<?xml version="1.0" encoding="UTF-8"?><!DOCTYPE article PUBLIC "-//NLM//DTD JATS (Z39.96) Journal Publishing DTD v1.2 20190208//EN" "http://jats.nlm.nih.gov/publishing/1.2/JATS-journalpublishing1.dtd"><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" article-type="research-article" dtd-version="1.2" xml:lang="en">
    <front>
        <journal-meta>
            <journal-id journal-id-type="pmc">F1000Research</journal-id>
            <journal-title-group>
                <journal-title>F1000Research</journal-title>
            </journal-title-group>
            <issn pub-type="epub">2046-1402</issn>
            <publisher>
                <publisher-name>F1000 Research Limited</publisher-name>
                <publisher-loc>London, UK</publisher-loc>
            </publisher>
        </journal-meta>
        <article-meta>
            <article-id pub-id-type="doi">10.12688/f1000research.125858.1</article-id>
            <article-categories>
                <subj-group subj-group-type="heading">
                    <subject>Research Article</subject>
                </subj-group>
                <subj-group>
                    <subject>Articles</subject>
                </subj-group>
            </article-categories>
            <title-group>
                <article-title>Neutrophil/lymphocyte ratio and overall survival in patients with breast cancer: a cohort study in a Latin-American hospital</article-title>
                <fn-group content-type="pub-status">
                    <fn>
                        <p>[version 1; peer review: 1 approved with reservations]</p>
                    </fn>
                </fn-group>
            </title-group>
            <contrib-group>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>Huam&#x00e1;n C&#x00f3;rdova</surname>
                        <given-names>Nataly Briyit</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Conceptualization</role>
                    <role content-type="http://credit.niso.org/">Data Curation</role>
                    <role content-type="http://credit.niso.org/">Project Administration</role>
                    <uri content-type="orcid">https://orcid.org/0000-0002-8708-5435</uri>
                    <xref ref-type="aff" rid="a1">1</xref>
                </contrib>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>Cervera-Oca&#x00f1;a</surname>
                        <given-names>Martha Sofia</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Original Draft Preparation</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Review &amp; Editing</role>
                    <xref ref-type="aff" rid="a2">2</xref>
                    <xref ref-type="aff" rid="a3">3</xref>
                </contrib>
                <contrib contrib-type="author" corresp="yes">
                    <name>
                        <surname>Qui&#x00f1;ones-Laveriano</surname>
                        <given-names>Dante M.</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Conceptualization</role>
                    <role content-type="http://credit.niso.org/">Formal Analysis</role>
                    <role content-type="http://credit.niso.org/">Investigation</role>
                    <role content-type="http://credit.niso.org/">Methodology</role>
                    <xref ref-type="corresp" rid="c1">a</xref>
                    <xref ref-type="aff" rid="a4">4</xref>
                </contrib>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>De La Cruz-Vargas</surname>
                        <given-names>Jhony A.</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Supervision</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Review &amp; Editing</role>
                    <xref ref-type="aff" rid="a1">1</xref>
                    <xref ref-type="aff" rid="a4">4</xref>
                </contrib>
                <aff id="a1">
                    <label>1</label>Facultad de Medicina Humana, Universidad Ricardo Palma, Lima, Peru</aff>
                <aff id="a2">
                    <label>2</label>Facultad de Ciencias M&#x00e9;dicas, Universidad C&#x00e9;sar Vallejo, Trujillo, Peru</aff>
                <aff id="a3">
                    <label>3</label>Sociedad Cient&#x00ed;fica de Estudiantes de Medicina de la Universidad C&#x00e9;sar Vallejo, Trujillo, Peru</aff>
                <aff id="a4">
                    <label>4</label>Instituto de Investigaciones en Ciencias Biom&#x00e9;dicas, Universidad Ricardo Palma, Lima, Peru</aff>
            </contrib-group>
            <author-notes>
                <corresp id="c1">
                    <label>a</label>
                    <email xlink:href="mailto:dante.quinones@urp.edu.pe">dante.quinones@urp.edu.pe</email>
                </corresp>
                <fn fn-type="conflict">
                    <p>No competing interests were disclosed.</p>
                </fn>
            </author-notes>
            <pub-date pub-type="epub">
                <day>24</day>
                <month>3</month>
                <year>2023</year>
            </pub-date>
            <pub-date pub-type="collection">
                <year>2023</year>
            </pub-date>
            <volume>12</volume>
            <elocation-id>331</elocation-id>
            <history>
                <date date-type="accepted">
                    <day>3</day>
                    <month>2</month>
                    <year>2023</year>
                </date>
            </history>
            <permissions>
                <copyright-statement>Copyright: &#x00a9; 2023 Huam&#x00e1;n C&#x00f3;rdova NB et al.</copyright-statement>
                <copyright-year>2023</copyright-year>
                <license xlink:href="https://creativecommons.org/licenses/by/4.0/">
                    <license-p>This is an open access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</license-p>
                </license>
            </permissions>
            <self-uri content-type="pdf" xlink:href="https://f1000research.com/articles/12-331/pdf"/>
            <abstract>
                <p>
                    <bold>Background:</bold> Breast cancer is a disease of high mortality globally. Inflammatory markers have been proposed as prognostic indicators. Therefore, we seek to find an association between the neutrophil-lymphocyte ratio (NLR) and overall survival (OS) of patients with breast cancer in a Latin-American hospital.</p>
                <p>
                    <bold>Methods:</bold> An observational, analytical, longitudinal survival study was conducted in 241 female patients with breast cancer, between 2012 and 2014. The dependent variable was OS, the independent variable was the NLR, and the intervening variables were age, clinical stage, and molecular subtype. The Kaplan&#x2013;Meier method was applied to generate OS functions, and the Cox regression to find crude and adjusted hazard ratio (HR).</p>
                <p>
                    <bold>Results:</bold> The mean age was 56.1 years and 59.8% of patients had an NLR&#x2265;3. According to the Kaplan&#x2013;Meier estimator, NLR&#x2265;3 (p&lt;0.001), age&gt;55 years (p=0.039), and clinical stage (p&lt;0.001), were associated with a lower OS. In the multivariate analysis, the factors significantly associated to a lower OS were NLR&#x2265;3 (HRa: 2.00; CI 95%: 1.36&#x2013;2.95), age&gt;55 years (HRa: 1.64; CI 95%: 1.10&#x2013;2.44), and clinical stage IV (HRa: 68; CI 95%: 2.28&#x2013;20.20).</p>
