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  <front>
    <journal-meta>
      <journal-id journal-id-type="nlm-ta">Arq Bras Cardiol</journal-id>
      <journal-id journal-id-type="publisher-id">abc</journal-id>
      <journal-title-group>
        <journal-title>Arquivos Brasileiros de Cardiologia</journal-title>
        <abbrev-journal-title abbrev-type="publisher">Arq. Bras. Cardiol.</abbrev-journal-title>
      </journal-title-group>
      <issn pub-type="ppub">0066-782X</issn>
      <issn pub-type="epub">1678-4170</issn>
      <publisher>
        <publisher-name>Sociedade Brasileira de Cardiologia - SBC</publisher-name>
      </publisher>
    </journal-meta>
    <article-meta>
      <article-id specific-use="scielo-v3" pub-id-type="publisher-id">rcpyMLYGBVQxPCjhWMyPRgx</article-id>
      <article-id specific-use="scielo-v2" pub-id-type="publisher-id">S0066-782X2022000200478</article-id>
      <article-id pub-id-type="publisher-id">abc.20200478</article-id>
      <article-id pub-id-type="doi">10.36660/abc.20200478</article-id>
      <article-categories>
        <subj-group subj-group-type="heading">
          <subject>Artigo Original</subject>
        </subj-group>
      </article-categories>
      <title-group>
        <article-title>Associa&#231;&#227;o entre a Gravidade da Doen&#231;a Arterial Coronariana e C&#226;ncer de Pulm&#227;o: Um Estudo Piloto Transversal</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <name>
            <surname>Sun</surname>
            <given-names>Mingzhuang</given-names>
          </name>
          <xref ref-type="fn" rid="fn_ast1">
            <sup>*</sup>
          </xref>
          <xref ref-type="aff" rid="aff1">
            <sup>1</sup>
          </xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Yang</surname>
            <given-names>Qian</given-names>
          </name>
          <xref ref-type="fn" rid="fn_ast1">
            <sup>*</sup>
          </xref>
          <xref ref-type="aff" rid="aff1">
            <sup>1</sup>
          </xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Li</surname>
            <given-names>Meng</given-names>
          </name>
          <xref ref-type="aff" rid="aff2">
            <sup>2</sup>
          </xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Jing</surname>
            <given-names>Jing</given-names>
          </name>
          <xref ref-type="aff" rid="aff1">
            <sup>1</sup>
          </xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Zhou</surname>
            <given-names>Hao</given-names>
          </name>
          <xref ref-type="aff" rid="aff1">
            <sup>1</sup>
          </xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Chen</surname>
            <given-names>Yundai</given-names>
          </name>
          <xref ref-type="aff" rid="aff1">
            <sup>1</sup>
          </xref>
        </contrib>
        <contrib contrib-type="author">
          <contrib-id contrib-id-type="orcid">0000-0002-8738-7417</contrib-id>
          <name>
            <surname>Hu</surname>
            <given-names>Shunying</given-names>
          </name>
          <xref ref-type="aff" rid="aff1">
            <sup>1</sup>
          </xref>
        </contrib>
      </contrib-group>
      <aff id="aff1">
        <label>1</label>
        <institution content-type="orgname">Chinese PLA General Hospital</institution>
        <institution content-type="orgdiv1">Department of Cardiology</institution>
        <addr-line>
