<?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.146498.1</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>Pulmonary function in Thai patients with systemic sclerosis;&#x00a0;a single center 6-year retrospective study</article-title>
                <fn-group content-type="pub-status">
                    <fn>
                        <p>[version 1; peer review: 3 approved with reservations]</p>
                    </fn>
                </fn-group>
            </title-group>
            <contrib-group>
                <contrib contrib-type="author" corresp="yes">
                    <name>
                        <surname>Pirompanich</surname>
                        <given-names>Pattarin</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/">Methodology</role>
                    <role content-type="http://credit.niso.org/">Project Administration</role>
                    <role content-type="http://credit.niso.org/">Supervision</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Review &amp; Editing</role>
                    <uri content-type="orcid">https://orcid.org/0000-0003-0181-5394</uri>
                    <xref ref-type="corresp" rid="c1">a</xref>
                    <xref ref-type="aff" rid="a1">1</xref>
                </contrib>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>Sathitakorn</surname>
                        <given-names>Ornnicha</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Validation</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Review &amp; Editing</role>
                    <xref ref-type="aff" rid="a2">2</xref>
                </contrib>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>Sakulvorakitti</surname>
                        <given-names>Thitisak</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Data Curation</role>
                    <role content-type="http://credit.niso.org/">Investigation</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Original Draft Preparation</role>
                    <xref ref-type="aff" rid="a2">2</xref>
                </contrib>
                <aff id="a1">
                    <label>1</label>Division of Pulmonary and Critical Care Medicine, Department of Medicine, Faculty of Medicine, Thammasat University, Bangkok, Bangkok, 12120, Thailand</aff>
                <aff id="a2">
                    <label>2</label>Department of Medicine, Faculty of Medicine, Thammasat University, Bangkok, Bangkok, 12120, Thailand</aff>
            </contrib-group>
            <author-notes>
                <corresp id="c1">
                    <label>a</label>
                    <email xlink:href="mailto:pattarin@tu.ac.th">pattarin@tu.ac.th</email>
                </corresp>
                <fn fn-type="conflict">
                    <p>No competing interests were disclosed.</p>
                </fn>
            </author-notes>
            <pub-date pub-type="epub">
                <day>18</day>
                <month>4</month>
                <year>2024</year>
            </pub-date>
            <pub-date pub-type="collection">
                <year>2024</year>
            </pub-date>
            <volume>13</volume>
            <elocation-id>296</elocation-id>
            <history>
                <date date-type="accepted">
                    <day>1</day>
                    <month>4</month>
                    <year>2024</year>
                </date>
            </history>
            <permissions>
                <copyright-statement>Copyright: &#x00a9; 2024 Pirompanich P et al.</copyright-statement>
                <copyright-year>2024</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/13-296/pdf"/>
            <abstract>
                <sec>
                    <title>Background</title>
                    <p>Interstitial lung fibrosis is a major cause of internal organ involvement and the leading cause of death in patients with systemic sclerosis (SSc). This study aimed to demonstrate the characteristics of pulmonary function (PF) in Thai patients with SSc and the association between PF and body mass index (BMI) and anti-topoisomerase (anti-Scl70).</p>
                </sec>
                <sec>
                    <title>Methods</title>
                    <p>All patients diagnosed with SSc in our tertiary care teaching hospital database between 2016 and 2021 were reviewed. Clinical characteristics and PF were recorded and analyzed.</p>
                </sec>
                <sec>
                    <title>Results</title>
                    <p>Of 211 SSc patients, 128 patients who underwent the PF test were enrolled; 102 (79.7%) were female. The mean (SD) age was 54.0 (12.5) years. The mean (SD) forced expiratory volume in one second (FEV1) forced vital capacity (FVC) ratio was 0.8 (0.1). The mean (SD) % predicted values of FEV1, FVC, and diffusing capacity of the lungs for carbon monoxide (DLCO) were 76.3 (16.3), 69.1 (15.8), and 75.5 (22.8), respectively. A restrictive spirometry pattern (RSP), defined as FVC &lt; 80% predicted, was found in 78.8% of the patients. DLCO had a moderate positive linear correlation with FVC (r=0.50, p &lt;0.001) and a moderate negative linear correlation with BMI (r=-0.36, p &lt;0.001). However, there was no correlation between FVC and BMI. There was no statistical difference in demographic data or the presence of anti-Scl70 among patients with or without RSP.</p>
                </sec>
                <sec>
                    <title>Conclusions</title>
                    <p>RSP is common among Thai patients with SSc. Spirometry is a cost-effective screening tool for detecting SSc-related pulmonary involvement in resource-limited settings. However, the power of using demographic data and the presence of anti-Scl70 to determine the probability of pulmonary complications remains limited.</p>
                </sec>
            </abstract>
            <kwd-group kwd-group-type="author">
                <kwd>Systemic sclerosis</kwd>
                <kwd>Pulmonary function</kwd>
                <kwd>Interstitial lung disease</kwd>
                <kwd>ILD</kwd>
                <kwd>Thailand</kwd>
            </kwd-group>
            <funding-group>
                <award-group id="fund-1">
                    <funding-source>Faculty of Medicine, Thammasat University</funding-source>
                    <award-id>2-02/2565</award-id>
                </award-group>
                <funding-statement>This study was financially supported by the Faculty of Medicine, Thammasat University (funding number 2-02/2565).</funding-statement>
                <funding-statement>
                    <italic>The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.</italic>
                </funding-statement>
            </funding-group>
        </article-meta>
    </front>
    <body>
        <sec id="sec5">
            <title>Background</title>
            <p>Systemic sclerosis (SSc) is an autoimmune disease that results from microvascular damage, dysregulation of innate and adaptive immunity, and widespread fibrosis that affects multiple organs. While skin fibrosis is a key feature in patients with SSc, the clinical prognosis is determined by the severity of internal organ involvement.
                <sup>
                    <xref ref-type="bibr" rid="ref1">1</xref>
                </sup> The prevalence of SSc ranged from 38 to 341 cases per million, and the 5- and 10-year survival rates following diagnosis are 75% and 63%, respectively.
                <sup>
                    <xref ref-type="bibr" rid="ref2">2</xref>
                </sup>
            </p>
            <p>Major internal organ involvements in SSc include the pulmonary, cardiovascular, renal, and gastrointestinal systems. Notably, interstitial lung disease (ILD) has emerged as a primary complication during the initial stages in Thai patients and is a significant contributor to mortality.
                <sup>
                    <xref ref-type="bibr" rid="ref3">3</xref>
                </sup>
                <sup>&#x2013;</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref5">5</xref>
                </sup> The clinical presentations of SSc patients with ILD include dyspnea, non-productive cough, and fine crackles at the lung based on auscultation. The decline in forced vital capacity (FVC) was significantly higher in patients who had anti-topoisomerase autoantibody (anti-Scl70). In contrast, sex and age did not correlate with pulmonary function.