                <p>
                    <bold>Conclusions:</bold> The inflammatory marker NLR&#x2265;3 was independently associated with a lower OS. Additionally, advanced stage and older age were associated with a lower OS.</p>
            </abstract>
            <kwd-group kwd-group-type="author">
                <kwd>Breast Neoplasm</kwd>
                <kwd>Survival</kwd>
                <kwd>Inflammatory markers</kwd>
                <kwd>prognostic factors</kwd>
            </kwd-group>
            <funding-group>
                <funding-statement>The author(s) declared that no grants were involved in supporting this work.</funding-statement>
            </funding-group>
        </article-meta>
    </front>
    <body>
        <p>
            <def-list>
                <title>Abbreviations</title>
                <def-item>
                    <term id="G3">HR</term>
                    <def>
                        <p>hazard ratio</p>
                    </def>
                </def-item>
                <def-item>
                    <term id="G2">NLR</term>
                    <def>
                        <p>neutrophil-lymphocyte ratio</p>
                    </def>
                </def-item>
                <def-item>
                    <term id="G4">NLR/LPR</term>
                    <def>
                        <p>neutrophil-lymphocyte ratio/lymphocyte platelet ratio</p>
                    </def>
                </def-item>
                <def-item>
                    <term id="G1">OS</term>
                    <def>
                        <p>overall survival</p>
                    </def>
                </def-item>
            </def-list>
        </p>
        <sec id="sec1" sec-type="intro">
            <title>Introduction</title>
            <p>Breast cancer represents 16% of all female cancers, causing 2.3 million cases and 685,000 deaths worldwide in 2020.
                <sup>
                    <xref ref-type="bibr" rid="ref1">1</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref2">2</xref>
                </sup> In Latin America, this pathology is the most important cause of death by neoplasms among women, with nearly 92,000 deaths,
                <sup>
                    <xref ref-type="bibr" rid="ref3">3</xref>
                </sup> while in Peru it represents the most common primary neoplasm among women.
                <sup>
                    <xref ref-type="bibr" rid="ref4">4</xref>
                </sup> Therefore, it is fundamental to determine the factors associated to overall survival (OS), such as age, comorbidities, metastasis, and laboratory analytical determinations such as neutrophil-lymphocyte ratio (NLR).
                <sup>
                    <xref ref-type="bibr" rid="ref5">5</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref6">6</xref>
                </sup>
            </p>
            <p>While research exists on an international level that associates an elevated NLR with lower OS in patients with breast cancer, these were developed in populations with early-stage diagnosis, as opposed to countries with middle and low incomes, where a high proportion are diagnosed in advanced stages. Furthermore, differences exist in breast cancer phenotype, prevalence of oncological infections,
                <sup>
                    <xref ref-type="bibr" rid="ref7">7</xref>
                </sup> and the presence of social risk factors such as marked poverty and reduced access to healthcare services between Latin-American countries
                <sup>
                    <xref ref-type="bibr" rid="ref8">8</xref>
                </sup> and others.
                <sup>
                    <xref ref-type="bibr" rid="ref9">9</xref>
                </sup> This highlights the need for studying the OS associated with breast cancer and its prognostic indices in this context.</p>
            <p>Since in developing countries, the rate of clinical oncologists per million inhabitants is below the recommended value,
                <sup>
                    <xref ref-type="bibr" rid="ref7">7</xref>
                </sup> simple, accessible, true, and low-cost methods, such as NLR, are required to potentially improve OS in these patients. Some research in Latin America has studied the NLR as an adverse prognostic factor in patients with different types of cancer, with few related to breast cancer.
                <sup>
                    <xref ref-type="bibr" rid="ref10">10</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref11">11</xref>
                </sup> However, these studies were conducted only in patients with triple-negative breast cancer, which, although more aggressive, is not the most frequent of those presented in the region; therefore, it is necessary to perform studies including other cancer subtypes such as Luminal A, Luminal B or HER 2. In this sense, the general objetive of this study is to determine the association between NLR and OS in patients with breast cancer in the gynecology department of Hospital Nacional Hip&#x00f3;lito Unanue (HNHU), Lima, Peru between 2012 and 2014. The specific objectives were to evaluate the association between OS and stage, molecular subtype and age. We hope to find an association between the NLR and the OS, so that the higher the NLR, the lower the OS.</p>
        </sec>
        <sec id="sec2" sec-type="methods">
            <title>Methods</title>
            <sec id="sec3">
                <title>Research design and setting</title>
                <p>An observational, longitudinal, analytical survival study was carried out in female patients diagnosed with breast cancer, seen in HNHU, between 2012 and 2014. The research protocol was carried out and uploaded to protocols.io platform, explaining step by step how the study was carried out.
                    <sup>
                        <xref ref-type="bibr" rid="ref12">12</xref>
                    </sup> The exposed group consisted of those patients with high NLR and their OS was compared with that of the group of patients with normal NLR. Both cohorts were women who were diagnosed at HNHU between 1
                    <sup>st</sup> January 2012 and 31
                    <sup>st</sup> December 2014. Follow-up began at the time of breast cancer diagnosis and exposure was measured on the blood cell count that was measured at the same time as the diagnosis. The follow-up period was up to eight years. The limitations were considered to be those patients who stopped attending their follow-ups without dying or without giving notice of death in the medical record. HNHU is the only III-I establishment in East Lima, Peru, which offers specialized and comprehensive care to cancer patients, and is characterized by having highly qualified staff, innovative health technology, and high-quality standards. The oncology department has a chemotherapy room equipped with nine service areas, one procedure room, and another of oncological combinations; these services are offered to the entire population, mainly to the patients most in need from Seguro Integral de Salud (SIS).
