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<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">Front. Virol.</journal-id>
<journal-title>Frontiers in Virology</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Front. Virol.</abbrev-journal-title>
<issn pub-type="epub">2673-818X</issn>
<publisher>
<publisher-name>Frontiers Media S.A.</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.3389/fviro.2022.822153</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Virology</subject>
<subj-group>
<subject>Original Research</subject>
</subj-group>
</subj-group>
</article-categories>
<title-group>
<article-title>CD4+ T lymphocyte recovery in the modern antiretroviral therapy era: Toward a new threshold for defining immunological non-responders</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author" corresp="yes">
<name>
<surname>Taramasso</surname>
<given-names>Lucia</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="author-notes" rid="fn001">
<sup>*</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/568637"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Labate</surname>
<given-names>Laura</given-names>
</name>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Briano</surname>
<given-names>Federica</given-names>
</name>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Brucci</surname>
<given-names>Giorgia</given-names>
</name>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1729531"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Mora</surname>
<given-names>Sara</given-names>
</name>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Blanchi</surname>
<given-names>Sabrina</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Giacomini</surname>
<given-names>Mauro</given-names>
</name>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
<xref ref-type="aff" rid="aff4">
<sup>4</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1203034"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Bassetti</surname>
<given-names>Matteo</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Di Biagio</surname>
<given-names>Antonio</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
</contrib>
</contrib-group>
<aff id="aff1">
<sup>1</sup>
<institution>Infectious Disease Clinic, IRCCS Policlinico San Martino Hospital</institution>, <addr-line>Genoa</addr-line>, <country>Italy</country>
</aff>
<aff id="aff2">
<sup>2</sup>
<institution>Infectious Diseases Clinic, Department of Health Sciences, University of Genoa, San Martino Hospital-IRCCS</institution>, <addr-line>Genoa</addr-line>, <country>Italy</country>
</aff>
<aff id="aff3">
<sup>3</sup>
<institution>Department of Informatics, Bioengineering, Robotics and System Engineering (DIBRIS), University of Genoa</institution>, <addr-line>Genoa</addr-line>, <country>Italy</country>
</aff>
<aff id="aff4">
<sup>4</sup>
<institution>Centre of Excellence for Biomedical Research (CEBR), University of Genoa</institution>, <addr-line>Genoa</addr-line>, <country>Italy</country>
</aff>
<author-notes>
<fn fn-type="edited-by">
<p>Edited by: Lara Manganaro, National Institute of Molecular Genetics (INGM), Italy</p>
</fn>
<fn fn-type="edited-by">
<p>Reviewed by: Maura Statzu, Emory University, United States; Yoshinori Fukazawa, Cytek Biosciences, United States</p>
</fn>
<fn fn-type="corresp" id="fn001">
<p>*Correspondence: Lucia Taramasso, <email xlink:href="mailto:taramasso.lucia@gmail.com">taramasso.lucia@gmail.com</email>
</p>
</fn>
<fn fn-type="other" id="fn002">
<p>This article was submitted to Virus and Host Immunity, a section of the journal Frontiers in Virology</p>
</fn>
</author-notes>
<pub-date pub-type="epub">
<day>10</day>
<month>01</month>
<year>2023</year>
</pub-date>
<pub-date pub-type="collection">
<year>2022</year>
</pub-date>
<volume>2</volume>
<elocation-id>822153</elocation-id>
<history>
<date date-type="received">
<day>25</day>
<month>11</month>
<year>2021</year>
</date>
<date date-type="accepted">
<day>12</day>
<month>12</month>
<year>2022</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#xa9; 2023 Taramasso, Labate, Briano, Brucci, Mora, Blanchi, Giacomini, Bassetti and Di Biagio</copyright-statement>
<copyright-year>2023</copyright-year>
<copyright-holder>Taramasso, Labate, Briano, Brucci, Mora, Blanchi, Giacomini, Bassetti and Di Biagio</copyright-holder>
<license xlink:href="http://creativecommons.org/licenses/by/4.0/">
<p>This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.</p>
</license>
</permissions>
<abstract>
<sec>
<title>Introduction</title>
<p>Despite the high level of efficacy of modern antiretroviral therapy (ART) in reducing HIV viremia and the control of viral replication, some people living with HIV (PLWH) do not recover their CD4+ T cell count.</p>
</sec>
<sec>
<title>Methods</title>
<p>To evaluate the frequency and predictive factors of discordant immune responses, we performed a retrospective cohort study of 324 antiretroviral-na<bold>&#xef;</bold>ve PLWH who initiated first-line ART between 2008 and 2018 and maintained HIV RNA &lt;&#xa0;50 copies/ml during 36 months of follow-up. PLWH were defined as immunological non-responders (INRs) when CD4+ T cell count was &lt;&#xa0;20% compared with baseline (INR<sub>20%</sub>), or &lt;&#xa0;500&#xa0;cells/mm<sup>3</sup> (INR<sub>500</sub>) or &lt;&#xa0;200&#xa0;cells/mm<sup>3</sup> (INR<sub>200</sub>) at 36 months.</p>
</sec>
<sec>
<title>Results</title>
<p>The prevalence of INR<sub>20%</sub>, INR<sub>500</sub>, and INR<sub>200</sub> was 12.5%, 34.6%, and 1.5%, respectively. After adjustment for possible confounders, CD4 nadir showed a significant association with all INR definitions, with lower values predicting INR<sub>500</sub> (aOR 0.98, 95% CI 0.98&#x2013;0.99, <italic>p</italic>&#xa0;&lt;&#xa0;0.001) and INR<sub>200</sub> (aOR 0.98, 95% CI 0.95&#x2013;1.01, <italic>p</italic>&#xa0;=&#xa0;0.096). Moreover, a higher baseline CD4/CD8 ratio was inversely related to the probability of being INR<sub>500</sub> (OR 0.03, 95% CI 0.01&#x2013;0.12, <italic>p</italic>&#xa0;&lt;&#xa0;0.001) and INR<sub>200</sub> (OR 0.002, 95% CI 18<sup>&#x2013;7</sup>&#x2013;67.72, <italic>p</italic>&#xa0;=&#xa0;0.255). By contrast, INR<sub>20%</sub> had a higher CD4 nadir and CD4/CD8 ratio than other INRs, suggesting the identification of an heterogenous population with such definition.</p>
</sec>
<sec>
<title>Discussion</title>
<p>The present study highlights how INR<sub>200</sub> has become rare in the contemporary ART era, and about one-third of PLWH meet the criteria for INR<sub>500</sub>. Overcoming the threshold of 500 CD4/mm<sup>3</sup> could be an appropriate definition of immune response, in contrast with the older definitions of INR<sub>200</sub> and INR<sub>20%</sub>. Early diagnosis and rapid treatment initiation, before CD4 counts and the CD4/CD8 ratio begin to decline, are critical for achieving an optimal immune response.</p>
</sec>
</abstract>
<kwd-group>
<kwd>immunological non responders</kwd>
<kwd>HIV</kwd>
<kwd>immune recovery</kwd>
<kwd>discordant immune response</kwd>
<kwd>antiretrovirals</kwd>
<kwd>CD4+T-cell count</kwd>
</kwd-group>
<counts>
<fig-count count="0"/>
<table-count count="7"/>
<equation-count count="0"/>
<ref-count count="54"/>
<page-count count="13"/>
<word-count count="6282"/>
</counts>
</article-meta>
</front>
<body>
<sec id="s1" sec-type="intro">
<label>1</label>
<title>Introduction</title>
<p>Because of the availability of modern combined antiretroviral therapy (ART), people living with HIV (PLWH) have experienced a reduction in overall mortality and incidence of AIDS-defining conditions, improving survival and quality of life (<xref ref-type="bibr" rid="B1">1</xref>&#x2013;<xref ref-type="bibr" rid="B3">3</xref>). The efficacy of ART is traditionally evaluated using two parameters: immunological recovery, namely the increase in CD4+ T-cell count (CD4), and the viral suppression, defined as an HIV RNA load of &lt;&#xa0;50 copies/ml in plasma. The extent of a CD4 increase, however, might have interpatient variations depending on age, ethnicity, test imprecision, intercurrent infection, and relative leukocyte count (<xref ref-type="bibr" rid="B4">4</xref>, <xref ref-type="bibr" rid="B5">5</xref>), and the immunological response in the course of ART can be heterogeneous, based on individual, clinical, and genetic factors (<xref ref-type="bibr" rid="B6">6</xref>&#x2013;<xref ref-type="bibr" rid="B8">8</xref>). Despite this variability, there is general agreement that CD4 count is the main marker of immunological staging (<xref ref-type="bibr" rid="B9">9</xref>). However, some PLWH fail to reconstitute CD4 count, even in the course of successful ART. These people are referred to as immunological non-responders (INRs). A consensus on the definition of INR has not been reached yet, owing to consistent interpatient variability of different factors, including age, HIV RNA load and CD4 count before starting ART, coinfections with HCV, HBV, and CMV, bone marrow and thymic dysfunction, genetic factors, and immune activation (<xref ref-type="bibr" rid="B10">10</xref>&#x2013;<xref ref-type="bibr" rid="B12">12</xref>). INRs have been defined in the past based on CD4 count relative or absolute recovery. In studies that use relative CD4 count recovery from baseline, thresholds varied from less than 20% to 25% or 30% (<xref ref-type="bibr" rid="B13">13</xref>&#x2013;<xref ref-type="bibr" rid="B15">15</xref>). Other studies consider the achievement of a predefined CD4 value, with thresholds that range from 200 to 500&#xa0;cells/mm<sup>3</sup> (<xref ref-type="bibr" rid="B16">16</xref>&#x2013;<xref ref-type="bibr" rid="B18">18</xref>).</p>