                <sup>
                    <xref ref-type="bibr" rid="ref3">3</xref>
                </sup>
            </p>
            <p>This study aimed to demonstrate the characteristics of pulmonary function in Thai patients with SSc and to explore the potential association between pulmonary function, body mass index (BMI), and the presence of anti-Scl70. The findings of this study may hold significant value in shaping management guidelines and provide insights for future studies on pulmonary complications in Thai patients with SSc.</p>
        </sec>
        <sec id="sec6" sec-type="methods">
            <title>Methods</title>
            <sec id="sec7">
                <title>Study design and setting</title>
                <p>This was a single-center, 6-year retrospective observational study conducted between January 2016 and December 2021. This study was approved by the Human Research Ethics Committee of the Faculty of Medicine, Thammasat University, Thailand (Project number MTU-EC-IM-1-177/65, Approval number 193/2022, Date of approval September 19, 2022), which was conducted in accordance with the Declaration of Helsinki. The informed consent was waived in view of the retrospective nature of the study. Patient data were sourced from our institutional database at a 650-bed tertiary care university hospital.</p>
            </sec>
            <sec id="sec8">
                <title>Patient selection and sample size</title>
                <p>The enrollment criteria included individuals aged &#x2265; 18 years diagnosed with systemic sclerosis. All patients fulfilled the 1980 classification criteria for SSc
                    <sup>
                        <xref ref-type="bibr" rid="ref6">6</xref>
                    </sup> and underwent a pulmonary function test (PFT) during the study period. Demographic data, presence of anti-Scl70, forced expiratory volume in one second (FEV1), FVC, and diffusing capacity of the lungs for carbon monoxide (DLCO) were recorded. In cases with multiple PFT results for a single patient, the earliest test conducted during the study period was employed to mitigate the impact of ongoing treatment and disease progression. This retrospective study included all eligible patients with available data, providing a complete representation of the entire population under investigation.</p>
            </sec>
            <sec id="sec9">
                <title>Outcomes</title>
                <p>The primary objective was to identify the characteristics of pulmonary function in patients with SSc. The secondary outcomes included comparing the pulmonary function based on the presence of anti-Scl70, demonstrating the association between body mass index (BMI), FVC, and DLCO, and distinguishing characteristics of the patients who had restrictive spirometry patterns, defined as FVC of less than 80% predicted.</p>
            </sec>
            <sec id="sec10">
                <title>Statistical analysis</title>
                <p>Normality was assessed using the Shapiro-Wilk normality test. Categorical variables were reported as counts and percentages, and continuous variables as means with standard deviations (SD) or medians with interquartile ranges (IQR). Differences in continuous variables were compared using Student&#x2019;s t-test or Mann-Whitney U test. Differences between separate groups of variables were compared using Fisher&#x2019;s test or the chi-square test. The relationship between parameters was evaluated using Pearson&#x2019;s correlation or Spearman&#x2019;s correlation. Cases with any missing data points were removed from the analysis. A two-sided P value of less than 0.05 was considered to indicate statistical significance for the outcomes. Analyses were performed using STATA software 17.0 (StataCorp LLC, College Station, TX, US).</p>
            </sec>
        </sec>
        <sec id="sec11" sec-type="results">
            <title>Results</title>
            <p>From a total of 211 SSc patients, 128 who underwent PFT were enrolled. Spirometry results were available for 118 (92.2%) patients, and DLCO results were available for 108 (84.4%) patients. The mean (SD) age of the patients was 54.0 (12.5) years, with 102 (79.7%) being female. The median (IQR) BMI for all patients was 21.7 (19.6-25.5) kg/m
                <sup>2</sup>, as detailed in 
                <xref ref-type="table" rid="T1">Table 1</xref>.
                <sup>
                    <xref ref-type="bibr" rid="ref9">9</xref>
                </sup>
            </p>
            <table-wrap id="T1" orientation="portrait" position="float">
                <label>Table 1. </label>
                <caption>
                    <title>Patient characteristics.</title>
                </caption>
                <table content-type="article-table" frame="hsides">
                    <thead>
                        <tr>
                            <th align="left" colspan="1" rowspan="1" valign="top">Characteristics</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">Overall (n = 128)</th>
                        </tr>
                    </thead>
                    <tbody>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Age &#x2013; mean (SD) years</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">54.0 (12.5)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Female &#x2013; n (%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">102 (79.7)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">BMI &#x2013; median (IQR) kg/m
                                <sup>2</sup>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">21.7 (19.6-25.5)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="2" rowspan="1" valign="top">
                                <bold>Presence of anti-topoisomerase &#x2013; n (%)</bold>
                            </td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">&#x2003;Positive</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">14 (10.9)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">&#x2003;Negative</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">10 (7.8)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">&#x2003;Not reported</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">104 (81.3)</td>
                        </tr>
                    </tbody>
                </table>
                <table-wrap-foot>
                    <p>BMI: body mass index; IQR: interquartile ranges; SD: standard deviations.</p>
                </table-wrap-foot>
            </table-wrap>
            <p>The primary outcome of the study revealed mean (SD) % predicted of FEV1, FVC, and DLCO as 76.3 (16.3), 69.1 (15.8), and 75.5 (22.8), respectively. The mean (SD) FEV1/FVC ratio was 0.8 (0.1). Notably, a restrictive spirometry pattern was predominant among the majority of the patients, accounting for 78.8% (93/118) of the study population. Further details regarding pulmonary function are presented in 
                <xref ref-type="table" rid="T2">Table 2</xref>.</p>
            <table-wrap id="T2" orientation="portrait" position="float">
                <label>Table 2. </label>
                <caption>
                    <title>Pulmonary function test of all participants.</title>
                </caption>
                <table content-type="article-table" frame="hsides">
                    <thead>
                        <tr>
                            <th align="left" colspan="1" rowspan="1" valign="top">Pulmonary function</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">Presence of spirometry (n = 118)</th>
                        </tr>
                    </thead>
                    <tbody>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">FVC &#x2013; mean (SD) L</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">2.1 (0.6)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">FVC &#x2013; mean (SD) % predicted</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">69.1 (15.8)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">FVC&lt;80% predicted &#x2013; n (%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">93 (78.8)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">FEV1 &#x2013; mean (SD) L</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">1.7 (0.5)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">FEV1 &#x2013; mean (SD) % predicted</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">76.3 (16.3)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">FEV1/FVC ratio &#x2013; mean (SD)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">0.8 (0.1)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">FEV1/FVC&gt;0.75 &#x2013; n (%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">102 (86.4)</td>
                        </tr>
                        <tr>
                            <td colspan="1" rowspan="1"/>
                            <td align="left" colspan="1" rowspan="1" valign="middle">
                                <bold>Presence of DLCO (n = 108)</bold>
                            </td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">DLCO &#x2013; mean (SD) % predicted</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">75.5 (22.8)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">DL adj &#x2013; mean (SD) % predicted</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">78.5 (24.3)</td>
                        </tr>
                    </tbody>
                </table>
                <table-wrap-foot>
                    <p>FVC: forced vital capacity; FEV1: forced expiratory volume in one second; DLCO: diffusing capacity for carbon monoxide; DLadj: diffusing capacity for carbon monoxide adjusted for hemoglobin content.</p>
                </table-wrap-foot>
            </table-wrap>
            <p>In the secondary outcome analysis, following the categorization of patients based on the presence of anti-Scl70, no statistical differences were observed in FVC, FEV1, FEV1/FVC, or DLCO (
                <xref ref-type="table" rid="T3">Table 3</xref>). DLCO demonstrated a moderate positive linear correlation with FVC (r=0.50, p&lt;0.001) and a moderate negative linear correlation with BMI (r=-0.36, p&lt;0.001) (
                <xref ref-type="fig" rid="f1">Figure 1</xref>). However, there was no correlation between FVC and BMI (r=-0.15, p-value=0.107).</p>
            <table-wrap id="T3" orientation="portrait" position="float">
                <label>Table 3. </label>
                <caption>
                    <title>Pulmonary function test stratified by anti-topoisomerase antibody.</title>
                </caption>
                <table content-type="article-table" frame="hsides">
                    <thead>
                        <tr>
                            <th align="left" colspan="1" rowspan="1" valign="top">Pulmonary function</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">Anti-topoisomerase positive (n=14)</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">Anti-topoisomerase negative (n=10)</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">P-value</th>
                        </tr>
                    </thead>