                    <sup>
                        <xref ref-type="bibr" rid="ref13">13</xref>
                    </sup> Data was collected from medical records during the months of January and February 2020.</p>
            </sec>
            <sec id="sec4">
                <title>Participants</title>
                <p>We did not have a sample since we worked with the entire population, with a total of 241 female patients. We found a statistical power of 98% for this number of participants to find an expected OS difference, as reported by a similar study,
                    <sup>
                        <xref ref-type="bibr" rid="ref14">14</xref>
                    </sup> of 86.2% for the exposed group and 97.9% for the unexposed group. This gave us a low probability of making a type 2 error when testing the hypothesis of our main objective, which was to compare the OS of those exposed and not exposed participants. To be included in the study, patients had to be over 18 years of age, with complete and follow-up clinical information from the moment of diagnosis until the last consultation or death. Patients with immune-suppressing diseases or a HIV/AIDS infection were excluded. Follow-up was performed retrospectively from medical assessments recorded in the medical history.</p>
            </sec>
            <sec id="sec5">
                <title>Variables</title>
                <p>The outcome variable of this study was the OS of the patients diagnosed with breast cancer, time was measured in months, from the time of diagnosis until death or date of last follow-up. A participant was considered dead if it was labeled as such in the medical record and corroborated with the death certificate. Additionally, the exposure variable was NLR, which was measured from the first blood count obtained at the time of diagnosis that appears in the medical record. This rate is defined as the division of absolute neutrophil count over absolute lymphocyte count. The rate was categorized as low if NLR&lt;3 and high if NLR&#x2265;3, according to Enr&#x00ed;quez 
                    <italic toggle="yes">et al</italic>.,
                    <sup>
                        <xref ref-type="bibr" rid="ref10">10</xref>
                    </sup> since said cut-off point predicted OS and complete pathological response in this study, in a very similar context. These measurements were made in the same way in the exposed and unexposed group.</p>
                <p>As confounders variables, we considered age, categorized in age groups for descriptive analysis and dichotomized (&gt;55 years), for survival analysis. Likewise, we took into account the clinical stage of breast cancer from the imaging analysis registered in the medical record at the time of diagnosis. The classifications were stage I: small and invasive tumor, with a capacity to spread to lymph nodes; stage II: cancer spread to lymph nodes without evidence of tumor in breasts; stage III: cancer spread to 4-9 axillary or internal mammary lymph nodes, a tumor greater than 50 mm may be found; stage IV: presence of metastasis.
                    <sup>
                        <xref ref-type="bibr" rid="ref15">15</xref>
                    </sup> We also considered the molecular subtype classified as Luminal A, Luminal B, HER 2, and triple-negative.
                    <sup>
                        <xref ref-type="bibr" rid="ref16">16</xref>
                    </sup> These variables were considered in the multivariate model only if they were associated with the bivariate analysis outcome.</p>
                <p>To reduce the selection bias, participants were selected from the same hospital, which contributes to the groups having fairly similar clinical and social characteristics. In addition, the clinical history was reviewed exhaustively to avoid information bias. Finally, an analysis adjusted for confounders was considered to avoid erroneous conclusions.</p>
            </sec>
            <sec id="sec6">
                <title>Procedure</title>
                <p>The data collection technique and follow-up were carried out from the documentation, through a review of medical records of each patient and filled out in a data collection sheet. This research instrument, designed specifically for this study (
                    <italic toggle="yes">Extended data</italic>
                    <sup>
                        <xref ref-type="bibr" rid="ref33">33</xref>
                    </sup>), was filled out with the patient&#x2019;s information, such as age, date of breast cancer diagnosis, molecular subtype, clinical stage, absolute neutrophil count, absolute lymphocyte count, NLR, date of last follow-up, and, if applicable, the date of death and cause of death. Once data was collected, the clinical records were entered into a data matrix in the Microsoft Excel (RRID: SCR_016137), which was used as a database. Later, this data was used to obtain calculations and graphs through the Stata (RRID: SCR_012763) 15.0 statistical program.</p>
            </sec>
            <sec id="sec7">
                <title>Statistical analysis</title>
                <p>First, we found the general characteristics of the entire population using frequencies and percentages for the qualitative variables, and central tendency and dispersion measures for quantitative variables, prior evaluation of its normalcy using the Shapiro-Wilk test.</p>
                <p>Later the Kaplan&#x2013;Meier method was applied to generate survival curves, which were compared using the log-rank test. Likewise, Cox regression was used to find crude and adjusted Hazard Ratios, with its respective 95% confidence intervals. The multivariate model included, as confounding variables, those variables that had statistical significance in the bivariate model, since they could influence the outcome. A p-value&lt;0.05 was considered statistically significant.</p>
                <p>There was only one observed missing observation in the molecular subtype variable and no extra modifications were made before the analysis. This missing number was not relevant to the conclusions of the study as this variable was not included in the multivariate model. Subjects who did not complete all follow-up were also included in the analysis. No sensitivity analyses were performed.</p>
            </sec>
            <sec id="sec8">
                <title>Ethical approval and consent</title>
                <p>This study was approved by the research ethical committee of Hospital Nacional Hip&#x00f3;lito Unanue (file N&#x00b0; 39993; 12
                    <sup>th</sup> December 2019. All the patients&#x2019; data remained in absolute confidentiality by encrypting their personal identification. Patients, or their relatives, signed a written informed consent at the time of admission to the hospital, in favor of performing medical procedures and using their data for teaching and research purposes.</p>
            </sec>
        </sec>
        <sec id="sec9" sec-type="results">
            <title>Results</title>
            <p>Of the 324 initial medical records, we excluded 35 not found and 48 incomplete medical records, leaving a total of 241 medical records for analysis (
                <xref ref-type="fig" rid="f1">Figure 1</xref>). A follow-up of patients was performed in a maximum period of 8 years, with a mean follow-up of 3.5&#x00b1;1.8 years total, 2.7&#x00b1;1.8 years in the exposed group, and 3.9&#x00b1;1.7 years in the non-exposed group. Seventy-five patients (31.1%) were diagnosed in 2012, 84 (34.9%) in 2013, and 82 (34%) in 2014, with 130 patients dying during the study (
                <xref ref-type="table" rid="T1">Table 1</xref>). The age range was 27 to 85 years old (mean: 56.1 years&#x00b1;11.6), the most frequent molecular subtype of breast cancer was HER2 (39.2%), while the most frequent clinical stage was II (42.7%). Furthermore, 144 (59.8%) patients had NLR&#x2265;3. The other general population characteristics are presented in 
                <xref ref-type="table" rid="T2">Table 2</xref>.</p>
            <fig fig-type="figure" id="f1" orientation="portrait" position="float">
                <label>Figure 1. </label>
                <caption>
                    <title>Flow diagram of number of patients with breast cancer in each stage of the study.</title>
                </caption>
                <graphic id="gr1" orientation="portrait" position="float" xlink:href="https://f1000research-files.f1000.com/manuscripts/138206/65cd1729-5e55-428f-ac08-acd9f180e8fb_figure1.gif"/>
            </fig>
            <table-wrap id="T1" orientation="portrait" position="float">
                <label>Table 1. </label>
                <caption>
                    <title>Follow-up characteristics of patients with breast cancer in a Latin-American hospital, between the years 2012 and 2014.</title>
                </caption>
                <table content-type="article-table" frame="hsides">
                    <thead>
                        <tr>
                            <th align="left" colspan="1" rowspan="2" valign="top">Follow-up year</th>
                            <th align="left" colspan="3" rowspan="1" valign="top">Overall</th>
                            <th align="left" colspan="3" rowspan="1" valign="top">NLR
                                <sup>3</sup>3</th>
                            <th align="left" colspan="3" rowspan="1" valign="top">NLR&lt;3</th>
                        </tr>
                        <tr>
                            <th align="left" colspan="1" rowspan="1" valign="top">Total</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">Deaths</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">Excluded</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">Total</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">Deaths</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">Excluded</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">Total</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">Deaths</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">Excluded</th>
                        </tr>
                    </thead>
