align="center" valign="top" rowspan="1" colspan="1">&#x02014;</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">&#x02003;All others</td><td align="center" valign="top" rowspan="1" colspan="1">0.79 (0.48 to 1.31)</td><td align="center" valign="top" rowspan="1" colspan="1">0.3598</td><td align="center" valign="top" rowspan="1" colspan="1">0.51 (0.34 to 0.77)</td><td align="center" valign="top" rowspan="1" colspan="1">0.0013</td></tr></tbody></table><table-wrap-foot><fn id="TFN5"><label>*</label><p id="P37">Persons aged &#x02265;50 years were compared with persons aged
&#x0003c;50 years.</p></fn><fn id="TFN6"><label>&#x02020;</label><p id="P38">Black, non-Hispanic persons were compared with persons of all other
race/ethnicities and persons with unknown race/ethnicity combined.</p></fn><fn id="TFN7"><label>&#x02021;</label><p id="P39">Persons with private insurance were compared with persons without
private insurance.</p></fn><fn id="TFN8"><label>&#x000a7;</label><p id="P40">INSTI-, NNRTI-, and PI-based regimens each included one medication
of the main component and 2 nucleoside reverse transcriptase (NRTI) drugs as
the &#x0201c;backbone&#x0201d; of the therapy.</p></fn></table-wrap-foot></table-wrap></floats-group></article>