                    <tbody>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">FVC &#x2013; mean (SD) L</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">2.1 (0.5)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">1.9 (0.7)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.305</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">FVC &#x2013; mean (SD) % predicted</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">68.4 (16.5)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">71.4 (17.2)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.673</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">FVC&lt;80% predicted - n (%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">11 (78.6)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">7 (70.0)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">0.665</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">FEV1 &#x2013; n (%)</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;&gt;70% predicted</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">6 (54.6)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">2 (28.6)</td>
                            <td colspan="1" rowspan="1"/>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">&#x2003;60-69% predicted</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">3 (27.3)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">4 (57.1)</td>
                            <td colspan="1" rowspan="1"/>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">&#x2003;50-59% predicted</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">1 (9.1)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">0 (0.0)</td>
                            <td colspan="1" rowspan="1"/>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">&#x2003;35-49% predicted</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">1 (9.1)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">1 (14.3)</td>
                            <td colspan="1" rowspan="1"/>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">&#x2003;&lt;35% predicted</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">0 (0.0)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">0 (0.0)</td>
                            <td colspan="1" rowspan="1"/>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">FEV1 &#x2013; mean (SD) L</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">1.8 (0.4)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">1.5 (0.5)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.203</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">FEV1 &#x2013; mean (SD) % predicted</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">75.2 (18.0)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">72.0 (15.7)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.650</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">FEV1/FVC mean (SD)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">0.8 (0.1)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">0.8 (0.1)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.203</td>
                        </tr>
                    </tbody>
                </table>
                <table content-type="article-table" frame="hsides">
                    <thead>
                        <tr>
                            <th align="left" colspan="1" rowspan="1" valign="top"/>
                            <th align="left" colspan="1" rowspan="1" valign="top">Anti-topoisomerase positive (n = 11)</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">Anti-topoisomerase negative (n = 7)</th>
                            <th align="left" colspan="1" rowspan="1" valign="top"/>
                        </tr>
                    </thead>
                    <tbody>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">DLCO &#x2013; mean (SD) % predicted</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">64.5 (18.4)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">70.3 (16.8)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.509</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">DLCO &#x2013; n (%)</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="top">&#x2003;&gt;75% predicted &#x2013; n (%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">3 (27.3)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">4 (57.1)</td>
                            <td colspan="1" rowspan="1"/>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">&#x2003;61-75% predicted &#x2013; n (%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">3 (27.3)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">2 (28.6)</td>
                            <td colspan="1" rowspan="1"/>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">&#x2003;40-60% predicted &#x2013; n (%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">5 (45.5)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0 (0.0)</td>
                            <td colspan="1" rowspan="1"/>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">&#x2003;&lt;40% predicted &#x2013; n (%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0 (0.0)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1 (14.3)</td>
                            <td colspan="1" rowspan="1"/>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">DLCO adj &#x2013; mean (SD) % predicted</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">65.1 (19.0)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">73.7 (16.9)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.344</td>
                        </tr>
                    </tbody>
                </table>
                <table-wrap-foot>
                    <p>DLCO: diffusing capacity for carbon monoxide; DLadj: diffusing capacity for carbon monoxide adjusted for hemoglobin content; FEV1: forced expiratory volume in one second; FVC: forced vital capacity.</p>
                </table-wrap-foot>
            </table-wrap>
            <fig fig-type="figure" id="f1" orientation="portrait" position="float">
                <label>Figure 1. </label>
                <caption>
                    <title>The correlation between diffusing capacity for carbon monoxide (DLCO) and forced vital capacity (FVC) (left) and DLCO and body mass index (BMI) (right).</title>
                </caption>
                <graphic id="gr1" orientation="portrait" position="float" xlink:href="https://f1000research-files.f1000.com/manuscripts/160591/fe4ff9e4-575b-4ef4-939b-a52cc62963d2_figure1.gif"/>
            </fig>
            <p>Patient characteristics, including age, sex, BMI, and the presence of anti-topoisomerase, did not demonstrate significant differences between those with and without a restrictive spirometry pattern. Notably, the majority of the patients with decreased DLCO exhibited a restrictive spirometry pattern (
                <xref ref-type="table" rid="T4">Table 4</xref>).</p>
            <table-wrap id="T4" orientation="portrait" position="float">
                <label>Table 4. </label>
                <caption>
                    <title>Patient characteristics stratified by restrictive spirometry pattern.</title>
                </caption>
                <table content-type="article-table" frame="hsides">
                    <thead>
                        <tr>
                            <th align="left" colspan="1" rowspan="1" valign="top"/>
                            <th align="left" colspan="1" rowspan="1" valign="top">FVC&#x2265;80% predicted (n=25)</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">FVC&lt;80% predicted (n=93)</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">p-value</th>
                        </tr>
                    </thead>
                    <tbody>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Age &#x2013; mean (SD) years</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">53.6 (15.0)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">54.7 (12.1)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.688</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Sex &#x2013; n (%)</td>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.589</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">&#x2003;Female</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">21 (84.0)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">72 (77.4)</td>
                            <td colspan="1" rowspan="1"/>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">&#x2003;Male</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">4 (16.0)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">21 (22.6)</td>
                            <td colspan="1" rowspan="1"/>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">BMI &#x2013; median (IQR) kg/m
                                <sup>2</sup>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">21.7 (19.9-24.4)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">21.8 (19.6-25.8)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.489</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Anti-topoisomerase &#x2013; n (%)</td>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.665</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">&#x2003;Positive</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">3 (50.0)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">11 (61.1)</td>
                            <td colspan="1" rowspan="1"/>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">&#x2003;Negative</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">3 (50.0)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">7 (38.9)</td>
                            <td colspan="1" rowspan="1"/>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">DLCO &#x2013; n (%)</td>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.018</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">&#x2003;&gt;75% predicted</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">15 (83.3)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">33 (41.3)</td>
                            <td colspan="1" rowspan="1"/>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">&#x2003;61-75% predicted</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">2 (11.1)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">21 (26.3)</td>
                            <td colspan="1" rowspan="1"/>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">&#x2003;40-60% predicted</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1 (5.6)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">22 (27.5)</td>
                            <td colspan="1" rowspan="1"/>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">&#x2003;&lt;40% predicted</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0 (0.0)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">4 (5.0)</td>
                            <td colspan="1" rowspan="1"/>
                        </tr>
                    </tbody>
                </table>
                <table-wrap-foot>
                    <p>BMI: body mass index; DLCO: diffusing capacity for carbon monoxide; FVC: forced vital capacity.</p>
                </table-wrap-foot>
            </table-wrap>
        </sec>
        <sec id="sec12" sec-type="discussion">
            <title>Discussion</title>
            <p>In this study, the mean % predicted values of FVC and DLCO were 69.1 and 75.5, respectively. A substantial majority of the patients (78.8%) exhibited a restrictive spirometry pattern. These results are consistent with those of a prior study on ILD in Thai patients with SSc, where the % predicted FVC ranged from 71.8 to 77.6.