<p>Each classification has pros and cons because of variable sensitivity and specificity. The choice of &gt;&#xa0;500 CD4+ T cells/mm<sup>3</sup> to define full immune recovery could be justified in comparison to the general population, as it is the approximately the minimum expected CD4 count in a healthy, HIV-uninfected person. In addition, when counts are &gt;&#xa0;500 CD4+ T cells/mm<sup>3</sup> in PLWH, their mortality rates become similar to those of the general population (<xref ref-type="bibr" rid="B19">19</xref>) and both mortality from AIDS- and non-AIDS-defining causes decreases as CD4 counts increase (<xref ref-type="bibr" rid="B20">20</xref>). On the other hand, the threshold of &gt;&#xa0;200 CD4+ T cells/mm<sup>3</sup> might better represent the turning point between high and low risk of opportunistic diseases and AIDS-defining conditions (<xref ref-type="bibr" rid="B21">21</xref>). However, despite different definitions, most studies agree that INRs are at higher risk of disease progression toward AIDS-defining conditions, non-AIDS-defining conditions, and death (<xref ref-type="bibr" rid="B11">11</xref>, <xref ref-type="bibr" rid="B14">14</xref>, <xref ref-type="bibr" rid="B22">22</xref>). Because of the heterogenicity of definitions, the prevalence of INRs varies from 10% to 40% in different studies (<xref ref-type="bibr" rid="B13">13</xref>, <xref ref-type="bibr" rid="B23">23</xref>); in the modern ART era INRs are expected to become rarer thanks to early diagnosis and immediate initiation of ART (<xref ref-type="bibr" rid="B24">24</xref>), and new antiretroviral agents characterized by high levels of efficacy and tolerability (<xref ref-type="bibr" rid="B25">25</xref>, <xref ref-type="bibr" rid="B26">26</xref>).</p>
<p>In Italy, as well as in many other countries in the world, after 2008 new antiretroviral agents were introduced in clinical practice that completed the therapeutic armamentarium, and integrase strand transfer inhibitors (INSTIs) have begun to enter first-line therapy in PLWH (<xref ref-type="bibr" rid="B27">27</xref>, <xref ref-type="bibr" rid="B28">28</xref>). With the aim of assessing the phenomenon of INR in an era of modern ART, we used three different definitions of immunological reconstitution, i.e., a CD4 level increase of &gt;&#xa0;20% from baseline, a CD4 level of &gt;&#xa0;200 cells/mm<sup>3</sup> or a CD4 level of &gt;&#xa0;500 cells/mm<sup>3</sup>, and we evaluated the prevalence of INR according to these definitions in recent years in our single-center experience.</p>
</sec>
<sec id="s2" sec-type="materials|methods">
<label>2</label>
<title>Material and methods</title>
<sec id="s2_1">
<label>2.1</label>
<title>Study design, subject, and inclusion criteria</title>
<p>We conducted a retrospective observational study in a cohort of people diagnosed with HIV from 2008 to 2018 in our center (Policlinico IRCCS San Martino University Hospital).</p>
<p>The inclusion criteria were a confirmed HIV infection, being ART-na&#xef;ve at the beginning of the study, being aged &#x2265;18 years, and achieving and maintaining viral suppression (i.e., HIV RNA &lt;&#xa0;50 copies/ml) throughout the follow-up period of 36 months after ART initiation.</p>
<p>Exclusion criteria were at least one HIV RNA  of &gt;&#xa0;50 copies/ml fter achieving viral suppression, being aged &#x2265;&#xa0;18 years, a lack of virological and immunological data during 36 months after the study baseline, and death before 36 months from the study initiation.</p>
</sec>
<sec id="s2_2">
<label>2.2</label>
<title>Data collection and study definitions</title>
<p>Data for all PLWH included in the study were extracted from the Liguria HIV Network Database (RLH-DB). The Liguria HIV Network is a locally developed online platform with a direct connection between medical and laboratory records of PLWH through the automatic and prospective transfer of anonymous data (<xref ref-type="bibr" rid="B29">29</xref>, <xref ref-type="bibr" rid="B30">30</xref>). Each person has an identification code, which is registered in the RLH-DB at initial engagement (i.e., at the first ambulatory visit for outpatients or first day of hospitalization for inpatients). Safety and precision are granted by the approved use of hospital anonymized codes. The use of the RLH-DB was approved by the Ligurian Ethics Committee. All people registered in the RHL-DB signed informed consent forms to be included in the study. The study has been performed in accordance with the ethics standards of the Declaration of Helsinki and with Italian national laws.</p>
<p>For the classification of the INR we used the following definitions: (a) ART-treated PLWH who failed to demonstrate a 20% recovery in their CD4 levels, compared with their baseline CD4 count, at 36 months after their first HIV RNA of &lt;&#xa0;50 copies/ml (who were defined as INR<sub>20%</sub>) (<xref ref-type="bibr" rid="B31">31</xref>&#x2013;<xref ref-type="bibr" rid="B33">33</xref>); (b) ART-treated PLWH with a total CD4 count of &lt;&#xa0;500 cells/mm<sup>3</sup> at 36 months after their first HIV RNA of &lt;&#xa0;50 copies/ml (who were defined as INR<sub>500</sub>) (<xref ref-type="bibr" rid="B34">34</xref>&#x2013;<xref ref-type="bibr" rid="B38">38</xref>); and (c) ART-treated PLWH with a total CD4 count of &lt;&#xa0;200 cells/mm<sup>3</sup> at 36 months after their first HIV RNA of &lt;&#xa0;50 copies/ml (who were defined as INR<sub>200</sub>) (<xref ref-type="bibr" rid="B11">11</xref>, <xref ref-type="bibr" rid="B15">15</xref>, <xref ref-type="bibr" rid="B17">17</xref>, <xref ref-type="bibr" rid="B33">33</xref>, <xref ref-type="bibr" rid="B39">39</xref>&#x2013;<xref ref-type="bibr" rid="B42">42</xref>).</p>
<p>Plasma viral load, measured as HIV RNA copies/ml, was quantified by using the K-PCR-HIV1 (Siemens Health Care, Erlangen, Germany) kit for samples collected between 2008 and 2010; by the Nucleosens HIV (bioMerieux, Marcy-l&#x2019;Etoile, France) kit between 2011 and 2018; and by Aptima HIV-1 Quant Dx Assay from 2019 onward.</p>
<p>CD4+ T cell counts were assessed in EDTA blood samples, which were analyzed using a BD FACSCanto flow cytometer (BD Biosciences). The following monoclonal antibodies (MABs) were used to analyze T-cell subsets: CD3FITC/CD8 PE/CD45 PercCP-Cy5.5/CD4 APC (BD Multitest).</p>
<p>HCV co-infection was defined as positive anti-HCV antibody test and detectable HCV RNA. HBV co-infection was defined as positive hepatitis B surface antigen (HBsAg) test. The time of HIV RNA viral decay was calculated as the difference in days between ART initiation and achievement of first HIV RNA load of &lt;&#xa0;50 copies/ml.</p>
<p>Clinical events were classified as AIDS defining based on CDC&#x2019;s classification (<xref ref-type="bibr" rid="B43">43</xref>).</p>
</sec>
<sec id="s2_3">
<label>2.3</label>
<title>Study objective</title>
<p>The primary objective of the study was to evaluate the frequency of INR<sub>20%</sub>, INR<sub>500</sub>, and INR<sub>200</sub> at 36 months after starting ART in the period 2008&#x2013;2018.</p>
<p>The secondary objective of the study was to evaluate the factors associated with a poor immune response in INR<sub>20%</sub>, INR<sub>500</sub>, and INR<sub>200</sub>.</p>
</sec>
<sec id="s2_4">
<label>2.4</label>
<title>Statistical analysis</title>
<p>Data were described using mean and standard deviation (SD) for normally distributed continuous variables, median and interquartile range (IQR) for not normally distributed continuous variables, and frequency (%) for categorical and ordinal variables. Continuous variables were compared by using the <italic>t</italic>-test or Mann&#x2013;Whitney <italic>U</italic>-test, and categorical variables were compared using chi-squared or Fisher&#x2019;s exact test, as appropriate. Factors associated with INR were evaluated using a binomial logistic regression model with the INR as the dependent variable; factors with a <italic>p</italic>-value &#x2264;&#xa0;0.1 at univariate analysis were included in the multivariable model. For INR<sub>500</sub> and INR<sub>200</sub> analysis, only PLWH with a CD4 nadir of &lt;&#xa0;500 and &lt;200 cells/mm<sup>3</sup>, respectively, were included in the logistic model. Since both CD4 and CD8 absolute numbers and the CD4/CD8 ratio reached significance in univariate analyses of different INR groups, a sensitivity analysis was performed to investigate the relationship between CD4/CD8 ratio, instead of absolute lymphocyte numbers, and INR. CD4 nadir was dichotomized according to the best threshold obtained from the receiver operating characteristic (ROC) curve analysis to identify the cut-off value predictive of becoming INR<sub>500</sub> or INR<sub>200</sub> in the study cohort. The significance level was defined as a <italic>p</italic>-value &lt;&#xa0;0.05.</p>
</sec>
</sec>
<sec id="s3" sec-type="results">
<label>3</label>
<title>Results</title>
<p>During the study period, 452 PLWH were newly diagnosed in our center. Among them, 128 were excluded from the study because they were lost to follow-up (N&#xa0;=&#xa0;98), died (N&#xa0;=&#xa0;20), or did not meet virological criteria for study inclusion (N&#xa0;=&#xa0;10) within 36 months of starting ART.</p>