                    <tbody>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">1</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">241</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">10</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">14</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">97</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">9</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">8</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">144</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">6</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">2</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">217</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">21</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">17</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">80</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">13</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">10</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">137</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">8</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">7</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">3</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">179</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">19</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">20</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">57</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">10</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">11</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">122</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">9</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">9</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">4</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">140</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">20</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">20</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">36</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">7</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">5</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">104</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">13</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">15</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">5</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">100</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">18</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">27</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">24</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">6</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">5</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">76</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">12</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">22</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">6</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">55</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">16</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">18</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">13</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">6</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">42</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">15</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">12</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">7</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">21</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">6</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">11</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">6</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">2</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">3</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">15</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">4</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">8</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">8</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">4</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">3</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">3</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">3</td>
                        </tr>
                    </tbody>
                </table>
                <table-wrap-foot>
                    <p>NLR: Neutrophil-to-lymphocyte ratio.</p>
                </table-wrap-foot>
            </table-wrap>
            <table-wrap id="T2" orientation="portrait" position="float">
                <label>Table 2. </label>
                <caption>
                    <title>General characteristics of patients with breast cancer in a Latin-American hospital, between the years 2012 and 2014.</title>
                </caption>
                <table content-type="article-table" frame="hsides">
                    <thead>
                        <tr>
                            <th align="left" colspan="1" rowspan="2" valign="top"/>
                            <th align="left" colspan="1" rowspan="1" valign="top">NLR&lt;3</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">NLR&#x2265;3</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">Total</th>
                        </tr>
                        <tr>
                            <th align="left" colspan="1" rowspan="1" valign="middle">N=144</th>
                            <th align="left" colspan="1" rowspan="1" valign="middle">N=97</th>
                            <th align="left" colspan="1" rowspan="1" valign="middle">N=241</th>
                        </tr>
                    </thead>
                    <tbody>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">
                                <bold>Mean age</bold>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">54.9&#x00b1;11.4</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">57.9&#x00b1;11.8</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">56.1&#x00b1;11.6</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">
                                <bold>Age groups</bold>
                            </td>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">&#x2003;27 to 40 years</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">15 (10.4%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">11 (11.3%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">26 (10.8%)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">&#x2003;41 to 50 years</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">39 (27.1%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">14 (14.4%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">53 (22.0%)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">&#x2003;51 to 60 years</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">44 (30.6%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">35 (36.1%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">79 (32.8%)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">&#x2003;61 to 70 years</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">31 (21.5%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">23 (23.7%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">54 (22.4%)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">&#x2003;71 or over</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">15 (10.4%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">14 (14.4%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">29 (12.0%)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">
                                <bold>Year of diagnosis</bold>
                            </td>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">&#x2003;2012</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">44 (30.6%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">31 (32.0%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">75 (31.1%)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">&#x2003;2013</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">46 (31.9%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">38 (39.2%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">84 (34.9%)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">&#x2003;2014</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">54 (37.5%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">28 (28.9%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">82 (34.0%)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">
                                <bold>Molecular subtype</bold> (n=240)</td>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">&#x2003;HER2</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">60 (42.0%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">34 (35.1%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">94 (39.2%)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">&#x2003;Luminal A</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">32 (22.4%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">21 (21.6%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">53 (22.1%)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">&#x2003;Luminal B</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">31 (21.7%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">25 (25.8%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">56 (23.3%)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">&#x2003;Triple negative</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">20 (14.0%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">17 (17.5%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">37 (15.4%)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">
                                <bold>Clinical stage</bold>
                            </td>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">&#x2003;Stage I</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">10 (6.9%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">4 (4.1%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">14 (5.8%)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">&#x2003;Stage II</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">65 (45.1%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">38 (39.2%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">103 (42.7%)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">&#x2003;Stage III</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">58 (40.3%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">42 (43.3%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">100 (41.5%)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">&#x2003;Stage IV</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">11 (7.6%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">13 (13.4%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">24 (10.0%)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">
                                <bold>Follow up</bold>