                <sup>
                    <xref ref-type="bibr" rid="ref7">7</xref>
                </sup> In that study, the mean % predicted FVC and incidence of ILD within 5 years from disease onset were 71.8 and 86% in patients with diffuse cutaneous SSc, and 77.6 and 54% in patients with limited cutaneous SSc, respectively.
                <sup>
                    <xref ref-type="bibr" rid="ref7">7</xref>
                </sup> These findings emphasize the impact of pulmonary involvement on SSc.</p>
            <p>However, the % predicted FVC in our study and the previously mentioned study appears to be lower than that reported in a previous large-scale study, The European Scleroderma Trials and Research group (EUSTAR) cohort,
                <sup>
                    <xref ref-type="bibr" rid="ref3">3</xref>
                </sup> where the mean % predicted FVC and DLCO in SSc patients were 93.5 and 68.9, respectively. This discrepancy may be attributed to the fact that the EUSTAR cohort assessed patients who presented within one year after the onset of Raynaud&#x2019;s phenomenon, the most common initial presentation, accounting for 59.5% of SSc cases.
                <sup>
                    <xref ref-type="bibr" rid="ref5">5</xref>
                </sup> Furthermore, the EUSTAR cohort&#x2019;s shorter disease duration compared to the referenced Thai study
                <sup>
                    <xref ref-type="bibr" rid="ref7">7</xref>
                </sup> might have contributed to the higher FVC values observed. These findings suggest a potential negative impact of disease duration on FVC, emphasizing the need for further studies to comprehensively explore this relationship.</p>
            <p>Our study revealed no association between demographic data and restrictive spirometry results in patients with SSc. This suggests that the manifestation of a restrictive spirometry pattern in patients with SSc may be influenced by disease-specific factors rather than by general demographic characteristics. Similarly, the presence of anti-topoisomerase antibody did not significantly affect pulmonary function, although this finding diverges from previous studies suggesting a negative association with pulmonary outcome.
                <sup>
                    <xref ref-type="bibr" rid="ref3">3</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref7">7</xref>
                </sup> However, it is important to note that a majority of our patients in this study demonstrated a restrictive spirometry pattern and only a small number of our patients had documented records of the presence of this antibody. These limitations may constrain our ability to thoroughly assess the impact of these factors on the pulmonary function. Notably, reduced chest wall compliance, potentially contributing to restrictive pulmonary defects, could also be found in SSc, which may have influenced our results.</p>
            <p>DLCO and FVC are the two most frequently used PFT for assessing the outcomes of SSc ILD.
                <sup>
                    <xref ref-type="bibr" rid="ref8">8</xref>
                </sup> SSc usually undergo regular DLCO and FVC. Our findings revealed a moderate linear correlation between DLCO and FVC, and nearly all patients with decreased DLCO exhibited a restrictive spirometry pattern. This finding suggests that spirometry can serve as an effective screening test for pulmonary involvement in SSc and is a cost-effective option, particularly in resource-limited settings.</p>
            <p>In this study, some essential medical history, particularly patient symptoms, previous treatments, disease duration, and co-existing organ involvement, were documented in diverse formats, posing challenges for analysis. Therefore, the earliest test conducted during the study period was employed to mitigate the impact of ongoing treatment and disease progression. However, this limits our ability to evaluate the relationship between pulmonary function and these factors. Further studies with pre-specified data collection of these factors may reveal new tools for the detection of pulmonary involvement.</p>
            <p>The strengths of our study are its considerable number of participants in a data-scarce field and being the only study that aims to explore pulmonary function exclusively in Thai patients with SSc. The effect of selective bias in the study is modest because most of our patients with SSc were screened with spirometry annually, regardless of patient symptoms.</p>
            <p>However, this study has some limitations. First, since SSc is a progressive disease, lack of disease duration data limited us from defining patient disease stage and severity. Second, the small number of documented anti-topoisomerase antibodies decreased our power to examine its relationship with patient pulmonary function. Third, our study did not capture data on the type of systemic sclerosis in all participants. This omission limits our ability to assess the potential influence of SSc type on FVC and DLCO. Lastly, our study did not include pulmonary hypertension (PH) assessments, thus limiting our ability to conclusively determine the extent to which PH contributed to the observed DLCO values.</p>
        </sec>
        <sec id="sec13" sec-type="conclusion">
            <title>Conclusion</title>
            <p>A restrictive spirometry pattern is common among Thai patients with SSc. Spirometry is a cost-effective screening tool for detecting SSc-related pulmonary involvement in resource-limited settings. However, the power of using demographic data and presence of anti-topoisomerase to determine the probability of pulmonary complications remains limited. Further studies are required to evaluate anti-topoisomerase antibody data, SSc type, and pulmonary hypertension assessment.</p>
        </sec>
        <sec id="sec14">
            <title>Ethics and consent</title>
            <p>Ethical approval was obtained from the Human Research Ethics Committee of Thammasat University (Faculty of Medicine), Thailand (Project number MTU-EC-IM-1-177/65, Approval number 193/2022, Date of approval September 19, 2022), and the study was conducted according to the Declaration of Helsinki. The informed consent was waived in view of the retrospective nature of the study.</p>
        </sec>
    </body>
    <back>
        <sec id="sec17" sec-type="data-availability">
            <title>Data availability</title>
            <p>Zenodo: Pulmonary function in Thai patients with systemic sclerosis data. 
                <ext-link ext-link-type="uri" xlink:href="https://zenodo.org/doi/10.5281/zenodo.10440509">https://zenodo.org/doi/10.5281/zenodo.10440509</ext-link>.