<p>The remaining 324 PLWH were included in the study. Among them, 91 out of 324 (28%) were female and 240 out of 324 (74%) were Italian. The median age of study participants was 41 years (IQR 18&#x2013;80 years). The risk factors for HIV acquisition were as follows: unprotected intercourse, 278 PLWH (heterosexual, 183 [56%]; men who had sex with men [MSM], 95 [29%]); intravenous drug use (IVDU), 29 (9%) PLWH; and other/unknown, 17 (5%) PLWH.</p>
<p>The mean CD4 nadir of study participants before they received ART was 276 (&#xb1;&#xa0;222) cells/mm<sup>3</sup>, and the mean CD4 count after 36 months of ART was 664 (&#xb1;&#xa0;326) cells/mm<sup>3</sup>.</p>
<p>According to the CDC classification, 121 (37%), 131 (40%), and 71 (22%) PLWH were on stage A, B, and C, respectively, at time of diagnosis (<xref ref-type="table" rid="T1">
<bold>Table&#xa0;1</bold>
</xref>).</p>
<table-wrap id="T1" position="float">
<label>Table&#xa0;1</label>
<caption>
<p>Clinical and demographic characteristics of the study population.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="top" align="left">Demographic variables</th>
<th valign="top" align="center"/>
<th valign="top" align="center"/>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="left">Age in years, mean (SD)</td>
<td valign="top" align="center">42 (&#xb1;12)</td>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="left">Male gender, N (%)</td>
<td valign="top" align="center">233/324</td>
<td valign="top" align="center">(72)</td>
</tr>
<tr>
<td valign="top" align="left">Italian, N (%)*</td>
<td valign="top" align="center">240/324</td>
<td valign="top" align="center">(74)</td>
</tr>
<tr>
<th valign="top" colspan="3" align="left">Risk factor for HIV infection, N (%)</th>
</tr>
<tr>
<td valign="top" align="left">Heterosexual</td>
<td valign="top" align="center">183/324</td>
<td valign="top" align="center">(56)</td>
</tr>
<tr>
<td valign="top" align="left">MSM</td>
<td valign="top" align="center">95/324</td>
<td valign="top" align="center">(29)</td>
</tr>
<tr>
<td valign="top" align="left">IVDU</td>
<td valign="top" align="center">29/324</td>
<td valign="top" align="center">(9)</td>
</tr>
<tr>
<td valign="top" align="left">Unknown</td>
<td valign="top" align="center">17/324</td>
<td valign="top" align="center">(5)</td>
</tr>
<tr>
<th valign="top" colspan="3" align="left">CDC classification at time of diagnosis, N (%)</th>
</tr>
<tr>
<td valign="top" align="left">Stage A</td>
<td valign="top" align="center">121/324</td>
<td valign="top" align="center">(37)</td>
</tr>
<tr>
<td valign="top" align="left">Stage B</td>
<td valign="top" align="center">131/324</td>
<td valign="top" align="center">(40)</td>
</tr>
<tr>
<td valign="top" align="left">Stage C</td>
<td valign="top" align="center">71/324</td>
<td valign="top" align="center">(22)</td>
</tr>
<tr>
<td valign="top" align="left">Unknown</td>
<td valign="top" align="center">1/324</td>
<td valign="top" align="center">(0)</td>
</tr>
<tr>
<th valign="top" colspan="3" align="left">Co-infections, N (%)</th>
</tr>
<tr>
<td valign="top" align="left">HCV Ab positivity</td>
<td valign="top" align="center">33/324</td>
<td valign="top" align="center">(10)</td>
</tr>
<tr>
<td valign="top" align="left">HBsAg positivity</td>
<td valign="top" align="center">15/324</td>
<td valign="top" align="center">(5)</td>
</tr>
<tr>
<td valign="top" align="left">CMV IgG positivity</td>
<td valign="top" align="center">272/324</td>
<td valign="top" align="center">(84)</td>
</tr>
<tr>
<th valign="top" colspan="3" align="left">Other, N (%)</th>
</tr>
<tr>
<td valign="top" align="left">Chemotherapy</td>
<td valign="top" align="center">8/324</td>
<td valign="top" align="center">(2)</td>
</tr>
<tr>
<th valign="top" colspan="3" align="left">Immunovirological data</th>
</tr>
<tr>
<td valign="top" align="left">CD4 nadir (n/mmc)</td>
<td valign="top" align="center">276</td>
<td valign="top" align="center">(222)</td>
</tr>
<tr>
<td valign="top" align="left">HIV RNA zenith, log<sub>10</sub> (copies/ml)</td>
<td valign="top" align="center">5.6</td>
<td valign="top" align="center">(6.2)</td>
</tr>
<tr>
<td valign="top" align="left">Time to HIV RNA &#x2264; 50 copies/ml (months)</td>
<td valign="top" align="center">4</td>
<td valign="top" align="center">(3)</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>*Overall, 259 out of 324 (80%) study participants were from Europe, 39 out of 324 (12%) were from South America, 18 out of 324 (6%) were from Africa, 4 out of 324 (1.2%) were from Asia, and 1 out 324 (0.3%) was from North America.</p>
</fn>
<fn>
<p>HBsAg, hepatitis B surface antigen; IQR, interquartile range; IVDU intravenous drug users; MSM, men who have sex with men; SD, standard deviation.</p>
</fn>
</table-wrap-foot>
</table-wrap>
<sec id="s3_1">
<label>3.1</label>
<title>Prevalence of suboptimal CD4+ T-cell recovery and factors associated with INR</title>
<sec id="s3_1_1">
<label>3.1.1</label>
<title>INR<sub>20%</sub>
</title>
<p>Overall, 41 out of 324 (12.6%) study participants met the criteria for INR<sub>20%</sub>; 32 were male (78%) and the mean age was 42 years (&#xb1;14.08 years). INR<sub>20%</sub> were less frequently in CDC stage C (7.3% vs. 24%, <italic>p</italic>&#xa0;=&#xa0;0.02), had a lower CD4 nadir (254 cells/mm<sup>3</sup> in INR<sub>20%</sub> vs. 420 cells/mm<sup>3</sup> in full responders, <italic>p</italic>&#xa0;&lt;&#xa0;0.001), and a lower HIV RNA zenith (4.44 log<sub>10</sub> in INR<sub>20%</sub> vs. 4.96 log<sub>10</sub> in full responders, <italic>p</italic>&#xa0;=&#xa0;0.01). The mean CD8+T cell counts were similar in INR<sub>20%</sub> and full responders at baseline (<italic>p</italic>&#xa0;=&#xa0;0.41), but were lower in INR<sub>20%</sub> at 36 months (731 vs. 916 cells/mm<sup>3</sup>, <italic>p</italic>&#xa0;=&#xa0;0.006).</p>
<p>Age (<italic>p</italic>&#xa0;=&#xa0;0.07), sex (<italic>p</italic>&#xa0;=&#xa0;0.35), risk factor for HIV infection (<italic>p</italic>&#xa0;=&#xa0;0.23), country of origin (<italic>p</italic>&#xa0;=&#xa0;0.31), and prevalence of HCV RNA, HBsAg, and CMV-IgG positivity were similar between INR<sub>20%</sub> and full responders (<italic>p</italic>&#xa0;=0.91, <italic>p</italic>&#xa0;=&#xa0;0.38, and <italic>p</italic>&#xa0;=&#xa0;0.50, respectively). In addition, the dynamics of HIV RNA decay during follow-up was similar in the two groups (<italic>p</italic>&#xa0;=&#xa0;0.38), and no difference was found in time of exposure to different ART regimens in INR<sub>20%</sub> and full responders. The mortality rate was similar in the two groups (<italic>p</italic>&#xa0;=&#xa0;0.39; <xref ref-type="table" rid="T2">
<bold>Table&#xa0;2</bold>
</xref>).</p>
<table-wrap id="T2" position="float">
<label>Table&#xa0;2</label>
<caption>
<p>Comparison of clinical and demographic characteristics of INR<sub>20%</sub> and full responders (FR).</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="top" align="left">Variable</th>
<th valign="top" align="center">FR<sub>20%</sub>
</th>
<th valign="top" align="center">INR<sub>20%</sub>
</th>
<th valign="top" align="center">
<italic>p</italic>-value</th>
</tr>
</thead>
<tbody>
<tr>
<th valign="top" colspan="4" align="left">Demographic variables</th>
</tr>
<tr>
<td valign="top" align="left">Age in years, mean (SD)</td>
<td valign="top" align="center">41 (&#xb1;12.07)</td>
<td valign="top" align="center">42 (&#xb1;14.08)</td>
<td valign="top" align="center">0.073</td>
</tr>
<tr>
<td valign="top" align="left">Male (%)</td>
<td valign="top" align="center">201/283 (71%)</td>
<td valign="top" align="center">32/41 (78%)</td>
<td valign="top" align="center">0.350</td>
</tr>
<tr>
<th valign="top" colspan="4" align="left">Risk factor for HIV</th>
</tr>
<tr>
<td valign="top" align="left">Heterosexuals (%)</td>
<td valign="top" align="center">162/283 (57%)</td>
<td valign="top" align="center">21/41 (51.3%)</td>
<td valign="middle" rowspan="4" align="center">0.236</td>
</tr>
<tr>
<td valign="top" align="left">MSM (%)</td>
<td valign="top" align="center">79/283 (28%)</td>
<td valign="top" align="center">16/41 (39%)</td>
</tr>
<tr>
<td valign="top" align="left">IVDU (%)</td>
<td valign="top" align="center">26/283 (9%)</td>
<td valign="top" align="center">3/41 (7,3%)</td>
</tr>
<tr>
<td valign="top" align="left">Unknown (%)</td>
<td valign="top" align="center">16/283 (6%)</td>
<td valign="top" align="center">1/41 (2,4%)</td>
</tr>
<tr>
<th valign="top" colspan="4" align="left">Nationality</th>
</tr>
<tr>
<td valign="top" align="left">Italian (%)</td>
<td valign="top" align="center">207/283 (73%)</td>
<td valign="top" align="center">33/41 (80.5%)</td>
<td valign="top" align="center">0.316</td>
</tr>
<tr>
<th valign="top" colspan="4" align="left">CDC stage at HIV diagnosis</th>
</tr>
<tr>
<td valign="top" align="left">A (%)</td>
<td valign="top" align="center">100/283 (35%)</td>
<td valign="top" align="center">21/41 (51.3%)</td>
<td valign="middle" rowspan="4" align="center">0.029</td>
</tr>
<tr>
<td valign="top" align="left">B (%)</td>
<td valign="top" align="center">115/283 (41%)</td>
<td valign="top" align="center">16/41 (39%)</td>
</tr>
<tr>
<td valign="top" align="left">C (%)</td>
<td valign="top" align="center">68/283 (24%)</td>
<td valign="top" align="center">3/41 (7.3%)</td>
</tr>
<tr>
<td valign="top" align="left">Unknown (%)</td>
<td valign="top" align="center">0 (0%)</td>
<td valign="top" align="center">1/41 (2.4%)</td>
</tr>
<tr>
<th valign="top" colspan="4" align="left">Co-infections</th>
</tr>
<tr>
<td valign="top" align="left">Ab anti-HCV positivity at baseline</td>