                            </td>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">&#x2003;Not dead</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">82 (56.9%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">48 (49.5%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">130 (53.9%)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">&#x2003;Dead</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">62 (43.1%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">49 (50.5%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">111 (46.1%)</td>
                        </tr>
                    </tbody>
                </table>
                <table-wrap-foot>
                    <p>NLR: Neutrophil-to-lymphocyte ratio.</p>
                </table-wrap-foot>
            </table-wrap>
            <p>When evaluating OS according to the year of follow-up, we observed that patients with NLR&#x2265;3 had a lower OS (
                <xref ref-type="fig" rid="f2">Figure 2A</xref>), compared to those who had an NLR&lt;3. This association was statistically significant (p&lt;0.001). When evaluating OS by molecular subtype, no statistically significant differences are observed (p=0.528) (
                <xref ref-type="fig" rid="f2">Figure 2B</xref>). While in the clinical stage (
                <xref ref-type="fig" rid="f2">Figure 2C</xref>), OS decreases in stage IV (p&lt;0.001). Furthermore, we observed that the age group &gt;55 years (
                <xref ref-type="fig" rid="f2">Figure 2D</xref>) presented a lower OS within the follow-up years (p=0.017), compared to patients up to 55 years of age.</p>
            <fig fig-type="figure" id="f2" orientation="portrait" position="float">
                <label>Figure 2. </label>
                <caption>
                    <title>Kaplan-Meier survival estimate for mortality in patients with breast cancer in a Latin-American hospital.</title>
                    <p>(A) According to NLR. (B) According to molecular subtype. (C) According to stage. (D) According to age.</p>
                </caption>
                <graphic id="gr2" orientation="portrait" position="float" xlink:href="https://f1000research-files.f1000.com/manuscripts/138206/65cd1729-5e55-428f-ac08-acd9f180e8fb_figure2.gif"/>
            </fig>
            <p>In the multivariate analysis, the NLR&#x2265;3 (p&lt;0.001) was a risk factor for mortality, adjusted for confounder variables of age and clinical stage. Additionally, age (p=0.016) and clinical stage IV (p=0.001) were also risk factors for mortality (
                <xref ref-type="table" rid="T3">Table 3</xref>).</p>
            <table-wrap id="T3" orientation="portrait" position="float">
                <label>Table 3. </label>
                <caption>
                    <title>Bivariate and multivariate analysis of OS.</title>
                </caption>
                <table content-type="article-table" frame="hsides">
                    <thead>
                        <tr>
                            <th align="left" colspan="1" rowspan="2" valign="top">Variable</th>
                            <th align="left" colspan="3" rowspan="1" valign="top">Bivariate analysis</th>
                            <th align="left" colspan="3" rowspan="1" valign="top">Multivariate an&#x00e1;lisis</th>
                        </tr>
                        <tr>
                            <th align="left" colspan="1" rowspan="1" valign="top">HR</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">CI (95%)</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">P</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">HR</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">CI (95%)</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">P</th>
                        </tr>
                    </thead>
                    <tbody>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">NLR&#x2265;3</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1.98</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1.36-2.89</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">&lt;0.001</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">2.00</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1.36-2.95</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">&lt;0.001</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="7" rowspan="1" valign="top">Molecular subtype</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">HER2</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1.42</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.82-2.46</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.208</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">-</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">-</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">-</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Luminal A</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Reference</td>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Luminal B</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1.38</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.76-2.54</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.285</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">-</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">-</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">-</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Triple negative</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1.56</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.83-2.92</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.165</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">-</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">-</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">-</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Clinical Stage I</td>
                            <td align="left" colspan="3" rowspan="1" valign="top">Reference</td>
                            <td align="left" colspan="3" rowspan="1" valign="top">Reference</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Clinical Stage II</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1.26</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.45-3.53</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.662</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1.89</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.66-5.42</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.236</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Clinical Stage III</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">2.00</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.72-5.52</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.184</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">2.63</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.94-7.36</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.066</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Clinical Stage IV</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">5.21</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1.77-15.33</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.003</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">6.78</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">2.28-20.20</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.001</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Age (55 years or older)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1.61</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1.09-2.38</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.018</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1.64</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1.10-2.44</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.016</td>
                        </tr>
                    </tbody>
                </table>
                <table-wrap-foot>
                    <p>HR: Hazard ratio; CI (95%): Confidence interval 95%.</p>
                </table-wrap-foot>
            </table-wrap>
        </sec>
        <sec id="sec10" sec-type="discussion">
            <title>Discussion</title>
            <p>In our study, we found that NLR&#x2265;3 (p&lt;0.001), age&gt;55 years (p=0.039), and clinical stage (p&lt;0.001), were associated with a lower OS. In the multivariate analysis, the factors significantly associated to a lower OS were NLR&#x2265;3, age&gt;55 years, and clinical stage IV. Although there have been international studies, we must consider that in all of them the population characteristics, such as risk factors, prevalence of infections, genetic susceptibility, and existing polymorphisms, are different from the Latin American context,
                <sup>
                    <xref ref-type="bibr" rid="ref9">9</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref17">17</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref18">18</xref>
                </sup> which makes it difficult to generalize its results in this context. This study is especially important given that a broad follow-up of 8 years for the NLR evaluation is a prognostic factor of OS in patients in a Latin American hospital. In this regard, this type of cancer is considered a health problem of high priority,
                <sup>
                    <xref ref-type="bibr" rid="ref19">19</xref>
                </sup> and the lack of resources requires cost-effective tools of easy access to orient the prognosis and need for treatment by a specialist.</p>
            <p>Regarding OS, we found that an NLR&gt;3 was related to a lower OS. Similar results were found by a Peruvian study, only in breast cancer with a triple-negative molecular subtype, while in our study we evidenced the use of this ratio in other molecular subtypes. Similar findings have been found in studies carried out in other regions of the world.
                <sup>
                    <xref ref-type="bibr" rid="ref20">20</xref>
                </sup> This is probably because a greater NLR reflects a greater number of neutrophils, whose high infiltration has been associated with the aggressiveness of the disease and resistance to therapy, in addition to promoting pro-cancerous factors and suppressing the cytotoxic activity of lymphocytes.
                <sup>
                    <xref ref-type="bibr" rid="ref21">21</xref>
                </sup>
                <sup>&#x2013;</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref23">23</xref>
                </sup> On the other hand, a decrease in lymphocyte count may decrease the effectiveness of the anti-tumoral immune response, which is why the combination of these conditions reflected in the NLR seems to be an excellent prognostic tool. Furthermore, it can be obtained through an accessible exam such as blood count, which is why its incorporation into the established prediction of risk justifies a larger study.