                <sup>

                    <xref ref-type="bibr" rid="ref9">9</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/legalcode">Creative Commons Attribution 4.0 International license</ext-link> (CC-BY 4.0).</p>
        </sec>
        <ack>
            <title>Acknowledgment</title>
            <p>The authors would like to express their gratitude to Thammasat University Hospital for providing the patient data and to Sam Ormond for reviewing the English language used in our manuscript.</p>
        </ack>
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                            <given-names>T</given-names>
                        </name>
</person-group>:
                    <data-title>Pulmonary function in Thai patients with systemic sclerosis data.</data-title>[Dataset].
                    <source>

                        <italic toggle="yes">Zenodo.</italic>
</source>
                    <year>2023</year>.
                    <pub-id pub-id-type="doi">10.5281/zenodo.10440510</pub-id>
                </mixed-citation>
            </ref>
        </ref-list>
    </back>
    <sub-article article-type="reviewer-report" id="report271795">
        <front-stub>
            <article-id pub-id-type="doi">10.5256/f1000research.160591.r271795</article-id>
            <title-group>
                <article-title>Reviewer response for version 1</article-title>
            </title-group>
            <contrib-group>
                <contrib contrib-type="author">
                    <name>
                        <surname>Tajarernmuang</surname>
                        <given-names>Pattraporn</given-names>
                    </name>
                    <xref ref-type="aff" rid="r271795a1">1</xref>
                    <role>Referee</role>
                    <uri content-type="orcid">https://orcid.org/0000-0003-4409-1832</uri>
                </contrib>
                <aff id="r271795a1">
                    <label>1</label>Division of Pulmonary, Critical Care, and Allergy, Department of Internal Medicine, Chiang Mai University, Chiang Mai, Thailand</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>5</month>
                <year>2024</year>
            </pub-date>
            <permissions>
                <copyright-statement>Copyright: &#x00a9; 2024 Tajarernmuang P</copyright-statement>
                <copyright-year>2024</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="relatedArticleReport271795" related-article-type="peer-reviewed-article" xlink:href="10.12688/f1000research.146498.1"/>
            <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>Thank you for the invitation to review the manuscript by Pirompanich et al. The authors presented a single-center retrospective study aiming to identify the clinical characteristics of pulmonary function in patients with systemic sclerosis. The minor concerns and suggestions for this study are as follows: 
                <list list-type="order">
                    <list-item>
                        <p>As we know, lung involvement in diffuse systemic sclerosis (SSc) is more common than in limited SSc. It would be beneficial to demonstrate the proportion of diffuse SSc and limited SSc in the patient characteristics.</p>
                    </list-item>
                    <list-item>
                        <p>There were 211 SSc patients, but only 128 (~60%) patients who had PFT results were enrolled. The possible reason for the unavailability of PFT results might be that the patients were too sick to perform the test. This selection bias could make the PFT results appear too favorable. The authors should mention this point in the limitations of the study.</p>
                    </list-item>
                    <list-item>
                        <p>The authors mentioned that limited chest wall compliance can cause restrictive pulmonary defects; however, lung imaging (e.g., HRCT) can help distinguish between chest wall and lung problems. Also, some patients with abnormal HRCT can have normal spirometry. I think the authors should clarify this point.</p>
                    </list-item>
                </list>
            </p>
            <p>Is the work clearly and accurately presented and does it cite the current literature?</p>
            <p>Yes</p>
            <p>If applicable, is the statistical analysis and its interpretation appropriate?</p>
            <p>Yes</p>
            <p>Are all the source data underlying the results available to ensure full reproducibility?</p>
            <p>No source data required</p>
            <p>Is the study design appropriate and is the work technically sound?</p>
            <p>Yes</p>
            <p>Are the conclusions drawn adequately supported by the results?</p>
            <p>Yes</p>
            <p>Are sufficient details of methods and analysis provided to allow replication by others?</p>
            <p>Partly</p>
            <p>Reviewer Expertise:</p>
            <p>pulmonary, interventional respirology, lung cancer, critical care</p>
            <p>I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above.</p>
        </body>
        <sub-article article-type="response" id="comment11655-271795">
            <front-stub>
                <contrib-group>
                    <contrib contrib-type="author">
                        <name>
                            <surname>Pirompanich</surname>
                            <given-names>Pattarin</given-names>
                        </name>
                        <aff>Medicine, Thammasat University, Klong Luang, Pathumthani, Thailand</aff>
                    </contrib>
                </contrib-group>
                <author-notes>
                    <fn fn-type="conflict">
                        <p>
                            <bold>Competing interests: </bold>None</p>
                    </fn>
                </author-notes>
                <pub-date pub-type="epub">
                    <day>27</day>
                    <month>5</month>
                    <year>2024</year>
                </pub-date>
            </front-stub>
            <body>
                <p>
                    <bold>Response to reviewer </bold>
                    <bold>3: </bold>
                </p>
                <p> Thank you very much for you kindly review. We really appreciate your response and revised our manuscript as you suggested.</p>
                <p> </p>
                <p> 
                    <bold>Point 1:</bold> As we know, lung involvement in diffuse systemic sclerosis (SSc) is more common than in limited SSc. It would be beneficial to demonstrate the proportion of diffuse SSc and limited SSc in the patient characteristics.</p>
                <p> 
                    <bold>Response 1: </bold>&#x00a0;We have acknowledged these on Discussion (Page 7, paragraph 2, line 8-10) and limitation (Page 8, paragraph 5, line 6-7).</p>
                <p> </p>
                <p> 
                    <bold>Point </bold>
                    <bold>2:</bold> There were 211 SSc patients, but only 128 (~60%) patients who had PFT results were enrolled. The possible reason for the unavailability of PFT results might be that the patients were too sick to perform the test. This selection bias could make the PFT results appear too favorable. The authors should mention this point in the limitations of the study.</p>
                <p> 
                    <bold>Response </bold>
                    <bold>2: </bold>&#x00a0;We have acknowledged these on limitation (Page 8, paragraph 5, line 10-12).</p>
                <p> </p>
                <p> 
                    <bold>Point </bold>
                    <bold>3:</bold> The authors mentioned that limited chest wall compliance can cause restrictive pulmonary defects; however, lung imaging (e.g., HRCT) can help distinguish between chest wall and lung problems. Also, some patients with abnormal HRCT can have normal spirometry. I think the authors should clarify this point.</p>
                <p> 
                    <bold>Response </bold>
                    <bold>3: </bold>&#x00a0;Thank you for the insightful comment regarding the role of chest wall compliance in restrictive lung disease.&#x00a0;We acknowledge that reduced chest wall compliance can be a contributing factor,&#x00a0;and ideally,&#x00a0;lung imaging techniques like HRCT would be incorporated to differentiate between restrictive etiologies. Unfortunately, due to limitations in our study design, we were unable to collect data on chest wall compliance. Therefore, we have decided to remove the sentence mentioning this factor from the manuscript.</p>
            </body>
        </sub-article>
    </sub-article>
    <sub-article article-type="reviewer-report" id="report271791">
        <front-stub>