<td valign="top" align="center">29/280 (10.4%)</td>
<td valign="top" align="center">4/41 (9.8%)</td>
<td valign="top" align="center">0.906</td>
</tr>
<tr>
<td valign="top" align="left">HBsAg positivity at baseline</td>
<td valign="top" align="center">12/283 (4%)</td>
<td valign="top" align="center">3/41 (7%)</td>
<td valign="top" align="center">0.381</td>
</tr>
<tr>
<td valign="top" align="left">CMV IgG positivity at baseline</td>
<td valign="top" align="center">235/283 (83%)</td>
<td valign="top" align="center">37/41 (90.2%)</td>
<td valign="top" align="center">0.502</td>
</tr>
<tr>
<th valign="top" colspan="4" align="left">Other</th>
</tr>
<tr>
<td valign="top" align="left">Chemotherapy</td>
<td valign="top" align="center">8/283 (3%)</td>
<td valign="top" align="center">0 (0%)</td>
<td valign="top" align="center">0.276</td>
</tr>
<tr>
<td valign="bottom" align="left">Deaths</td>
<td valign="top" align="center">5/283 (2%)</td>
<td valign="top" align="center">0 (0%)</td>
<td valign="top" align="center">0.391</td>
</tr>
<tr>
<th valign="top" colspan="4" align="left">Immunovirological data</th>
</tr>
<tr>
<td valign="top" align="left">CD4 nadir (n/mmc) mean (SD)</td>
<td valign="top" align="center">420 (&#xb1;235)</td>
<td valign="top" align="center">254 (&#xb1;212)</td>
<td valign="top" align="center">&lt; 0.001</td>
</tr>
<tr>
<td valign="top" align="left">CD8+ at baseline, mean (SD)</td>
<td valign="top" align="center">918 (&#xb1;592)</td>
<td valign="top" align="center">1067 (&#xb1;491)</td>
<td valign="top" align="center">0.419</td>
</tr>
<tr>
<td valign="top" align="left">CD8+ at 36 months, mean (SD)</td>
<td valign="top" align="center">916 (&#xb1;391)</td>
<td valign="top" align="center">731 (&#xb1;450)</td>
<td valign="top" align="center">0.006</td>
</tr>
<tr>
<td valign="top" align="left">CD4/CD8 ratio at baseline, median (IQR)</td>
<td valign="top" align="center">0.28 (0.14&#x2013;0.52)</td>
<td valign="top" align="center">0.63 (0.41&#x2013;0.86)</td>
<td valign="top" align="center">&lt;0.001</td>
</tr>
<tr>
<td valign="top" align="left">CD4/CD8 ratio at 36 months median (IQR)</td>
<td valign="top" align="center">0.76 (0.47&#x2013;1.06)</td>
<td valign="top" align="center">0.92 (0.62&#x2013;1.28)</td>
<td valign="top" align="center">0.022</td>
</tr>
<tr>
<td valign="top" align="left">HIV-RNA zenith, log<sub>10</sub> (copies/ml), mean (SD)</td>
<td valign="top" align="center">4.82 (&#xb1;1.02)</td>
<td valign="top" align="center">4.46 (&#xb1;1.04)</td>
<td valign="top" align="center">0.036</td>
</tr>
<tr>
<td valign="bottom" align="left">Time to HIV-RNA &#x2264; 50 copies/ml (months), mean (SD)</td>
<td valign="top" align="center">4.4 (&#xb1;0.21)</td>
<td valign="top" align="center">3.8 (&#xb1;0.43)</td>
<td valign="top" align="center">0.389</td>
</tr>
<tr>
<th valign="bottom" colspan="4" align="left">Therapy</th>
</tr>
<tr>
<td valign="bottom" align="left">Months of INI exposure, mean (SD)</td>
<td valign="top" align="center">13 (&#xb1;0.97)</td>
<td valign="top" align="center">14 (&#xb1;2.73)</td>
<td valign="top" align="center">0.788</td>
</tr>
<tr>
<td valign="bottom" align="left">Months of PI exposure, mean (SD)</td>
<td valign="top" align="center">10 (&#xb1;0.91)</td>
<td valign="top" align="center">8 (&#xb1;2.24)</td>
<td valign="top" align="center">0.161</td>
</tr>
<tr>
<td valign="bottom" align="left">Months of NNRTI exposure, mean (SD)</td>
<td valign="top" align="center">12.7 (&#xb1;0.96)</td>
<td valign="top" align="center">16.7 (&#xb1;2.73)</td>
<td valign="top" align="center">0.319</td>
</tr>
<tr>
<td valign="bottom" align="left">Months of ABC/3TC exposure, mean (SD)</td>
<td valign="top" align="center">4 (&#xb1;0.6)</td>
<td valign="top" align="center">2 (&#xb1;1.33)</td>
<td valign="top" align="center">0.117</td>
</tr>
<tr>
<td valign="bottom" align="left">Months of TDF/FTC exposure, mean (SD)</td>
<td valign="top" align="center">28 (&#xb1;0.78)</td>
<td valign="top" align="center">26 (&#xb1;2.19)</td>
<td valign="top" align="center">0.287</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>ABC/3TC, abacavir+ lamivudine; FR<sub>20%</sub>: full responders, defined as people who recovered at least 20%CD4+T cell after 36 months of virological suppression (HIV RNA &lt;50 copies/ml) on antiretroviral therapy; HBsAg hepatitis B surface antigen; INR<sub>20%</sub> people who did not recover at least 20%CD4+T cells after 36 months of virological suppression (HIV RNA &lt;50 copies/ml) on antiretroviral therapy; IQR, interquartile range; INI, integrase inhibitors; IVDU intravenous drug users; MSM, men who have sex with men; NNRTI, nonnucleoside reverse transcriptase inhibitors; NRTI, nucleoside or nucleotide reverse transcriptase inhibitors; PI, protease inhibitors; SD, standard deviation; TDF/FTC tenofovir disoproxil fumarate/emtricitabine.</p>
</fn>
</table-wrap-foot>
</table-wrap>
</sec>
<sec id="s3_1_2">
<label>3.1.2</label>
<title>INR<sub>500</sub>
</title>
<p>A total of 112 out 324 (34.6%) PLWH met the criteria for INR<sub>500</sub> at 36 months; 86 were male (77%) and the median age was 42 years (&#xb1;12.06 years). INR<sub>500</sub> were more often non-Italian (40% vs. 22%, <italic>p</italic>&#xa0;=&#xa0;0.01) and in CDC stage C at the time of HIV diagnosis (37% vs.14%, <italic>p</italic>&#xa0;&lt;&#xa0;0.001) compared with full responders. CD4 nadir (109 vs. 364 cells/mm<sup>3</sup>, <italic>p&#xa0;</italic>&lt;&#xa0;0.001) and 36-month CD8+ T cell counts (780 vs. 949 cells/mm<sup>3</sup>, <italic>p</italic>&#xa0;&lt;0.001) were lower in INR<sub>500</sub>, and, at baseline, CD8+ T cell counts were higher in INR<sub>500</sub> (1030 vs.768 cells/mm<sup>3</sup>, <italic>p</italic>&#xa0;=&#xa0;0.038). According to the ROC curve, a CD4 nadir &#x2264;&#xa0;200 cells/mm<sup>3</sup> showed 83.93% specificity and 71.43% sensitivity in predicting becoming INR<sub>500</sub> [area under the curve (AUC) 0.839;143 people had CD4 nadir &#x2264;&#xa0;200 cells/mm<sup>3</sup> in the study cohort] in this cohort. The CD4/CD8 ratio was lower in INR<sub>500</sub> at both baseline and 36 months&#x2019; evaluation (0.14 vs.0.43, <italic>p</italic>&#xa0;&lt;&#xa0;0.001 and 0.48 vs. 0.92, <italic>p</italic>&#xa0;&lt;&#xa0;0.001, respectively).</p>
<p>No difference was found in time to achievement of HIV RNA of &lt;&#xa0;50 copies/ml (<italic>p</italic>&#xa0;=&#xa0;0.71) or in the zenith of HIV RNA (<italic>p</italic>&#xa0;=&#xa0;0.31). No differences were found in time of exposure to different ART classes or in the other patient characteristics that were evaluated. The mortality rate was similar in the two groups (<italic>p</italic>&#xa0;=&#xa0;0.22; <xref ref-type="table" rid="T3">
<bold>Table&#xa0;3</bold>
</xref>).</p>
<table-wrap id="T3" position="float">
<label>Table&#xa0;3</label>
<caption>
<p>Comparison of clinical and demographic characteristics of INR<sub>500</sub> and full responders (FR).</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="top" align="left">Variable</th>
<th valign="top" align="center">FR<sub>500</sub>
</th>
<th valign="top" align="center">INR<sub>500</sub>
</th>
<th valign="top" align="center">
<italic>p</italic>-value</th>
</tr>
</thead>
<tbody>
<tr>
<th valign="top" colspan="4" align="left">Demographic variables</th>
</tr>
<tr>
<td valign="top" align="left">Age in years, mean (SD)</td>
<td valign="top" align="center">43 (&#xb1;12.07)</td>
<td valign="top" align="center">41 (&#xb1;12.6)</td>
<td valign="top" align="center">0.347</td>
</tr>
<tr>
<td valign="top" align="left">Male (%)</td>
<td valign="top" align="center">147/212 (70%)</td>
<td valign="top" align="center">86/112 (77%)</td>
<td valign="top" align="center">0.156</td>
</tr>
<tr>
<th valign="top" colspan="4" align="left">Risk factor for HIV</th>
</tr>
<tr>
<td valign="top" align="left">Heterosexuals (%)</td>
<td valign="top" align="center">120/212 (56.6%)</td>
<td valign="top" align="center">63/112 (56.8%)</td>
<td valign="middle" rowspan="4" align="center">0.843</td>
</tr>
<tr>
<td valign="top" align="left">MSM (%)</td>
<td valign="top" align="center">64/212 (30.2%)</td>
<td valign="top" align="center">31/112 (27.9%)</td>
</tr>
<tr>
<td valign="top" align="left">IVDU (%)</td>
<td valign="top" align="center">17/212 (8%)</td>
<td valign="top" align="center">12/112 (10.8%)</td>
</tr>
<tr>
<td valign="top" align="left">Unknown (%)</td>
<td valign="top" align="center">11/212 (5.2%)</td>
<td valign="top" align="center">5/112 (4.5%)</td>
</tr>
<tr>
<th valign="top" colspan="4" align="left">Nationality</th>
</tr>
<tr>
<td valign="top" align="left">Italian (%)</td>
<td valign="top" align="center">166/212 (78.3%)</td>
<td valign="top" align="center">74/112 (66.1%)</td>
<td valign="top" align="center">0.017</td>
</tr>
<tr>
<th valign="top" colspan="4" align="left">CDC stage at HIV diagnosis</th>
</tr>
<tr>
<td valign="top" align="left">A (%)</td>
<td valign="top" align="center">95/212 (44.8%)</td>
<td valign="top" align="center">26/112 (23%)</td>
<td valign="middle" rowspan="4" align="center">&lt;0.001</td>
</tr>
<tr>
<td valign="top" align="left">B (%)</td>
<td valign="top" align="center">87/212 (41%)</td>
<td valign="top" align="center">44/112 (39%)</td>
</tr>
<tr>
<td valign="top" align="left">C (%)</td>
<td valign="top" align="center">30/212 (14.2%)</td>
<td valign="top" align="center">41/112 (37%)</td>
</tr>
<tr>
<td valign="top" align="left">Unknown</td>
<td valign="top" align="center">0 (0%)</td>
<td valign="top" align="center">1/112 (1%)</td>
</tr>
<tr>