                <sup>
                    <xref ref-type="bibr" rid="ref24">24</xref>
                </sup>
            </p>
            <p>We observed that patients with NLR&#x2265;3 had a lower OS, however, as of the fifth follow-up year the survival curves in both NLR categories tended to approach each other. This is similar to other inflammatory indices such as the combination of the NLR with the lymphocyte platelet index (NLR/LPR) studied by Hirahara 
                <italic toggle="yes">et al</italic>.
                <sup>
                    <xref ref-type="bibr" rid="ref25">25</xref>
                </sup> They also observed that survival was greater as this rate decreased (p&lt;0.0001); however, from approximately the fifth follow-up year, we observed that survival functions were similar. This indicates that NLR or other hematological rates are likely not useful in predicting OS after a certain number of years. Likewise, in a Peruvian study,
                <sup>
                    <xref ref-type="bibr" rid="ref11">11</xref>
                </sup> the survival functions with an NLR&lt;2.5 and NLR&#x2265;2 were different during a 2-year follow-up in patients with triple negative breast cancer. It is probable that if it they had a longer follow-up, the behavior of the curves would have been similar to our study. Breast cancer mortality after 5 years could be high due to diverse factors foreign to what NLR might reflect, such as tumoral growth, comorbidities, and age-related functional impairment.</p>
            <p>We found that over half of patients had an NLR&#x2265;3, similar to that found in other studies.
                <sup>
                    <xref ref-type="bibr" rid="ref26">26</xref>
                </sup> On the other hand, the stages that were most frequently found during diagnosis were stages II and III, unlike the United States, where the most frequent stages were I and II.
                <sup>
                    <xref ref-type="bibr" rid="ref27">27</xref>
                </sup> This could reflect a late diagnosis, typical of developing countries with deficits in their health system.
                <sup>
                    <xref ref-type="bibr" rid="ref7">7</xref>
                </sup> Conversely, the average age at the time of diagnosis is comparable to that of other international reports.
                <sup>
                    <xref ref-type="bibr" rid="ref28">28</xref>
                </sup> The most frequent molecular subtype was HER2 with a 39.2%, unlike the Asiatic indigenous population, where the most frequent was the luminal A type (33%). This correlates with greater risk and worse results in cancer among the indigenous communities.
                <sup>
                    <xref ref-type="bibr" rid="ref29">29</xref>
                </sup>
            </p>
            <p>Furthermore, OS decreased noticeably in stage IV, probably since cancer diagnosis in advanced stages is more biologically aggressive and presents high recurrence rates.
                <sup>
                    <xref ref-type="bibr" rid="ref30">30</xref>
                </sup> Likewise, we found that NLR was associated with the disease staging, which could imply a confusing role of that variable when evaluating the predictive capacity of the NLR. Additionally, we found that the greater the age, the lower the OS. This finding is related to the study by Tao 
                <italic toggle="yes">et al.</italic>
                <sup>
                    <xref ref-type="bibr" rid="ref31">31</xref>
                </sup> where older patients with breast cancer had 17% greater mortality than younger patients. This age group also had a lower OS, since breast cancer at an older age may have late diagnosis and insufficient treatments.
                <sup>
                    <xref ref-type="bibr" rid="ref32">32</xref>
                </sup>
            </p>
            <p>By studying the entire population of a referral hospital that accepts patients from all over the country, these results could be generalized to the urban context of Peru and other cities in Latin America, since the sociodemographic characteristics and the environment where the study was made is similar to that of other Latin American cities. On the other hand, although there was a long follow-up of eight years, during this period there was no important change in the treatment that significantly affected the survival of the patients evaluated, so the results are still useful.</p>
            <sec id="sec11">
                <title>Study limitations</title>
                <p>Among the study&#x2019;s limitations, reporting bias likely exists due to the use of secondary sources such as medical records. Likewise, the patients&#x2019; treatment was not reported, a covariable that could influence OS. However, patients were treated in the same hospital, therefore it is probable that they received the same treatment regimen directed towards their type of cancer.</p>
            </sec>
        </sec>
        <sec id="sec12" sec-type="conclusions">
            <title>Conclusions</title>
            <p>We conclude that NLR&#x2265;3 is a risk factor for mortality, adjusted by age and clinical stage. Additionally, age and clinical stage IV could also be risk factors for mortality. A total of 59.3% of breast cancer patients had an NLR&#x2265;3, while the most frequently diagnosed stage was stage II with 42.74%, and the most frequent molecular subtype was HER2 with 39.2%.</p>
        </sec>
    </body>
    <back>
        <sec id="sec15" sec-type="data-availability">
            <title>Data availability</title>
            <sec id="sec16">
                <title>Underlying data</title>
                <p>Figshare: Underlying data for &#x2018;Neutrophil/lymphocyte ratio and overall survival in patients with breast cancer: a cohort study in a Latin-American hospital&#x2019;, 
                    <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.6084/m9.figshare.20419401.v2">https://doi.org/10.6084/m9.figshare.20419401.v2</ext-link>.
                    <sup>

                        <xref ref-type="bibr" rid="ref33">33</xref>
</sup>
                </p>
                <p>The project contains the following underlying data:
                    <list list-type="simple">
                        <list-item>
                            <p>DATASET - Breast cancer - Hospital Hipolito Unanue (main data; in.xls and.dta format)
</p>
                        </list-item>
                    </list>
                </p>
            </sec>
            <sec id="sec17">
                <title>Extended data</title>
                <p>Figshare: Underlying data for &#x2018;Neutrophil/lymphocyte ratio and overall survival in patients with breast cancer: a cohort study in a Latin-American hospital&#x2019;, 
                    <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.6084/m9.figshare.20419401.v2">https://doi.org/10.6084/m9.figshare.20419401.v2</ext-link>.
                    <sup>

                        <xref ref-type="bibr" rid="ref33">33</xref>
</sup>
                </p>
                <p>The project contains the following extended data:
                    <list list-type="bullet">
                        <list-item>
                            <label>&#x2022;</label>
                            <p>Data collection sheet in English</p>
                        </list-item>
                        <list-item>
                            <label>&#x2022;</label>
                            <p>Research protocol
</p>
                        </list-item>
                    </list>
                </p>
            </sec>
            <sec id="sec18">
                <title>Reporting guidelines</title>
                <p>Figshare: STROBE checklist for &#x2018;Neutrophil/lymphocyte ratio and overall survival in patients with breast cancer: a cohort study in a Latin-American hospital&#x2019;, 
                    <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.6084/m9.figshare.20419401.v2">https://doi.org/10.6084/m9.figshare.20419401.v2</ext-link>.