          <named-content content-type="city">Beijing</named-content>
        </addr-line>
        <country country="CN">China</country>
        <institution content-type="original">Chinese PLA General Hospital - Department of Cardiology, Beijing &#8211; China</institution>
      </aff>
      <aff id="aff2">
        <label>2</label>
        <institution content-type="orgname">Chinese PLA General Hospital</institution>
        <institution content-type="orgdiv1">Department of Medical Records Management</institution>
        <addr-line>
          <named-content content-type="city">Beijing</named-content>
        </addr-line>
        <country country="CN">China</country>
        <institution content-type="original">Chinese PLA General Hospital - Department of Medical Records Management, Beijing &#8211; China</institution>
      </aff>
      <author-notes>
        <corresp id="c01"> Correspond&#234;ncia: Shunying Hu &#8226; Department of Cardiology, Chinese PLA General Hospital - 28 Fuxing Road Beijing 100853 &#8211; China E-mail: <email>hsylily@163.com</email> </corresp>
        <fn fn-type="other" id="fn_ast1">
          <label>*</label>
          <p>Os autores contribu&#237;ram igualmente para esse estudo</p>
        </fn>
        <fn fn-type="con">
          <p>Contribui&#231;&#227;o dos autores</p>
          <p>Concep&#231;&#227;o e desenho da pesquisa: Chen Y, Hu S; Obten&#231;&#227;o de dados: Sun M, Yang Q, Li M, Jing J, Zhou H, Hu S; An&#225;lise e interpreta&#231;&#227;o dos dados: Sun M, Yang Q, Zhou H, Hu S; An&#225;lise estat&#237;stica: Sun M, Hu S; Obten&#231;&#227;o de financiamento e Reda&#231;&#227;o do manuscrito: Hu S; Revis&#227;o cr&#237;tica do manuscrito quanto ao conte&#250;do intelectual importante: Sun M, Chen Y, Hu S.</p>
        </fn>
        <fn fn-type="conflict">
          <p>Potencial conflito de interesse</p>
          <p>N&#227;o h&#225; conflito com o presente artigo</p>
        </fn>
      </author-notes>
      <pub-date date-type="pub" publication-format="electronic">
        <day>07</day>
        <month>03</month>
        <year>2022</year>
      </pub-date>
      <pub-date date-type="collection" publication-format="electronic">
        <month>2</month>
        <year>2022</year>
      </pub-date>
      <volume>118</volume>
      <issue>2</issue>
      <fpage>478</fpage>
      <lpage>485</lpage>
      <history>
        <date date-type="received">
          <day>15</day>
          <month>05</month>
          <year>2020</year>
        </date>
        <date date-type="rev-recd">
          <day>29</day>
          <month>01</month>
          <year>2021</year>
        </date>
        <date date-type="accepted">
          <day>24</day>
          <month>02</month>
          <year>2021</year>
        </date>
      </history>
      <permissions>
        <license license-type="open-access" xlink:href="https://creativecommons.org/licenses/by/4.0/" xml:lang="en">
          <license-p> This is an Open Access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. </license-p>
        </license>
      </permissions>
      <abstract>
        <title>Resumo</title>
        <sec>
          <title>Fundamento</title>
          <p> A rela&#231;&#227;o direta entre a doen&#231;a arterial coronariana (DAC) e o c&#226;ncer de pulm&#227;o n&#227;o &#233; bem conhecida.</p>
        </sec>
        <sec>
          <title>Objetivo</title>
          <p> Investigar a associa&#231;&#227;o entre a gravidade anat&#244;mica da DAC e do c&#226;ncer de pulm&#227;o.</p>
        </sec>
        <sec>