<th valign="top" colspan="4" align="left">Co-infections</th>
</tr>
<tr>
<td valign="top" align="left">Ab anti-HCV positivity at baseline</td>
<td valign="top" align="center">18/212 (8.5%)</td>
<td valign="top" align="center">15/112 (14%)</td>
<td valign="top" align="center">0.153</td>
</tr>
<tr>
<td valign="top" align="left">HBsAg positivity at baseline</td>
<td valign="top" align="center">8/212 (3.8%)</td>
<td valign="top" align="center">7/112 (6.3%)</td>
<td valign="top" align="center">0.313</td>
</tr>
<tr>
<td valign="top" align="left">CMV IgG positivity at baseline</td>
<td valign="top" align="center">175/212 (82.5%)</td>
<td valign="top" align="center">97/112 (86.6%)</td>
<td valign="top" align="center">0.221</td>
</tr>
<tr>
<th valign="top" colspan="4" align="left">Other</th>
</tr>
<tr>
<td valign="top" align="left">Chemotherapy</td>
<td valign="top" align="center">3/212 (1.4%)</td>
<td valign="top" align="center">5/112 (4.5%)</td>
<td valign="top" align="center">0.093</td>
</tr>
<tr>
<td valign="top" align="left">Deaths</td>
<td valign="top" align="center">2/212 (1%)</td>
<td valign="top" align="center">3/112 (3%)</td>
<td valign="top" align="center">0.228</td>
</tr>
<tr>
<th valign="top" colspan="4" align="left">Immunovirological data</th>
</tr>
<tr>
<td valign="top" align="left">CD4 nadir (cells/mm<sup>3</sup>), mean (SD)</td>
<td valign="top" align="center">363.6 (&#xb1;220.3)</td>
<td valign="top" align="center">109.5 (&#xb1;94.5)</td>
<td valign="top" align="center">&lt; 0.001</td>
</tr>
<tr>
<td valign="top" align="left">CD8+ at baseline, mean (SD)</td>
<td valign="top" align="center">768 (&#xb1;441)</td>
<td valign="top" align="center">1030 (&#xb1;628)</td>
<td valign="top" align="center">0.038</td>
</tr>
<tr>
<td valign="top" align="left">CD8+ at 36 months, mean (SD)</td>
<td valign="top" align="center">949 (&#xb1;434)</td>
<td valign="top" align="center">780 (&#xb1;309)</td>
<td valign="top" align="center">&lt; 0.001</td>
</tr>
<tr>
<td valign="top" align="left">CD4/CD8 ratio at baseline, median (IQR)</td>
<td valign="top" align="center">0.43 (0.24&#x2013;0.73)</td>
<td valign="top" align="center">0.14 (0.08&#x2013;0.27)</td>
<td valign="top" align="center">&lt; 0.001</td>
</tr>
<tr>
<td valign="top" align="left">CD4/CD8 ratio at 36 months median (IQR)</td>
<td valign="top" align="center">0.92 (0.67&#x2013;1.21)</td>
<td valign="top" align="center">0.48 (0.32&#x2013;0.70)</td>
<td valign="top" align="center">&lt; 0.001</td>
</tr>
<tr>
<td valign="top" align="left">HIV-RNA zenith, log<sub>10</sub> (copies/ml) mean, (SD)</td>
<td valign="top" align="center">4.74 (1.02)</td>
<td valign="top" align="center">4.81 (1.06)</td>
<td valign="top" align="center">0.615</td>
</tr>
<tr>
<td valign="bottom" align="left">Time to HIV-RNA &#x2264; 50 copies/ml (months), mean (SD)</td>
<td valign="top" align="center">4.3 (&#xb1;0.24)</td>
<td valign="top" align="center">4.3 (&#xb1;0.29)</td>
<td valign="top" align="center">0.713</td>
</tr>
<tr>
<th valign="bottom" colspan="4" align="left">Therapy</th>
</tr>
<tr>
<td valign="bottom" align="left">Months of INI exposure, mean (SD)</td>
<td valign="top" align="center">12.8 (&#xb1;1.12)</td>
<td valign="top" align="center">14.3 (&#xb1;1.58)</td>
<td valign="top" align="center">0.567</td>
</tr>
<tr>
<td valign="bottom" align="left">Months of PI exposure, mean (SD)</td>
<td valign="top" align="center">9.8 (&#xb1;1.04)</td>
<td valign="top" align="center">11.4 (&#xb1;1.44)</td>
<td valign="top" align="center">0.123</td>
</tr>
<tr>
<td valign="bottom" align="left">Months of NNRTI exposure, mean (SD)</td>
<td valign="top" align="center">14.6 (&#xb1;1.17)</td>
<td valign="top" align="center">10.7 (&#xb1;1.41)</td>
<td valign="top" align="center">0.103</td>
</tr>
<tr>
<td valign="bottom" align="left">Months of ABC/3TC exposure, mean (SD)</td>
<td valign="top" align="center">4.4(&#xb1;0.73)</td>
<td valign="top" align="center">2.6 (&#xb1;0.76)</td>
<td valign="top" align="center">0.507</td>
</tr>
<tr>
<td valign="bottom" align="left">Months of TDF/FTC exposure, mean (SD)</td>
<td valign="top" align="center">27 (&#xb1;0.95)</td>
<td valign="top" align="center">29 (&#xb1;1.16)</td>
<td valign="top" align="center">0.518</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>ABC/3TC, abacavir+ lamivudine; FR<sub>500</sub>: full responders, defined as people who recovered at least 500 CD4+T cells after 36 months of virological suppression (HIV RNA &lt;50 copies/ml) on antiretroviral therapy; HBsAg hepatitis B surface antigen; INR<sub>500</sub> people who did not recover at least 500 CD4+T cells after 36 months of virological suppression (HIV RNA &lt;50 copies/ml) on antiretroviral therapy; IQR, interquartile range; INI, integrase inhibitors; IVDU intravenous drug users; MSM, men who have sex with men; NNRTI, nonnucleoside reverse transcriptase inhibitors; NRTI, nucleoside or nucleotide reverse transcriptase inhibitors; PI, protease inhibitors; SD, standard deviation; TDF/FTC tenofovir disoproxil fumarate/emtricitabine.</p>
</fn>
</table-wrap-foot>
</table-wrap>
</sec>
<sec id="s3_1_3">
<label>3.1.3</label>
<title>INR<sub>200</sub>
</title>
<p>In the study population, 5 out of 324 (1.5%) PLWH did not recover at least 200 CD4/mm<sup>3</sup> at 36 months after ART initiation and were thus classified as INR<sub>200</sub>. Among them, four were male (80%) and the median age was 51 years (&#xb1;12.06 years). They had a lower CD4 nadir (33 vs. 279 cells/mm<sup>3</sup>, <italic>p</italic>&#xa0;&lt;&#xa0;0.001) and a lower CD4/CD8 ratio at both baseline and 36 months&#x2019; follow-up than full responders (0.14 vs. 0.42, <italic>p</italic>&#xa0;=&#xa0;0.012, and 0.17 vs. 0.78, <italic>p</italic>&#xa0;&lt;&#xa0;0.001, respectively). According to the ROC curve, a CD4 nadir &#x2264;&#xa0;65 cells/mm<sup>3</sup> showed 56.5% specificity and 100% sensitivity in predicting becoming INR<sub>200</sub> (AUC 0.765) in this cohort (65 people had a CD4 nadir &#x2264;&#xa0;65 cells/mm<sup>3</sup> in the study cohort). The CDC stage at diagnosis was not significantly different in INR<sub>200</sub> than in full responders (<italic>p</italic>&#xa0;=&#xa0;0.559). The crude mortality was higher in this group because of one death out of five INR<sub>200</sub> (<xref ref-type="table" rid="T4">
<bold>Table&#xa0;4</bold>
</xref>). No other significant differences were found in the other analyzed characteristics and drug exposure in the study population.</p>
<table-wrap id="T4" position="float">
<label>Table&#xa0;4</label>
<caption>
<p>Comparison of clinical and demographic characteristics of INR<sub>200</sub> and full responders.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="bottom" align="left">Variable</th>
<th valign="bottom" align="center">FR<sub>200</sub>
</th>
<th valign="bottom" align="center">INR<sub>200</sub>
</th>
<th valign="bottom" align="center">
<italic>p</italic>-value</th>
</tr>
</thead>
<tbody>
<tr>
<th valign="bottom" colspan="4" align="left">Demographic variables</th>
</tr>
<tr>
<td valign="bottom" align="left">Age in years, mean (SD)</td>
<td valign="bottom" align="center">41 (&#xb1;12.4)</td>
<td valign="bottom" align="center">51(&#xb1;13.4)</td>
<td valign="bottom" align="center">0.827</td>
</tr>
<tr>
<td valign="bottom" align="left">Male (%)</td>
<td valign="bottom" align="center">229/319 (72%)</td>
<td valign="bottom" align="center">4/5 (80%)</td>
<td valign="bottom" align="center">0.568</td>
</tr>
<tr>
<th valign="bottom" colspan="4" align="left">Risk factor for HIV</th>
</tr>
<tr>
<td valign="bottom" align="left">Heterosexual (%)</td>
<td valign="bottom" align="center">180/319 (56%)</td>
<td valign="bottom" align="center">3/5 (60%)</td>
<td valign="middle" align="center">0.425</td>
</tr>
<tr>
<td valign="bottom" align="left">MSM (%)</td>
<td valign="bottom" align="center">95/319 (30%)</td>
<td valign="bottom" align="center">0/5 (0%)</td>
<td valign="bottom" align="center"/>
</tr>
<tr>
<td valign="bottom" align="left">IVDU (%)</td>
<td valign="bottom" align="center">28/319 (9%)</td>
<td valign="bottom" align="center">1/5 (20%)</td>
<td valign="bottom" align="center"/>
</tr>
<tr>
<td valign="bottom" align="left">Unknown (%)</td>
<td valign="bottom" align="center">16/319 (5%)</td>
<td valign="bottom" align="center">1/5 (20%)</td>
<td valign="bottom" align="center"/>
</tr>
<tr>
<th valign="bottom" colspan="4" align="left">Nationality</th>
</tr>
<tr>
<td valign="bottom" align="left">Italian (%)</td>
<td valign="bottom" align="center">236/319 (74%)</td>
<td valign="bottom" align="center">4/5 (80%)</td>
<td valign="bottom" align="center">0.613</td>
</tr>
<tr>
<th valign="bottom" colspan="4" align="left">CDC stage at the time of diagnosis</th>
</tr>
<tr>
<td valign="bottom" align="left">Stage A (%)</td>
<td valign="bottom" align="center">120/319 (38%)</td>
<td valign="bottom" align="center">1/5 (20%)</td>
<td valign="middle" align="center">0.559</td>
</tr>
<tr>
<td valign="bottom" align="left">Stage B (%)</td>
<td valign="bottom" align="center">129/319 (40.7%)</td>
<td valign="bottom" align="center">2/5 (40%)</td>
<td valign="bottom" align="center"/>
</tr>
<tr>
<td valign="bottom" align="left">Stage C (%)</td>
<td valign="bottom" align="center">69/319 (21%)</td>
<td valign="bottom" align="center">2/5 (40%)</td>
<td valign="bottom" align="center"/>
</tr>
<tr>
<td valign="bottom" align="left">Unknown</td>
<td valign="bottom" align="center">1/319 (0.3%)</td>
<td valign="bottom" align="center">0 (0%)</td>