                    <sup>

                        <xref ref-type="bibr" rid="ref33">33</xref>
</sup>
                </p>
                <p>Data are available under the terms of the 
                    <ext-link ext-link-type="uri" xlink:href="https://creativecommons.org/licenses/by/4.0/">Creative Commons Attribution 4.0 International license</ext-link> (CC-BY 4.0).</p>
            </sec>
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    <sub-article article-type="reviewer-report" id="report180426">
        <front-stub>
            <article-id pub-id-type="doi">10.5256/f1000research.138206.r180426</article-id>
            <title-group>
                <article-title>Reviewer response for version 1</article-title>
            </title-group>
            <contrib-group>
                <contrib contrib-type="author">
                    <name>
                        <surname>Rundqvist</surname>
                        <given-names>Helene</given-names>
                    </name>
                    <xref ref-type="aff" rid="r180426a1">1</xref>
                    <role>Referee</role>
                    <uri content-type="orcid">https://orcid.org/0000-0002-5617-9076</uri>
                </contrib>
                <contrib contrib-type="author">
                    <name>
                        <surname>Rietz</surname>
                        <given-names>Marlene</given-names>
                    </name>
                    <xref ref-type="aff" rid="r180426a2">2</xref>
                    <role>Co-referee</role>
                </contrib>
                <aff id="r180426a1">
                    <label>1</label>Karolinska Institutet, Stockholm,, Sweden</aff>
                <aff id="r180426a2">
                    <label>2</label>Karolinska Institutet, Solna, Sweden</aff>
            </contrib-group>
            <author-notes>
                <fn fn-type="conflict">
                    <p>
                        <bold>Competing interests: </bold>No competing interests were disclosed.</p>
                </fn>
            </author-notes>
            <pub-date pub-type="epub">
                <day>23</day>
                <month>11</month>
                <year>2023</year>
            </pub-date>
            <permissions>
                <copyright-statement>Copyright: &#x00a9; 2023 Rundqvist H and Rietz M</copyright-statement>
                <copyright-year>2023</copyright-year>
                <license xlink:href="https://creativecommons.org/licenses/by/4.0/">
                    <license-p>This is an open access peer review report distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</license-p>
                </license>
            </permissions>
            <related-article ext-link-type="doi" id="relatedArticleReport180426" related-article-type="peer-reviewed-article" xlink:href="10.12688/f1000research.125858.1"/>
            <custom-meta-group>
                <custom-meta>
                    <meta-name>recommendation</meta-name>
                    <meta-value>approve-with-reservations</meta-value>
                </custom-meta>
            </custom-meta-group>
        </front-stub>
        <body>
            <p>
                <bold>Content </bold>
            </p>
            <p> This article presents retrospective findings regarding the association of the neutrophil/lymphocyte ratio (NLR) with overall survival (OS) in 241 female breast cancer patients in Peru. Kaplan-Meier statistics and cox proportional hazard models were used to estimate risk of overall survival. Findings suggest an association between NLR and OS.</p>
            <p> </p>
            <p> 
                <bold>General Comments </bold>
            </p>
            <p> The study population is of common interest as evidence from industrial countries may not be generalisable to cancer patients in developing countries. The study design is appropriate if the major revisions are addressed. There are sufficient details to allow replication. The statistical analysis and interpretation need to be revised, as there are several mistakes concerning data, results, and statistical testing. Data on participant characteristics are available but not the exposure variable. NLR and absolute neutrophil and lymphocyte counts should be added to the supplementary data file. Some conclusions are not properly drawn, and references need to be added to numerous statements.</p>
            <p> </p>
            <p> 
                <bold>Major Revisions</bold> 
                <list list-type="bullet">
                    <list-item>
                        <p>The study is a retrospective study, prospective needs to be changed to retrospective.</p>
                    </list-item>
                    <list-item>
                        <p>The article has already been shared on Research Gate, and it is not clearly stated that this publication has not been peer-reviewed. I would strongly suggest removing the article from research gate until the peer-review is completed (especially considering the major revision), or to clearly indicate that it has not been peer-reviewed. 