            <article-id pub-id-type="doi">10.5256/f1000research.160591.r271791</article-id>
            <title-group>
                <article-title>Reviewer response for version 1</article-title>
            </title-group>
            <contrib-group>
                <contrib contrib-type="author">
                    <name>
                        <surname>Somboonviboon</surname>
                        <given-names>Dujrath</given-names>
                    </name>
                    <xref ref-type="aff" rid="r271791a1">1</xref>
                    <role>Referee</role>
                    <uri content-type="orcid">https://orcid.org/0000-0002-9309-1284</uri>
                </contrib>
                <aff id="r271791a1">
                    <label>1</label>Phramongkutklao Hospital, Bangkok, Thailand</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>20</day>
                <month>5</month>
                <year>2024</year>
            </pub-date>
            <permissions>
                <copyright-statement>Copyright: &#x00a9; 2024 Somboonviboon D</copyright-statement>
                <copyright-year>2024</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="relatedArticleReport271791" related-article-type="peer-reviewed-article" xlink:href="10.12688/f1000research.146498.1"/>
            <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>I appreciate the opportunity to review this article, which presents on pulmonary function in Thai systemic sclerosis patients, and I would like to offer a few comments and suggestions to further enhances its clarity and impact.</p>
            <p> </p>
            <p> Abstract 
                <list list-type="bullet">
                    <list-item>
                        <p>The authors did not compare spirometry to other interventions, particularly HRCT. Therefore, the conclusion regarding the cost-effectiveness of spirometry should be revised.</p>
                    </list-item>
                </list> Full manuscript&#x00a0;</p>
            <p> Background 
                <list list-type="bullet">
                    <list-item>
                        <p>The correlation between pulmonary function and SSc is understandable, but the authors should explain why they were interested in BMI. &#x00a0;</p>
                    </list-item>
                    <list-item>
                        <p>The authors mentioned the importance of ILD in SSc patients, however, this study did not include HRCT data, only pulmonary functions were recorded. Therefore, using &#x2018;pulmonary involvement&#x2019; would be more appropriate than ILD.</p>
                    </list-item>
                </list> Discussion 
                <list list-type="bullet">
                    <list-item>
                        <p>There are several confusing points in the discussion section, particularly when the authors compare the findings from this cohort to those of previous studies.</p>
                    </list-item>
                    <list-item>
                        <p>Please check the numbers, particularly regarding the data from the referenced papers.</p>
                    </list-item>
                    <list-item>
                        <p>The authors found that FVC in this cohort was lower than in the EUSTAR cohort and explained this by noting that EUSTAR cohort had shorter disease duration. However, a previous Thai cohort [Ref -1] demonstrated that a shorter duration of pulmonary fibrosis after onset also correlated with poorer outcome based on the longitudinal data analysis. Furthermore, the mean disease duration in the referenced Thai study [Ref - 2] was only 12.9 months. Therefore, this part should be revised.</p>
                    </list-item>
                    <list-item>
                        <p>As mentioned earlier, the authors did not investigate the cost-effectiveness of spirometry.</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>Yes</p>
            <p>Are all the source data underlying the results available to ensure full reproducibility?</p>
            <p>No source data required</p>
            <p>Is the study design appropriate and is the work technically sound?</p>
            <p>Yes</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>Internal Medicine and Pulmonology.</p>
            <p>I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above.</p>
        </body>
        <back>
            <ref-list>
                <title>References</title>
                <ref id="rep-ref-271791-1">
                    <label>1</label>
                    <mixed-citation publication-type="journal">
                        <person-group person-group-type="author"/>:
                        <article-title>Clinical characteristics and outcomes of 566 Thais with systemic sclerosis: A cohort study.</article-title>
                        <source>
                            <italic>Int J Rheum Dis</italic>
                        </source>.<year>2020</year>;<volume>23</volume>(<issue>7</issue>) :
                        <elocation-id>10.1111/1756-185X.13859</elocation-id>
                        <fpage>945</fpage>-<lpage>957</lpage>
                        <pub-id pub-id-type="pmid">32420701</pub-id>
                        <pub-id pub-id-type="doi">10.1111/1756-185X.13859</pub-id>
                    </mixed-citation>
                </ref>
                <ref id="rep-ref-271791-2">
                    <label>2</label>
                    <mixed-citation publication-type="journal">
                        <person-group person-group-type="author"/>:
                        <article-title>Incidence and predictors of interstitial lung disease (ILD) in Thai patients with early systemic sclerosis: Inception cohort study.</article-title>
                        <source>
                            <italic>Mod Rheumatol</italic>
                        </source>.<year>2016</year>;<volume>26</volume>(<issue>4</issue>) :
                        <elocation-id>10.3109/14397595.2015.1115455</elocation-id>
                        <fpage>588</fpage>-<lpage>93</lpage>
                        <pub-id pub-id-type="pmid">26561397</pub-id>
                        <pub-id pub-id-type="doi">10.3109/14397595.2015.1115455</pub-id>
                    </mixed-citation>
                </ref>
            </ref-list>
        </back>
        <sub-article article-type="response" id="comment11654-271791">
            <front-stub>
                <contrib-group>
                    <contrib contrib-type="author">
                        <name>
                            <surname>Pirompanich</surname>
                            <given-names>Pattarin</given-names>
                        </name>
                        <aff>Medicine, Thammasat University, Klong Luang, Pathumthani, Thailand</aff>
                    </contrib>
                </contrib-group>
                <author-notes>
                    <fn fn-type="conflict">
                        <p>
                            <bold>Competing interests: </bold>None</p>
                    </fn>
                </author-notes>
                <pub-date pub-type="epub">
                    <day>27</day>
                    <month>5</month>
                    <year>2024</year>
                </pub-date>
            </front-stub>
            <body>
                <p>Thank you very much for you kindly review. We really appreciate your response and revised our manuscript as you suggested.</p>
                <p> </p>
                <p> 
                    <bold>Abstract</bold>
                </p>
                <p> 
                    <bold>Point 1:</bold> The authors did not compare spirometry to other interventions, particularly HRCT. Therefore, the conclusion regarding the cost-effectiveness of spirometry should be revised.</p>
                <p> 
                    <bold>Response 1: </bold>&#x00a0;We have deleted this sentence from the abstract section and also in conclusion section.</p>
                <p> </p>
                <p> 
                    <bold>Background</bold>
                </p>
                <p> 
                    <bold>Point 1:</bold> The correlation between pulmonary function and SSc is understandable, but the authors should explain why they were interested in BMI. &#x00a0;</p>
                <p> 
                    <bold>Response 1: </bold>&#x00a0;BMI was included because it's a readily available measure of body composition that might influence lung function through various mechanisms. Understanding this relationship can provide insights into disease severity and potential risk factors for SSc patients.</p>
                <p> We have added this data on Background (Page 2, paragraph 2, line 8-9) (reference 6). 