          <title>M&#233;todos</title>
          <p> Trezentos pacientes, incluindo 75 rec&#233;m-diagnosticados com c&#226;ncer de pulm&#227;o e 225 pacientes correspondentes sem c&#226;ncer, foram submetidos &#224; angiografia coron&#225;ria durante a interna&#231;&#227;o, sem interven&#231;&#227;o coron&#225;ria percut&#226;nea (ICP) pr&#233;via nem enxerto de bypass da art&#233;ria coron&#225;ria (CABG). O escore SYNTAX foi utilizado para avaliar a gravidade da DAC. Uma pontua&#231;&#227;o alta no escore foi definida como &gt; 15 (o maior quartil do escore SYNTAX). O teste de tend&#234;ncia de Cochran-Armitage foi utilizado para verificar a distribui&#231;&#227;o dos escores dos pacientes. Uma an&#225;lise de regress&#227;o log&#237;stica foi utilizada para avaliar a associa&#231;&#227;o entre a gravidade da DAC e o c&#226;ncer de pulm&#227;o. Os valores de p foram estabelecidos quando o n&#237;vel de signific&#226;ncia era 5%.</p>
        </sec>
        <sec>
          <title>Resultados</title>
          <p> A tend&#234;ncia de distribui&#231;&#227;o dos escores SYNTAX dos pacientes por quartis foi diferente entre aqueles com c&#226;ncer de pulm&#227;o e controles (do quartil mais baixo ao mais alto: 20,0%; 20,0%; 24,0%; 36,0% vs. 26,7%; 26,2%; 25,8%; 21,3%; p=0,022). A pontua&#231;&#227;o no escore SYNTAX foi mais alta em pacientes com c&#226;ncer do que nos pacientes controle (36,0% vs. 21,3%, p=0,011).O maior quartil do escore demonstrou mais riscos de desenvolver c&#226;ncer de pulm&#227;o em compara&#231;&#227;o ao quartil mais baixo (OR: 2.250, IC95%: 1.077 a 4.699 ; <italic>P</italic> -trend= 0,016). Ap&#243;s ajustes, os pacientes no maior quartil do escore SYNTAX tinham mais risco de desenvolver c&#226;ncer de pulm&#227;o (OR: 2.1o49, IC95%: 1.008 a 4.584; <italic>P</italic> -trend= 0,028). Pacientes com escores SYNTAX alto (&gt; 15) tinham 1.985 mais chances de ter c&#226;ncer de pulm&#227;o (IC95%: 1.105&#8211;3.563, P= 0,022).</p>
        </sec>
        <sec>
          <title>Conclus&#227;o</title>
          <p> A gravidade anat&#244;mica da DAC est&#225; associada ao risco de c&#226;ncer de pulm&#227;o, o que indica que um rastreamento completo deste tipo de c&#226;ncer possa ser mais significativo entre pacientes com DAC.</p>
        </sec>
      </abstract>
      <kwd-group xml:lang="pt">
        <kwd>Doen&#231;a da Art&#233;ria Coronariana/complica&#231;&#245;es</kwd>
        <kwd>Neoplasias Pulmonares/complica&#231;&#245;es</kwd>
        <kwd>Angiografia Coron&#225;ria Percut&#226;nea/m&#233;todos</kwd>
        <kwd>&#205;ndice de Gravidade de Doen&#231;a</kwd>
        <kwd>Escore Sintax</kwd>
        <kwd>Interven&#231;&#227;o Coron&#225;ria Percut&#226;nea/m&#233;todos</kwd>
      </kwd-group>
      <funding-group>
        <award-group>
          <funding-source>National Natural Science Foundation of China</funding-source>
          <award-id>81770237</award-id>
        </award-group>
        <funding-statement>Fontes de financiamento: O presente estudo foi parcialmente financiado pela National Natural Science Foundation of China. (No. 81770237).</funding-statement>
      </funding-group>
      <counts>
        <fig-count count="2"/>
        <table-count count="6"/>
        <equation-count count="0"/>
        <ref-count count="29"/>
      </counts>
    </article-meta>
  </front>
  <body>
    <sec sec-type="intro">
      <title>Introdu&#231;&#227;o</title>