<td valign="bottom" align="center"/>
</tr>
<tr>
<th valign="bottom" colspan="4" align="left">Co-infections</th>
</tr>
<tr>
<td valign="bottom" align="left">Ab anti-HCV positivity at baseline</td>
<td valign="bottom" align="center">31/319 (10%)</td>
<td valign="bottom" align="center">2/5 (40%)</td>
<td valign="bottom" align="center">0.084</td>
</tr>
<tr>
<td valign="bottom" align="left">HBsAg positivity at baseline</td>
<td valign="bottom" align="center">304/319 (95%)</td>
<td valign="bottom" align="center">5/5 (100%)</td>
<td valign="bottom" align="center">0.788</td>
</tr>
<tr>
<td valign="bottom" align="left">CMV-IgG positivity at baseline</td>
<td valign="bottom" align="center">267/319 (84%)</td>
<td valign="bottom" align="center">5/5 (100%)</td>
<td valign="bottom" align="center">0.615</td>
</tr>
<tr>
<th valign="bottom" colspan="4" align="left">Other</th>
</tr>
<tr>
<td valign="bottom" align="left">Chemotherapy</td>
<td valign="bottom" align="center">8/319 (2%)</td>
<td valign="bottom" align="center">0 (0%)</td>
<td valign="bottom" align="center">0.882</td>
</tr>
<tr>
<td valign="bottom" align="left">Deaths</td>
<td valign="bottom" align="center">4/319 (2%)</td>
<td valign="bottom" align="center">1/5 (20%)</td>
<td valign="bottom" align="center">&lt;0.001</td>
</tr>
<tr>
<th valign="bottom" colspan="4" align="left">Immunovirological data</th>
</tr>
<tr>
<td valign="top" align="left">CD4 nadir (n/mmc) mean (SD)</td>
<td valign="bottom" align="center">279 (&#xb1;222)</td>
<td valign="bottom" align="center">33 (&#xb1;26)</td>
<td valign="bottom" align="center">0.014</td>
</tr>
<tr>
<td valign="top" align="left">CD8+ at baseline, median (SD)</td>
<td valign="bottom" align="center">942 (&#xb1;584)</td>
<td valign="bottom" align="center">609 (&#xb1;308)</td>
<td valign="bottom" align="center">0.365</td>
</tr>
<tr>
<td valign="top" align="left">CD8+ at 36 months, mean (SD)</td>
<td valign="bottom" align="center">893 (&#xb1;404)</td>
<td valign="bottom" align="center">811(&#xb1;367)</td>
<td valign="bottom" align="center">0.652</td>
</tr>
<tr>
<td valign="top" align="left">CD4/CD8 ratio at baseline, median (IQR)</td>
<td valign="bottom" align="center">0.32 (0.16&#x2013;0.61)</td>
<td valign="bottom" align="center">0.14 (0.05&#x2013;0.15)</td>
<td valign="bottom" align="center">0.012</td>
</tr>
<tr>
<td valign="top" align="left">CD4/CD8 ratio at 36 months median (IQR)</td>
<td valign="bottom" align="center">0.78 (0.49&#x2013;1.11)</td>
<td valign="bottom" align="center">0.17 (0.13&#x2013;0.25)</td>
<td valign="bottom" align="center">&lt;0.001</td>
</tr>
<tr>
<td valign="top" align="left">HIV-RNA zenith, log<sub>10</sub> (copies/ml), mean (SD)</td>
<td valign="bottom" align="center">4.77 (&#xb1;1.04)</td>
<td valign="bottom" align="center">4.61 (&#xb1;0.55)</td>
<td valign="bottom" align="center">0.719</td>
</tr>
<tr>
<td valign="bottom" align="left">Time to HIV-RNA &#x2264; 50 copies/ml (months), mean (SD)</td>
<td valign="bottom" align="center">4 (&#xb1;0.19)</td>
<td valign="bottom" align="center">5 (&#xb1;2.34)</td>
<td valign="bottom" align="center">0.970</td>
</tr>
<tr>
<th valign="bottom" colspan="4" align="left">Therapy</th>
</tr>
<tr>
<td valign="bottom" align="left">Months of INI exposure, mean (SD)</td>
<td valign="bottom" align="center">13 (&#xb1;0.92)</td>
<td valign="bottom" align="center">21 (&#xb1;8.81)</td>
<td valign="bottom" align="center">0.322</td>
</tr>
<tr>
<td valign="bottom" align="left">Months of PI exposure, mean (SD)</td>
<td valign="bottom" align="center">10 (&#xb1;0.85)</td>
<td valign="bottom" align="center">14 (&#xb1;8.18)</td>
<td valign="bottom" align="center">0.690</td>
</tr>
<tr>
<td valign="bottom" align="left">Months of NNRTI exposure, mean (SD)</td>
<td valign="bottom" align="center">13 (&#xb1;0.92)</td>
<td valign="bottom" align="center">7 (&#xb1;7.22)</td>
<td valign="bottom" align="center">0.310</td>
</tr>
<tr>
<td valign="bottom" align="left">Months of ABC/3TC exposure, mean (SD)</td>
<td valign="bottom" align="center">4 (&#xb1;0.55)</td>
<td valign="bottom" align="center">0</td>
<td valign="bottom" align="center">0.322</td>
</tr>
<tr>
<td valign="bottom" align="left">Months of TDF/FTC exposure, mean (SD)</td>
<td valign="bottom" align="center">28 (&#xb1;0.74)</td>
<td valign="bottom" align="center">22 (&#xb1;8.81)</td>
<td valign="bottom" align="center">0.447</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>ABC/3TC, abacavir+ lamivudine; HBsAg hepatitis B surface antigen; INR<sub>200</sub> people who did not recover at least 200 CD4+T cells after 36 months of virological suppression (HIV RNA &lt;50 copies/ml) on antiretroviral therapy; IQR, interquartile range; INI, integrase inhibitors; IVDU intravenous drug users; MSM, men who have sex with men; NNRTI, nonnucleoside reverse transcriptase inhibitors; NRTI, nucleoside or nucleotide reverse transcriptase inhibitors; PI, protease inhibitors; SD, standard deviation; TDF/FTC tenofovir disoproxil fumarate/emtricitabine.</p>
</fn>
</table-wrap-foot>
</table-wrap>
</sec>
</sec>
<sec id="s3_2">
<label>3.2</label>
<title>Comparison of factors associated with INR<sub>20%</sub>, INR<sub>500</sub>, and INR<sub>200</sub> at multivariable analysis</title>
<p>Univariate analysis of factors associated with INR<sub>20%</sub>, INR<sub>500</sub>, and INR<sub>200</sub> are shown in <xref ref-type="supplementary-material" rid="SM1">
<bold>Supplementary Tables 1, 2, and 3</bold>
</xref>. After adjustment for possible confounders, CD4 nadir remained the only factor that maintained a significant association with all INR definitions, with higher values predicting INR<sub>20%</sub> [adjusted odds ratio (aOR) 1.003, 95% CI 1.001&#x2013;1.004, <italic>p</italic>&#xa0;&lt;&#xa0;0.001] and lower values predicting INR<sub>500</sub> (aOR 0.984, 95% CI 0.980&#x2013;0.988, <italic>p</italic>&#xa0;&lt;&#xa0;0.001) and INR<sub>200</sub> (aOR 0.98, 95% CI 0.95&#x2013;1.001, <italic>p</italic>&#xa0;=&#xa0;0.098). Both INR<sub>20%</sub> and INR<sub>500</sub> were associated with lower CD8+ T cell counts after 36 months of suppressive ART (aOR 0.99, 95% CI 0.99&#x2013;1.00, <italic>p</italic>&#xa0;=&#xa0;0.010, and aOR 0.99, 95% CI 0.99&#x2013;1.00, <italic>p</italic>&#xa0;&lt;&#xa0;0.001, respectively). The complete multivariable analysis is shown in <xref ref-type="table" rid="T5">
<bold>Table&#xa0;5</bold>
</xref>.</p>
<table-wrap id="T5" position="float">
<label>Table&#xa0;5</label>
<caption>
<p>Multivariable analysis of factors associated to INR<sub>20%</sub>, INR<sub>500</sub> and INR<sub>200</sub>.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="top" align="left"/>
<th valign="top" colspan="2" align="center">INR<sub>20%</sub>
</th>
<th valign="top" colspan="2" align="center">INR<sub>500</sub>
</th>
<th valign="top" colspan="2" align="center">INR<sub>200</sub>
</th>
</tr>
<tr>
<th valign="top" align="left">Variable</th>
<th valign="top" align="center">aOR (95%CI)</th>
<th valign="top" align="center">
<italic>p</italic> value</th>
<th valign="top" align="center">aOR</th>
<th valign="top" align="center">
<italic>p</italic> value</th>
<th valign="top" align="center">aOR</th>
<th valign="top" align="center">
<italic>p</italic> value</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="left">Non-Italian</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center">1.47 (0.68&#x2013;3.18)</td>
<td valign="top" align="center">0.332</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="left">CDC C stage at HIV diagnosis</td>
<td valign="top" align="center">0.54 (0.15&#x2013;1.95)</td>
<td valign="top" align="center">0.346</td>
<td valign="top" align="center">0.55 (0.23&#x2013;1.33)</td>
<td valign="top" align="center">0.185</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="bottom" align="left">Deaths</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center">9.07 (0.64&#x2013;126.9)</td>
<td valign="top" align="center">0.101</td>
</tr>
<tr>
<td valign="top" align="left">
<bold>Immunovirological data</bold>
</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="left">CD4 nadir (n/mmc)</td>
<td valign="top" align="center">1.003 (1.001&#x2013;1.004)</td>
<td valign="top" align="center">&lt;0.001</td>
<td valign="top" align="center">0.98 (0.98&#x2013;0.99)</td>
<td valign="top" align="center">&lt;0.001</td>
<td valign="top" align="center">0.98 (0.95&#x2013;1.01)</td>
<td valign="top" align="center">0.096</td>
</tr>
<tr>
<td valign="top" align="left">CD8 at 36 months</td>
<td valign="top" align="center">0.99 (0.99&#x2013;1.00)</td>
<td valign="top" align="center">0.010</td>
<td valign="top" align="center">0.99 (0.99&#x2013;1.00)</td>
<td valign="top" align="center">&lt;0.001</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="left">HIV-RNA zenith, log<sub>10</sub>
</td>
<td valign="top" align="center">0.99 (0.99&#x2013;1.00)</td>
<td valign="top" align="center">0.010</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="bottom" align="left">Months of INI exposure</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center">1.03 (1.01&#x2013;1.05)</td>
<td valign="top" align="center">0.037</td>
<td valign="bottom" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="bottom" align="left">Months of NNRTI exposure</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center">1.03 (0.99&#x2013;1.05)</td>