                    <list list-type="bullet">
                        <list-item>
                            <p>Ishikawa C, Barbieri MA, Bettiol H, Bazo G, Ferraro AA, Vianna EO. Comparison of body composition parameters in the study of the association between body composition and pulmonary function. BMC Pulm Med. 2021;21(1):178.</p>
                        </list-item>
                    </list> 
                    <bold>Point </bold>
                    <bold>2:</bold> The authors mentioned the importance of ILD in SSc patients, however, this study did not include HRCT data, only pulmonary functions were recorded. Therefore, using &#x2018;pulmonary involvement&#x2019; would be more appropriate than ILD.</p>
                <p> 
                    <bold>Response </bold>
                    <bold>2: </bold>&#x00a0;We have changed accordingly.</p>
                <p> </p>
                <p> 
                    <bold>Discussion</bold>
                </p>
                <p> 
                    <bold>Point 1:</bold> There are several confusing points in the discussion section, particularly when the authors compare the findings from this cohort to those of previous studies.</p>
                <p> 
                    <bold>Response 1: </bold>&#x00a0;We have revised the data in the Discussion section to provide a clearer picture of the findings (Page 7, paragraph 1 and 2).</p>
                <p> </p>
                <p> 
                    <bold>Point </bold>
                    <bold>2:</bold> Please check the numbers, particularly regarding the data from the referenced papers.</p>
                <p> 
                    <bold>Response </bold>
                    <bold>2: </bold>&#x00a0;We have revised the data in the Discussion section to accurately reflect the information from the referenced papers (Page 7, paragraph 1 and 2).</p>
                <p> </p>
                <p> 
                    <bold>Point </bold>
                    <bold>3:</bold> The authors found that FVC in this cohort was lower than in the EUSTAR cohort and explained this by noting that EUSTAR cohort had shorter disease duration. However, a previous Thai cohort [Ref -1] demonstrated that a shorter duration of pulmonary fibrosis after onset also correlated with poorer outcome based on the longitudinal data analysis. Furthermore, the mean disease duration in the referenced Thai study [Ref - 2] was only 12.9 months. Therefore, this part should be revised.</p>
                <p> 
                    <bold>Response 3: </bold>&#x00a0;We have revised the data in the Discussion section to provide a clearer picture of the findings and to accurately reflect the information from the referenced papers (Page 7, paragraph 1 and 2).</p>
                <p> </p>
                <p> 
                    <bold>Point </bold>
                    <bold>4:</bold> As mentioned earlier, the authors did not investigate the cost-effectiveness of spirometry.</p>
                <p> 
                    <bold>Response </bold>
                    <bold>4: </bold>&#x00a0;We have deleted this sentence from the abstract section and also in conclusion section.</p>
            </body>
        </sub-article>
    </sub-article>
    <sub-article article-type="reviewer-report" id="report271788">
        <front-stub>
            <article-id pub-id-type="doi">10.5256/f1000research.160591.r271788</article-id>
            <title-group>
                <article-title>Reviewer response for version 1</article-title>
            </title-group>
            <contrib-group>
                <contrib contrib-type="author">
                    <name>
                        <surname>Foocharoen</surname>
                        <given-names>Chingching</given-names>
                    </name>
                    <xref ref-type="aff" rid="r271788a1">1</xref>
                    <role>Referee</role>
                </contrib>
                <aff id="r271788a1">
                    <label>1</label>Department of Medicine, Khon Kaen University, Nai Mueang, Khon Kaen, Thailand</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>10</day>
                <month>5</month>
                <year>2024</year>
            </pub-date>
            <permissions>
                <copyright-statement>Copyright: &#x00a9; 2024 Foocharoen C</copyright-statement>
                <copyright-year>2024</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="relatedArticleReport271788" related-article-type="peer-reviewed-article" xlink:href="10.12688/f1000research.146498.1"/>
            <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>The authors presented an association factors with pulmonary function in scleroderma. However, I believe there are some areas where additional details would strengthen the manuscript and provide a more convincing argument for the coexistence of both conditions. I have listed my points of concern below:</p>
            <p> Abstract 
                <list list-type="order">
                    <list-item>
                        <p>Mean BMI and the proportion of patient with positive for anti-Scl70 should be mentioned in abstract because they were endpoints of the study.</p>
                    </list-item>
                    <list-item>
                        <p>This study did not investigate the cost-effectiveness of spirometry. Please revise the conclusion in abstract section and also in conclusion section.</p>
                    </list-item>
                </list> Background 
                <list list-type="order">
                    <list-item>
                        <p>The authors should mention why BMI was in your interested to be an endpoint of the study. What is/are the rationales for defining the association between BMI and spirometry parameters?</p>
                    </list-item>
                </list> Methods 
                <list list-type="order">
                    <list-item>
                        <p>The diagnosis of systemic sclerosis is now using the 2013 ACR/EULAR Classification criteria not from 1980 ACR criteria.</p>
                    </list-item>
                    <list-item>
                        <p>128 out of 211 SSc patients underwent spirometry, so nearly 40% were not performed the spirometry. This may cause selection bias. Of those 40% who were not performed the test, they might be too tired to do the test or have difficulty to do the test for example air leak from mouth related to skin tightness of face, etc. Please clarify this point.</p>
                    </list-item>
                    <list-item>
                        <p>Spirometry parameters and BMI can dynamically change or fluctuate over the course of follow-up, but anti-Scl70 is still be stable. Please clarify when of the spirometry test as well as BMI was picked up for analysis.</p>
                    </list-item>
                    <list-item>
                        <p>The association between spirometry and anti-Scl70 might not be reliable and valid due to fluctuations during follow-up, as mentioned above.</p>
                    </list-item>
                    <list-item>
                        <p>The authors presented only a 10% positivity rate for anti-Scl70. From previous study of SSc in Thailand, the proportion of patients with anti-Scl70 was reported around 70-80% [Int J Rheum Dis. 2020 Jul;23(7):945-957.]. Why was the prevalence of anti-Scl70 in this study much lower than previous large cohort among Thais?</p>
                    </list-item>
                </list> Minor points 
                <list list-type="order">
                    <list-item>
                        <p>The term anti-topoisomerase I and anti-Scl70 were alternately used in the text. The authors should choose only 1 term and make it consistency to the whole manuscript.</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>Yes</p>
            <p>Are all the source data underlying the results available to ensure full reproducibility?</p>
            <p>No source data required</p>
            <p>Is the study design appropriate and is the work technically sound?</p>
            <p>Yes</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>Internal Medicine and Rheumatology</p>
            <p>I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above.</p>
        </body>
        <sub-article article-type="response" id="comment11653-271788">
            <front-stub>
                <contrib-group>
                    <contrib contrib-type="author">
                        <name>
                            <surname>Pirompanich</surname>
                            <given-names>Pattarin</given-names>
                        </name>
                        <aff>Medicine, Thammasat University, Klong Luang, Pathumthani, Thailand</aff>
                    </contrib>
                </contrib-group>
                <author-notes>
                    <fn fn-type="conflict">
                        <p>
                            <bold>Competing interests: </bold>None</p>
                    </fn>
                </author-notes>
                <pub-date pub-type="epub">
                    <day>27</day>
                    <month>5</month>
                    <year>2024</year>
                </pub-date>
            </front-stub>
            <body>
                <p>Thank you very much for you kindly review. We really appreciate your response and revised our manuscript as you suggested.</p>
                <p> </p>
                <p> 
                    <bold>Abstract</bold>
                </p>
                <p> 
                    <bold>Point 1:</bold> Mean BMI and the proportion of patient with positive for anti-Scl70 should be mentioned in abstract because they were endpoints of the study.</p>
                <p> 
                    <bold>Response 1: </bold>&#x00a0;We have added this data on Abstract (Page 2, Line 9-11).</p>
                <p> 
                    <bold>Point </bold>
                    <bold>2:</bold> This study did not investigate the cost-effectiveness of spirometry. Please revise the conclusion in abstract section and also in conclusion section.</p>
                <p> 
                    <bold>Response </bold>
                    <bold>2: </bold>&#x00a0;We have deleted this sentence from the abstract section and also in conclusion section.</p>
                <p> </p>
                <p> 
                    <bold>Background</bold>
                </p>
                <p> 
                    <bold>Point 1:</bold> The authors should mention why BMI was in your interested to be an endpoint of the study. What is/are the rationales for defining the association between BMI and spirometry parameters?</p>
                <p> 
                    <bold>Response 1: </bold>
                </p>
                <p> BMI was included because it's a readily available measure of body composition that might influence lung function through various mechanisms. Understanding this relationship can provide insights into disease severity and potential risk factors for SSc patients.</p>
                <p> We have added this data on Background (Page 2, paragraph 2, line 8-9) (reference 6). 