      <p>Doen&#231;as card&#237;acas e c&#226;nceres s&#227;o problemas de sa&#250;de cr&#237;ticos para seres humanos em todo o mundo.<sup><xref ref-type="bibr" rid="B1">1</xref> , <xref ref-type="bibr" rid="B2">2</xref></sup> A toxicidade cardiovascular induzida pela terapia antic&#226;ncer levou ao novo campo interdisciplinar da cardio-oncologia.<sup><xref ref-type="bibr" rid="B2">2</xref> - <xref ref-type="bibr" rid="B5">5</xref></sup> No momento, oncologistas e cardiologistas est&#227;o mais focados em doen&#231;as card&#237;acas relacionadas &#224; terapia antic&#226;ncer entre os sobreviventes de c&#226;ncer.<sup><xref ref-type="bibr" rid="B6">6</xref> , <xref ref-type="bibr" rid="B7">7</xref></sup> Alguns estudos demonstram que h&#225; uma rela&#231;&#227;o direta de intera&#231;&#227;o entre doen&#231;as card&#237;acas e c&#226;ncer.<sup><xref ref-type="bibr" rid="B8">8</xref></sup></p>
      <p>A doen&#231;a arterial coronariana (DAC) e o c&#226;ncer compartilham fatores de risco em comum, al&#233;m de mecanismos fisiopatol&#243;gicos.<sup><xref ref-type="bibr" rid="B9">9</xref> - <xref ref-type="bibr" rid="B11">11</xref></sup> H&#225; grandes evid&#234;ncias que mostram que pacientes com c&#226;ncer tinham mais riscos de desenvolver doen&#231;as cardiovasculares. Um estudo sueco mostrou que os c&#226;nceres est&#227;o associados ao maior risco de DAC; por&#233;m, neste caso, os pacientes tinham recebido tratamentos antic&#226;ncer, ent&#227;o o estudo n&#227;o p&#244;de demonstrar se havia ou n&#227;o uma rela&#231;&#227;o direta entre a DAC e o c&#226;ncer.<sup><xref ref-type="bibr" rid="B2">2</xref></sup> Este fato de a gravidade da CAD estar ou n&#227;o associada ao c&#226;ncer foi pouco reportado at&#233; o momento. &#201; essencial esclarecer se h&#225; uma rela&#231;&#227;o potencial direta entre a DAC e o c&#226;ncer para um melhor entendimento e administra&#231;&#227;o dessas duas doen&#231;as.</p>
      <p>O c&#226;ncer de pulm&#227;o &#233; o tipo de c&#226;ncer mais comum, e uma das principais causas de morte ligada ao c&#226;ncer.<sup><xref ref-type="bibr" rid="B12">12</xref></sup> Vale investigar a associa&#231;&#227;o entre a DAC e o c&#226;ncer de pulm&#227;o. Uma meta-an&#225;lise mostrou que o c&#226;ncer de pulm&#227;o esteve associado ao risco significativamente maior de DAC durante o acompanhamento em compara&#231;&#227;o aos pacientes sem c&#226;ncer de pulm&#227;o.<sup><xref ref-type="bibr" rid="B13">13</xref></sup> No estudo, os pacientes com c&#226;ncer de pulm&#227;o foram acompanhados por mais de um ano ap&#243;s serem diagnosticados, ent&#227;o havia mais chances de terem recebido tratamentos antic&#226;ncer, o que n&#227;o poderia excluir o efeito desses tratamentos na CAD. A rela&#231;&#227;o direta entre a DAC e o c&#226;ncer de pulm&#227;o n&#227;o &#233; bem compreendida at&#233; hoje. A hip&#243;tese de que a gravidade da CAD est&#225; associada a este tipo de c&#226;ncer n&#227;o foi reportada at&#233; o momento.</p>
      <p>Realizamos um estudo transversal para investigar a associa&#231;&#227;o direta entre a gravidade anat&#244;mica da CAD e o c&#226;ncer de pulm&#227;o. Todos os pacientes com este tipo de c&#226;ncer foram recentemente diagnosticados e n&#227;o receberam nenhum tratamento antic&#226;ncer. Os pacientes controle n&#227;o tinham c&#226;ncer de pulm&#227;o e foram inclu&#237;dos no estudo utilizando escores de propens&#227;o relacionados a pacientes com c&#226;ncer. Todos os pacientes do estudo foram submetidos &#224; angiografia coron&#225;ria (AGC) durante a hospitaliza&#231;&#227;o inicial. A gravidade anat&#244;mica da DAC foi avaliada utilizando o escore SYNTAX, com base nas AGC.<sup><xref ref-type="bibr" rid="B14">14</xref></sup> O objetivo deste estudo foi determinar se a gravidade anat&#244;mica da DAC est&#225; relacionada ao risco de c&#226;ncer de pulm&#227;o.</p>