<td valign="top" align="center">0.076</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>95%CI, 95% Confidence Interval; aOR, adjusted Odds Ratio; FR<sub>200</sub>, full responders, defined as people who recover at least 200 CD4+T cells after 36 months of virological suppression (HIV RNA &lt;50 copies/ml) on antiretroviral therapy INR<sub>20%</sub> people who did not recover at least 20% CD4+T cells after 36 months of virological suppression (HIV RNA &lt;50 copies/ml) on antiretroviral therapy; INR<sub>500</sub> people who did not recover at least 500 CD4+T cells after 36 months of virological suppression (HIV RNA &lt;50 copies/ml) on antiretroviral therapy; INR<sub>200</sub> people who did not recover at least 200 CD4+T cells after 36 months of virological suppression (HIV RNA &lt;50 copies/ml) on antiretroviral therapy.</p>
</fn>
</table-wrap-foot>
</table-wrap>
<p>In the sensitivity analysis including the CD4/CD8 ratio instead of the absolute numbers of CD4 and CD8+ T cells (<xref ref-type="table" rid="T6">
<bold>Table&#xa0;6</bold>
</xref>), a higher baseline CD4/CD8 ratio was confirmed to be inversely related to the probability of poor immune recovery for INR<sub>500</sub> (OR 0.03, 95% CI 0.01&#x2013;0.12, <italic>p</italic>&#xa0;&lt;&#xa0;0.001) and INR<sub>200</sub> (OR 0.002, 95% CI 18<sup>&#x2013;7</sup>&#x2013;67.72, <italic>p</italic>&#xa0;=&#xa0;0.255), and it was directly related to the odds of being INR<sub>20%</sub> (OR 6.14, 95%CI 2.36&#x2013;15.97, p&lt;0.001).</p>
<table-wrap id="T6" position="float">
<label>Table&#xa0;6</label>
<caption>
<p>Multivariable analysis of factors associated to INR<sub>20%</sub>, INR<sub>500</sub> and INR<sub>200</sub>, including CD4/CD8 ratio at baseline.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="top" align="left"/>
<th valign="top" colspan="2" align="center">INR<sub>20%</sub>
</th>
<th valign="top" colspan="2" align="center">INR<sub>500</sub>
</th>
<th valign="top" colspan="2" align="center">INR<sub>200</sub>
</th>
</tr>
<tr>
<th valign="top" align="left">Variable</th>
<th valign="top" align="center">aOR (95% CI)</th>
<th valign="top" align="center">
<italic>p</italic>-value</th>
<th valign="top" align="center">aOR</th>
<th valign="top" align="center">
<italic>p</italic>-value</th>
<th valign="top" align="center">aOR</th>
<th valign="top" align="center">
<italic>p</italic>-value</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="left">Non-Italian</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center">1.39 (0.76&#x2013;2.56)</td>
<td valign="top" align="center">0.285</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="left">CDC C stage at HIV diagnosis</td>
<td valign="top" align="center">0.46 (0.13&#x2013;1.62)</td>
<td valign="top" align="center">0.227</td>
<td valign="top" align="center">1.36 (0.71&#x2013;2.59)</td>
<td valign="top" align="center">0.348</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="bottom" align="left">Deaths</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center">10.24 (0.81&#x2013;129.41)</td>
<td valign="top" align="center">0.072</td>
</tr>
<tr>
<td valign="top" align="left">
<bold>Immunovirological data</bold>
</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="left">CD4/CD8 ratio at baseline</td>
<td valign="top" align="center">6.14 (2.36&#x2013;15.97)</td>
<td valign="top" align="center">&lt;0.001</td>
<td valign="top" align="center">0.03 (0.01&#x2013;0.12)</td>
<td valign="top" align="center">&lt;0.001</td>
<td valign="top" align="center">0.002 (18e-7&#x2013;67.72)</td>
<td valign="top" align="center">0.255</td>
</tr>
<tr>
<td valign="top" align="left">HIV-RNA zenith, log<sub>10</sub>
</td>
<td valign="top" align="center">0.84 (0.59&#x2013;1.19)</td>
<td valign="top" align="center">0.328</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="bottom" align="left">Months of INI exposure</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center">1.00 (0.99&#x2013;1.03)</td>
<td valign="top" align="center">0.394</td>
<td valign="bottom" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="bottom" align="left">Months of NNRTI exposure</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center">0.99 (0.97&#x2013;1.01)</td>
<td valign="top" align="center">0.592</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>95%CI, 95% confidence interval; aOR, adjusted odds ratio; INR<sub>20%</sub> people who did not recover at least 20% CD4+T cells after 36 months of virological suppression (HIV RNA &lt;50 copies/ml) on antiretroviral therapy; INR<sub>500</sub> people who did not recover at least 500 CD4+T cells after 36 months of virological suppression (HIV RNA &lt;50 copies/ml) on antiretroviral therapy; INR<sub>200</sub> people who did not recover at least 200 CD4+T cells after 36 months of virological suppression (HIV RNA &lt;50 copies/ml) on antiretroviral therapy.</p>
</fn>
</table-wrap-foot>
</table-wrap>
<p>At the 36-month evaluation, the relationship between CD4/CD8 ratio and INR was confirmed, with OR 0.05 (95% CI 0.02&#x2013;0.13, <italic>p</italic>&#xa0;&lt;&#xa0;0.001) and 1.9<sup>&#x2013;14</sup> (95% CI 4.5<sup>&#x2013;25</sup>&#x2013;7.88<sup>&#x2013;4</sup>, <italic>p</italic>&#xa0;=&#xa0;0.011) of being INR<sub>500</sub> and INR<sub>200</sub>, respectively, and OR 1.30 (95% CI 0.72&#x2013;2.33) of being INR<sub>20%</sub> for each unit of increase of CD4/CD8 ratio (<xref ref-type="table" rid="T7">
<bold>Table&#xa0;7</bold>
</xref>).</p>
<table-wrap id="T7" position="float">
<label>Table&#xa0;7</label>
<caption>
<p>Multivariable analysis of factors associated to INR<sub>20%</sub>, INR<sub>500</sub> and INR<sub>200</sub>, including CD4/CD8 ratio at 36 months evaluation.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="top" align="left"/>
<th valign="top" colspan="2" align="center">INR<sub>20%</sub>
</th>
<th valign="top" colspan="2" align="center">INR<sub>500</sub>
</th>
<th valign="top" colspan="2" align="center">INR<sub>200</sub>
</th>
</tr>
<tr>
<th valign="top" align="left">Variable</th>
<th valign="top" align="center">aOR (95% CI)</th>
<th valign="top" align="center">
<italic>p</italic>-value</th>
<th valign="top" align="center">aOR</th>
<th valign="top" align="center">
<italic>p</italic>-value</th>
<th valign="top" align="center">aOR</th>
<th valign="top" align="center">
<italic>p</italic>-value</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" colspan="7" align="left">Age in years</td>
</tr>
<tr>
<td valign="top" align="left">Non-Italian</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center">1.42 (0.76&#x2013;2.66)</td>
<td valign="top" align="center">0.271</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="left">CDC C stage at HIV diagnosis</td>
<td valign="top" align="center">0.31 (0.09&#x2013;1.07)</td>
<td valign="top" align="center">0.063</td>
<td valign="top" align="center">1.68 (0.88&#x2013;3.23)</td>
<td valign="top" align="center">0.118</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="left">Deaths</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center">15.1 (4.59e-25&#x2013;7.88e-4)</td>
<td valign="top" align="center">0.587</td>
</tr>
<tr>
<td valign="top" align="left">
<bold>Immunovirological data</bold>
</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="left">CD4/CD8 ratio at 36 months</td>
<td valign="top" align="center">1.30 (0.72&#x2013;2.33)</td>
<td valign="top" align="center">0.378</td>
<td valign="top" align="center">0.05 (0.02&#x2013;0.13)</td>
<td valign="top" align="center">&lt;0.001</td>
<td valign="top" align="center">1.9e-14 (4.5e-25&#x2013;7.88e-4)</td>
<td valign="top" align="center">0.011</td>
</tr>
<tr>
<td valign="top" align="left">HIV-RNA zenith, log<sub>10</sub>
</td>
<td valign="top" align="center">0.81 (0.59&#x2013;1.10)</td>
<td valign="top" align="center">0.170</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="left">Months of INI exposure</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center">1.00 (0.98&#x2013;1.03)</td>
<td valign="top" align="center">0.512</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="left">Months of NNRTI exposure</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center">0.99 (0.97&#x2013;1.02)</td>
<td valign="top" align="center">0.715</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>95% CI, 95% confidence interval; aOR, adjusted odds ratio; INR<sub>20%</sub> people who did not recover at least 20% CD4+T cells after 36 months of virological suppression (HIV RNA &lt;50 copies/ml) on antiretroviral therapy; INR<sub>500</sub> people who did not recover at least 500 CD4+T cells after 36 months of virological suppression (HIV RNA &lt;50 copies/ml) on antiretroviral therapy; INR<sub>200</sub> people who did not recover at least 200 CD4+T cells after 36 months of virological suppression (HIV RNA &lt;50 copies/ml) on antiretroviral therapy.</p>
</fn>
</table-wrap-foot>
</table-wrap>
</sec>
</sec>
<sec id="s4" sec-type="discussion">
<label>4</label>
<title>Discussion</title>
<p>In the present study we found a prevalence of INR ranging between 1.5% and 34.6%, exploring different definition of immunological non-response.</p>