                    <list list-type="bullet">
                        <list-item>
                            <p>Ishikawa C, Barbieri MA, Bettiol H, Bazo G, Ferraro AA, Vianna EO. Comparison of body composition parameters in the study of the association between body composition and pulmonary function. BMC Pulm Med. 2021;21(1):178.</p>
                        </list-item>
                    </list> </p>
                <p> 
                    <bold>Methods</bold>
                </p>
                <p> 
                    <bold>Point 1:</bold> The diagnosis of systemic sclerosis is now using the 2013 ACR/EULAR Classification criteria not from 1980 ACR criteria.</p>
                <p> 
                    <bold>Response 1: </bold>&#x00a0;Thank you for your value suggestion. We have already revised (Page 3, paragraph 2, line 2-3).</p>
                <p> 
                    <bold>Point </bold>
                    <bold>2:</bold> 128 out of 211 SSc patients underwent spirometry, so nearly 40% were not performed the spirometry. This may cause selection bias. Of those 40% who were not performed the test, they might be too tired to do the test or have difficulty to do the test for example air leak from mouth related to skin tightness of face, etc. Please clarify this point.</p>
                <p> 
                    <bold>Response </bold>
                    <bold>2: </bold>&#x00a0;We have acknowledged these on limitation (Page 8, paragraph 5, line 10-12).</p>
                <p> </p>
                <p> 
                    <bold>Point </bold>
                    <bold>3:</bold> Spirometry parameters and BMI can dynamically change or fluctuate over the course of follow-up, but anti-Scl70 is still be stable. Please clarify when of the spirometry test as well as BMI was picked up for analysis.</p>
                <p> 
                    <bold>Response </bold>
                    <bold>3: </bold>&#x00a0;In cases with multiple PFT results for a single patient, the earliest test conducted during the study period was employed to mitigate the impact of ongoing treatment and disease progression. BMI was obtained at the time of the PFT was done.</p>
                <p> We have added this data in Methods (Page 3, paragraph 2, line 6-9).</p>
                <p> 
                    <bold>Point </bold>
                    <bold>4:</bold> The association between spirometry and anti-Scl70 might not be reliable and valid due to fluctuations during follow-up, as mentioned above.</p>
                <p> 
                    <bold>Response </bold>
                    <bold>4: </bold>&#x00a0;While spirometry parameters and BMI can fluctuate over time, anti-Scl-70 is known for its relative stability. To minimize the impact of ongoing treatment and disease progression on lung function analysis, this study used the earliest PFT result for each participant (Page 3, paragraph 2, line 6-7).</p>
                <p> However, this approach might not fully capture the potential influence of anti-Scl-70 levels on spirometry, as anti-Scl-70 is considered stable. Future longitudinal studies with repeated measurements of both anti-Scl-70 and spirometry parameters could provide a more comprehensive understanding of the interplay between these factors and their impact on lung function in SSc patients.</p>
                <p> We have acknowledged these on limitation (Page 8, paragraph 5, line 1-4).</p>
                <p> </p>
                <p> Further studies are required to evaluate comprehensive data on disease duration to gain a more understanding of the disease course and its impact on SSc patients.</p>
                <p> We have added this data in Conclusion (Page 8, line 4-5).</p>
                <p> 
                    <bold>Point </bold>
                    <bold>5:</bold> The authors presented only a 10% positivity rate for anti-Scl70. From previous study of SSc in Thailand, the proportion of patients with anti-Scl70 was reported around 70-80% [Int J Rheum Dis. 2020 Jul;23(7):945-957.]. Why was the prevalence of anti-Scl70 in this study much lower than previous large cohort among Thais?</p>
                <p> 
                    <bold>Response </bold>
                    <bold>5:</bold> &#x00a0;Among the analyzed samples, 14 patients (10.9%) were positive for anti-topoisomerase antibodies, while 10 patients (7.8%) were negative. However, anti-topoisomerase antibody status was unreported for a large portion of the study group (n=104, 81.3%) due to limitations in data availability. This high percentage of missing data&#x00a0;
                    <bold>precludes definitive conclusions about the overall prevalence of anti-Scl-70 in our cohort and hinders comparisons with previous studies that likely had more complete data.</bold>
                </p>
                <p> 
                    <bold>We </bold>have added this data in Results (Page 3, paragraph 1, line 2-4).</p>
                <p> </p>
                <p> 
                    <bold>Minor point</bold>
                </p>
                <p> 
                    <bold>Point </bold>
                    <bold>1:</bold> The term anti-topoisomerase I and anti-Scl70 were alternately used in the text. The authors should choose only 1 term and make it consistency to the whole manuscript.</p>
                <p> 
                    <bold>Response </bold>
                    <bold>1: </bold>&#x00a0;We revised throughout the manuscript.</p>
                <p> </p>
                <p> 
                    <bold>Additional revision: </bold>Because the interest of brevity, we delete some wordings in Abstract and the total wording is 262 words.</p>
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        </sub-article>
    </sub-article>
</article>