    </sec>
    <sec sec-type="methods">
      <title>Pacientes e M&#233;todos</title>
      <sec>
        <title>Pacientes do estudo</title>
        <p>No Hospital Geral Chinese PLA, todos os dados dos pacientes internados est&#227;o armazenados no registro m&#233;dico, incluindo os angiogramas coron&#225;rios. Havia 173 pacientes com c&#226;ncer de pulm&#227;o (CID-10, c&#243;digo 34) e 49.968 sem nenhum tipo de c&#226;ncer que foram submetidos &#224; AGC (CID-9-MC, c&#243;digos 88,5; 88,55; 88,56 e 88,57) no departamento de cardiologia, de 1&#186; de janeiro de 2009 a 31 de julho de 2019.</p>
        <p>Os diagn&#243;sticos de c&#226;ncer de pulm&#227;o foram validados de acordo com o diagn&#243;stico patol&#243;gico. Dos 173 pacientes com c&#226;ncer de pulm&#227;o, 75 tinham sido rec&#233;m-diagnosticados sem receber nenhum tratamento antic&#226;ncer e foram inseridos no estudo, &#224; exce&#231;&#227;o de 31 com hist&#243;rico de tratamento antic&#226;ncer e 67 que j&#225; tinham sido submetidos &#224; interven&#231;&#227;o coron&#225;ria percut&#226;nea (ICP) ou enxerto de bypass da art&#233;ria coron&#225;ria (CABG). Dos 48.968 pacientes sem c&#226;ncer, 225 foram inclu&#237;dos como pacientes controle por meio de escores de propens&#227;o em rela&#231;&#227;o aos indiv&#237;duos com c&#226;ncer (raz&#227;o de 1:3), de acordo com idade, g&#234;nero, hist&#243;rico familiar de DAC, &#237;ndice de massa corporal (IMC), h&#225;bito de fumar, hipertens&#227;o, diabetes e hiperlipidemia. Nenhum dos pacientes inclu&#237;dos tinha hist&#243;rico de doen&#231;a do tecido conjuntivo ou outras doen&#231;as inflamat&#243;rias, nem de ICP ou CABG antes da hospitaliza&#231;&#227;o inicial. Um fluxograma do processo de inclus&#227;o dos pacientes &#233; demonstrado na <xref ref-type="fig" rid="f01">Figura 1</xref> .</p>
        <p>
          <fig id="f01">
            <label>Figura 1</label>
            <caption>
              <title>&#8211; <italic>Fluxograma dos pacientes do estudo.</italic></title>
            </caption>
            <graphic xlink:href=""/>
          </fig>
        </p>
        <p>Calculamos o tamanho da amostra utilizando o programa PASS. De acordo com par&#226;metros incluindo a = 0,05; &#946; = 0,20; OR= 2 e a raz&#227;o do caso-controle = 1:3, o tamanho da amostra do grupo com c&#226;ncer de pulm&#227;o foi de 74, e o do grupo dos indiv&#237;duos sem c&#226;ncer foi de 222. Neste estudo, inclu&#237;mos 300 pacientes (75 com c&#226;ncer de pulm&#227;o e 225 sem c&#226;ncer) que estavam de acordo com a exig&#234;ncia do tamanho da amostra.</p>
      </sec>
      <sec>
        <title>Escores SYNTAX da CAD com base na AGC</title>
        <p>A gravidade da CAD foi avaliada utilizando o algoritmo do escore SYNTAX (descrito na &#237;ntegra em outros estudos).<sup><xref ref-type="bibr" rid="B14">14</xref> , <xref ref-type="bibr" rid="B15">15</xref></sup> Todas as vari&#225;veis angiogr&#225;ficas relacionadas ao c&#225;lculo do escore SYNTAX foram computadas por dois cardiologistas intervencionistas experientes e cegos. Quando o escore de cada paciente foi diferente entre os dois cardiologistas, eles discutiam os angiogramas e chegavam a um escore comum. Os escores SYNTAX finais foram calculados por paciente e salvos em uma base de dados dedicada. O escore de 15 foi o maior quartil do estudo. Um escore baixo foi definido como &#8804;15, e um escore alto, como &gt;15. Na an&#225;lise de regress&#227;o log&#237;stica, definimos o escore &gt;15 como positivo.</p>