<p>The most restrictive definition that we used, namely that of INR<sub>200</sub>, revealed an INR<sub>200</sub> rate of only 1.5%, which was lower than that reported in older studies that used the same threshold, which ranged between 15% and 26% (<xref ref-type="bibr" rid="B11">11</xref>, <xref ref-type="bibr" rid="B42">42</xref>, <xref ref-type="bibr" rid="B44">44</xref>), but which is consistent with the results of others (<xref ref-type="bibr" rid="B45">45</xref>). However, comparison among studies might be influenced by different study periods and antiretrovirals used in different settings and by heterogeneous duration of follow-up. The higher frequency of INR<sub>200</sub> found in previous years might reflect the use of older drugs that are currently considered sub-optimal or less tolerable, possibly compromising overall ART efficacy and, consequently, also immunological recovery (<xref ref-type="bibr" rid="B11">11</xref>, <xref ref-type="bibr" rid="B42">42</xref>, <xref ref-type="bibr" rid="B44">44</xref>). On the contrary, newer drugs such as INSTIs (<xref ref-type="bibr" rid="B46">46</xref>, <xref ref-type="bibr" rid="B47">47</xref>), and also PIs, when compared with older ART approaches (<xref ref-type="bibr" rid="B48">48</xref>), might favor a more effective immune recovery. However, in our study, we did not find a consistent correlation between INR rate and months of exposure to different classes of antiretrovirals. It is notable that the study was conducted in an era of modern ART; if different ART classes were used in first-line therapy, the usefulness of comparing newer and older drugs is limited by the absence of an historical control group. In addition, the observation about the role of a low CD4 nadir underlying the INR<sub>200</sub> phenomenon underscores the very important role of early diagnosis in preventing the INR phenomenon; increased awareness of the risk of infection and improved timing of diagnosis could explain, at least in part, the reduction in the current number of INR<sub>200</sub>.</p>
<p>On the other hand, when assessing frequency of INR<sub>500</sub>, we still found about 35% of PLWH with a discordant viro-immunological response, in line with the frequency found in previous studies (<xref ref-type="bibr" rid="B34">34</xref>, <xref ref-type="bibr" rid="B45">45</xref>, <xref ref-type="bibr" rid="B46">46</xref>), suggesting that, even if modern therapies have contributed to make INR<sub>200</sub> rarer, the complete viro-immunological response is still not guaranteed nor consistently improved compared with the past, when using the CD4 threshold of 500 cells/mm<sup>3</sup>. Even if the highest risk of clinical events and death has been associated with INR<sub>200</sub> (<xref ref-type="bibr" rid="B11">11</xref>, <xref ref-type="bibr" rid="B42">42</xref>, <xref ref-type="bibr" rid="B44">44</xref>), PLWH with a CD4 count in the range 200&#x2013;499 cells/mm<sup>3</sup> still have higher mortality rates than those with a CD4 count &gt;&#xa0;500 cells/mm<sup>3</sup> (<xref ref-type="bibr" rid="B49">49</xref>). Therefore, the goal of ART should be to get patients over this threshold and reaching an immunological condition as close as possible to that of the general population. Moreover, INR<sub>500</sub> have been shown to have higher percentages of activated CD4+ T cells, regulatory T cells (T<sub>reg</sub>), effector T<sub>reg</sub> and terminal effector T<sub>reg</sub> suggesting, in this group of PLWH, a residual immune activation persisting after many years of ART (<xref ref-type="bibr" rid="B18">18</xref>, <xref ref-type="bibr" rid="B35">35</xref>). In addition, immune responses against vaccines are still different among PWH with CD4+ T cell counts of &lt;&#xa0;200, 200&#x2013;500, or &gt;&#xa0;500 cells/mm<sup>3</sup>, and in those with counts of &gt;&#xa0;500 cells/mm<sup>3</sup> responses comparable to those in the HIV-uninfected population have been described (<xref ref-type="bibr" rid="B50">50</xref>). The persistence of a certain grade of inflammation might also be indirectly inferred from the CD4/CD8 ratio, a surrogate marker of T-cell compartment balance, reflecting both CD4 T-cell recovery and CD8 T-cell activation, expansion, and senescence (<xref ref-type="bibr" rid="B51">51</xref>, 8). Few studies have investigated the relationship between CD4/CD8 ratio and immune recovery, supporting an association between lower baseline levels and immunodiscordant response to ART (<xref ref-type="bibr" rid="B46">46</xref>, <xref ref-type="bibr" rid="B52">52</xref>). In our study, we found not only that a higher CD4/CD8 ratio was protective toward becoming either INR<sub>200</sub> or INR<sub>500</sub> at time of ART initiation, but also that that CD4/CD8 ratio was more likely to be lower after 36 months of ART in INR<sub>200</sub> and INR<sub>500</sub> than in full responders, supporting the hypothesis of a possible persistent immune activation impairing reconstitution of the immune system and CD4 gains (<xref ref-type="bibr" rid="B53">53</xref>). Moreover, CD4 nadir was confirmed to be the stronger predictor of immunological non-response in INR<sub>200</sub> and INR<sub>500</sub>, in accordance with data from the literature (<xref ref-type="bibr" rid="B18">18</xref>, <xref ref-type="bibr" rid="B34">34</xref>, <xref ref-type="bibr" rid="B44">44</xref>, <xref ref-type="bibr" rid="B45">45</xref>, <xref ref-type="bibr" rid="B54">54</xref>), and all other epidemiological and clinical variables considered did not consistently correlate with INR. Instead, these data were not confirmed when using the definition of INR<sub>20%</sub>. In fact, in our study, the odds of being INR<sub>20%</sub> was higher in PLWH with a higher CD4 nadir and higher CD4/CD8 ratio. Being INR<sub>20%</sub> has been described in the past as a predictor of clinical progression (<xref ref-type="bibr" rid="B14">14</xref>); however, the definition of INR<sub>20%</sub> is highly influenced by baseline CD4&#x2013; T cell count and, in an era of modern ART, where therapy is initiated regardless of total CD4 count at HIV diagnosis, this definition may be misleading, as it may imply the inclusion of early-treated patients with unimpaired baseline CD4 counts. Consequently, these PLWH do not experience an increase in CD4 above the predefined threshold of 20% from baseline, but this should not be interpreted as a poor response. On the contrary, for PLWH with extremely low CD4 counts, a small CD4 gain could even exceed the threshold of 20% while remaining with a very low absolute number of lymphocytes and CD4/CD8 ratio. Therefore, even if the definition can still be applied to certain clinical situations in PLWH stratified based on baseline CD4 counts, or in certain research contexts, INR<sub>20%</sub> might not be a suitable definition for identifying in general PLWH with poor responses in clinical practice.</p>
<p>The present study has several limitations. The retrospective design and relatively small sample size of the cohort limit the strength and generalizability of the findings. Moreover, data on biomarkers of immune activation, on viral reservoir, as well as data on herpetic viral co-infections, genetics, and behavioral or dietary factors were not available, limiting the possibility of investigation of further variables influencing immunological responses. In addition, the exclusion of people lost to follow-up or dead before the predefined time point of 36 months might have contributed to underestimation of INRs. Despite these limits, the study highlights how INR<sub>200</sub> have become very rare in the contemporary ART era, and still about one-third of PLWH meet the criteria for INR<sub>500</sub>. Overcoming the threshold of 500&#xa0;CD4/mm<sup>3</sup> could be more appropriate to define full responders, in contrast with the older definitions of INR<sub>200</sub> and INR<sub>20%</sub>. Although our results do not show a benefit from choosing different ART strategies to improve immune recovery, early diagnosis, and rapid treatment initiation before CD4 counts and CD4/CD8 ratio begin to decline are critical to achieving an optimal immune response.</p>
</sec>
<sec id="s5" sec-type="data-availability">
<title>Data availability statement</title>
<p>The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.</p>
</sec>
<sec id="s6" sec-type="ethics-statement">
<title>Ethics statement</title>
<p>The studies involving human participants were reviewed and approved by Ligurian Ethics Committee. The patients/participants provided their written informed consent to participate in this study.</p>
</sec>
<sec id="s7" sec-type="author-contributions">
<title>Author contributions</title>
<p>LT, LL, FB, GB, SB, AB, and MB performed the research. SM, SB, and MG managed the database and checked the accuracy of the data. LT, LL, and AB designed the research study. LT analyzed the data. LT, LL, FB, and GB wrote the paper. MB and AB reviewed the final version of the paper and the scientific contents of the study. All authors have read and approved the final version of the paper.</p>
</sec>
</body>
<back>
<sec id="s8" sec-type="COI-statement">
<title>Conflict of interest</title>
<p>The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.</p>
</sec>
<sec id="s9" sec-type="disclaimer">
<title>Publisher&#x2019;s note</title>
<p>All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.</p>
</sec>
<sec id="s10" sec-type="supplementary-material">
<title>Supplementary material</title>
<p>The Supplementary Material for this article can be found online at: <ext-link ext-link-type="uri" xlink:href="https://www.frontiersin.org/articles/10.3389/fviro.2022.822153/full#supplementary-material">https://www.frontiersin.org/articles/10.3389/fviro.2022.822153/full#supplementary-material</ext-link>
</p>
<supplementary-material xlink:href="Table_1.docx" id="SM1" mimetype="application/vnd.openxmlformats-officedocument.wordprocessingml.document"/>
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