                            <list list-type="bullet">
                                <list-item>
                                    <p>
                                        <ext-link ext-link-type="uri" xlink:href="https://www.researchgate.net/publication/369519865_Neutrophillymphocyte_ratio_and_overall_survival_in_patients_with_breast_cancer_a_cohort_study_in_a_Latin-American_hospital">https://www.researchgate.net/publication/369519865_Neutrophillymphocyte_ratio_and_overall_survival_in_patients_with_breast_cancer_a_cohort_study_in_a_Latin-American_hospital</ext-link>
                                    </p>
                                </list-item>
                            </list> </p>
                    </list-item>
                    <list-item>
                        <p>The lack of statistical significance regarding tumor subtype is likely due to the number of groups and the small number of observations. Pathologically, it is expected that tumor subtypes affects both NLR and survival. Therefore, I strongly believe that subtypes need to be added to the multivariable model as a confounder, irrespectively of univariable statistical significance.</p>
                    </list-item>
                    <list-item>
                        <p>The publication is lacking sensitivity analyses: 
                            <list list-type="bullet">
                                <list-item>
                                    <p>I strongly encourage statistical comparison between baseline characteristics between groups, especially mean &#x00b1;SD of continuous age, and an addition of mean &#x00b1; SD of raw neutrophil and leukocyte counts.</p>
                                </list-item>
                                <list-item>
                                    <p>It could be of benefit to add a sensitivity analysis with removal of overall mortality events six months after baseline to remove mortality that the individuals were predisposed to before cancer diagnosis.</p>
                                </list-item>
                                <list-item>
                                    <p>Moreover, survival models for raw lymphocyte and neutrophil counts may be added.</p>
                                </list-item>
                            </list> </p>
                    </list-item>
                    <list-item>
                        <p>P-values in Figure 2 differ from p-values reported in text: 
                            <list list-type="bullet">
                                <list-item>
                                    <p>&#x00a0;Figure 2C and 2D both include p =0.017</p>
                                </list-item>
                                <list-item>
                                    <p>&#x201c;
                                        <italic>When evaluating OS by molecular subtype, no statistically significant differences are observed (p=0.528) (Figure 2B)</italic>. P-values differ from Figure 2B (p=0,444).</p>
                                </list-item>
                            </list> </p>
                    </list-item>
                    <list-item>
                        <p>I suggest statistical testing for p-values in figures and tables to be added to the legend text.</p>
                    </list-item>
                    <list-item>
                        <p>HRa at 68 for Stage 4 in abstract needs to be corrected.</p>
                    </list-item>
                    <list-item>
                        <p>As age is available as continuous variable, there is no reason to dichotomize the variable. Since the age range is quite high (26-85), a binary variable is not enough to adjust away differences of mortality risk across age. Moreover, the cut-off at 55 is not elaborated on in the method section.</p>
                    </list-item>
                    <list-item>
                        <p>In the text you state: 
                            <list list-type="bullet">
                                <list-item>
                                    <p>&#x201c;
                                        <italic>Total of 59.3% of breast cancer patients had an NLR&#x2265;3</italic>&#x201d;</p>
                                </list-item>
                                <list-item>
                                    <p>&#x201c;
                                        <italic>Furthermore, 144 (59.8%) patients had NLR&#x2265;3</italic>.&#x201d; &#x2013;</p>
                                </list-item>
                                <list-item>
                                    <p>&#x201c;
                                        <italic>I found that over half of patients had an NLR&#x2265;3, similar to that found in other studies.</italic>&#x201d;</p>
                                </list-item>
                            </list> </p>
                    </list-item>
                </list> However, in the Table 1 AND 2 the numbers are NLR&lt;3 = 144 and NLR&#x2265;3=97. This is a very critical mistake. Please correct throughout manuscript. 
                <list list-type="bullet">
                    <list-item>
                        <p>You state: &#x201c;
                            <italic>In our study, I found that NLR&#x2265;3 (p&lt;0.001), age&gt;55 years (p=0.039), and clinical stage (p&lt;0.001), were associated with a lower OS</italic>.&#x201d; &#x2013; Where does the p-value 0.039 come from? It is not reported in any table or figure, and it needs to be clarified what the p-values refer to.</p>
                    </list-item>
                    <list-item>
                        <p>Table 3 &#x2013; I understand the bivariate refers to models for NLR and one independent variable and the multivariate refers to models for NLR and significant confounders from univariable testing? Bivariate and multivariate needs to be changed to univariable and multivariable &#x00a0;as the ending -variate refers to response variables whereas -variable refers to independent variables, i.e. see 
                            <ext-link ext-link-type="uri" xlink:href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3518362/#:~:text=Statistically%20speaking%2C%20multivariate%20analysis%20refers,multiple%20independent%20or%20response%20variables.">link</ext-link>. Moreover, please add information about confounders included in multivariable models to the table legend.</p>
                    </list-item>
                    <list-item>
                        <p>Suggest to rephase &#x201c;We hope to find&#x201d; to &#x201c;We hypothesized that there is an association &#x2026;&#x201d; in introduction.</p>
                    </list-item>
                </list> 
                <bold>Minor Revisions</bold> 
                <list list-type="bullet">
                    <list-item>
                        <p>Please change term &#x201c;qualitative&#x201d; variables to &#x201c;categorical&#x201d; or &#x201c;discrete&#x201d; variables (see 
                            <ext-link ext-link-type="uri" xlink:href="https://www150.statcan.gc.ca/n1/edu/power-pouvoir/ch8/5214817-eng.htm">link</ext-link>)</p>
                    </list-item>
                </list> 
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                    <list-item>
                        <p>There are several parts that require references to previous literature. 
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                                <list-item>
                                    <p>&#x201e;While research exists on an international level that associates an elevated NLR with lower OS in patients with breast cancer, these were developed in populations with early-stage diagnosis, as opposed to countries with middle and low incomes, where a high proportion are diagnosed in advanced stages.&#x201c;</p>
                                </list-item>
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                                    <p>&#x201c;Similar results were found by a Peruvian study, only in breast cancer with a triple-negative molecular subtype, while in our study I evidenced the use of this ratio in other molecular subtypes.&#x201d;</p>
                                </list-item>
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                                    <p>&#x201e;On the other hand, a decrease in lymphocyte count may decrease the effectiveness of the anti-tumoral immune response&#x201c;</p>
                                </list-item>
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                                    <p>&#x201e;Breast cancer mortality after 5 years could be high due to diverse factors foreign to what NLR might reflect, such as tumoral growth, comorbidities, and age-related functional impairment&#x201c;</p>
                                </list-item>
                                <list-item>
                                    <p>&#x201e;The most frequent molecular subtype was HER2 with a 39.2%, unlike the Asiatic indigenous population, where the most frequent was the luminal A type (33%).&#x201d;</p>
                                </list-item>
                            </list> </p>
                    </list-item>
                    <list-item>
                        <p>Please elaborate on how excluded observations were handled, i.e., considering Table 1.</p>
                    </list-item>
                    <list-item>
                        <p>Please comment on the high incidence of HER2 in the population in the discussion. Does this reflect trends in South America, please refer to current literature.</p>
                    </list-item>
                </list>
            </p>
            <p>Is the work clearly and accurately presented and does it cite the current literature?</p>
            <p>Partly</p>
            <p>If applicable, is the statistical analysis and its interpretation appropriate?</p>
            <p>Partly</p>
            <p>Are all the source data underlying the results available to ensure full reproducibility?</p>
            <p>Partly</p>
            <p>Is the study design appropriate and is the work technically sound?</p>
            <p>Partly</p>
            <p>Are the conclusions drawn adequately supported by the results?</p>
            <p>Partly</p>
            <p>Are sufficient details of methods and analysis provided to allow replication by others?</p>
            <p>Partly</p>
            <p>Reviewer Expertise:</p>
            <p>Breast cancer, immunology, hypoxia, exercise</p>
            <p>We confirm that we have read this submission and believe that we have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however we have significant reservations, as outlined above.</p>
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    </sub-article>
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