      </sec>
      <sec>
        <title>An&#225;lise estat&#237;stica</title>
        <p>As estat&#237;sticas descritivas est&#227;o apresentadas como taxas de frequ&#234;ncia e porcentagem para vari&#225;veis categ&#243;ricas, e m&#233;dia &#177; desvio padr&#227;o (DP) e medianas [intervalo interquartil (IIQ)] para vari&#225;veis cont&#237;nuas, de acordo com a normalidade dos dados. Avaliamos a normalidade dos dados com os testes de normalidade de Skewness e Kurtosis. Utilizamos o teste t para amostras independentes para comparar as m&#233;dias entre os grupos quando as vari&#225;veis foram distribu&#237;das normalmente. O teste U de Mann-Whitney n&#227;o-param&#233;trico foi usado para as vari&#225;veis cont&#237;nuas com distribui&#231;&#227;o normal, incluindo triglic&#233;rides, lipoprote&#237;na de baixa densidade, lipoprote&#237;na de alta densidade, glicemia de jejum, alanina aminotransferase, aspartato aminotransferase, creatinina s&#233;rica e &#225;cido &#250;rico. Os testes qui-quadrado ou exato de Fisher foram usados para analisar as diferen&#231;as nas medidas categ&#243;ricas.</p>
        <p>O escore SYNTAX foi dividido em quartis com base na distribui&#231;&#227;o do escore em todos os indiv&#237;duos do estudo, sendo que o primeiro quartil foi usado como refer&#234;ncia. Os valores do escore SYNTAX para os quartis 1, 2, 3 e 4 foram <italic>&lt;</italic> 4,0; 4,0&#8211;9,0; 9,0&#8211;15,0 e <italic>&gt;</italic> 15,0, respectivamente. O teste de tend&#234;ncia de Cochran-Armitage foi utilizado para analisar a distribui&#231;&#227;o dos escores dos pacientes. Avaliamos a rela&#231;&#227;o entre a gravidade da DAC (escore SYNTAX estratificado em quartis) e o c&#226;ncer de pulm&#227;o utilizando a an&#225;lise de regress&#227;o log&#237;stica, ajustando para fatores de risco comuns, incluindo idade, IMC, g&#234;nero e o h&#225;bito de fumar. A raz&#227;o de chances (OR) e os intervalos de confian&#231;a de 95% (IC) foram calculados. Os valores de p eram bicaudais, e consideramos como significativos quando 5%. As an&#225;lises estat&#237;sticas foram realizadas com o software SPSS, vers&#227;o 23 (SPSS, Inc. Chicago, IL, EUA) e com o SAS (SAS Institute, Cary, Carolina do Norte).</p>
      </sec>
    </sec>
    <sec sec-type="results">
      <title>Resultados</title>
      <sec>
        <title>Caracter&#237;sticas dos pacientes</title>
        <p>Os indiv&#237;duos do estudo faziam parte de uma popula&#231;&#227;o espec&#237;fica do hospital geral Chinese PLA. A idade m&#233;dia dos 300 pacientes do estudo era 63,5&#177;9,7 anos, e 70 (23,3%) eram do sexo feminino. Todos os 75 pacientes com c&#226;ncer de pulm&#227;o tinham evid&#234;ncias patol&#243;gicas da doen&#231;a; 69 (92%) foram diagnosticados com c&#226;ncer de pulm&#227;o de c&#233;lulas n&#227;o pequenas; e os outros 6 (8%), com c&#226;ncer de pulm&#227;o de c&#233;lulas pequenas. Quarenta e oito pacientes (75%) tinham c&#226;ncer est&#225;gio I ou II; 12 deles (16%), est&#225;gio III; e 4 (5,3%), est&#225;gio IV; n&#227;o foi poss&#237;vel confirmar o est&#225;gio da doen&#231;a para outros 11 pacientes (14,7%). Quatro pacientes (5,3%) apresentavam met&#225;stase. Os pacientes com c&#226;ncer de pulm&#227;o n&#227;o tinham recebido tratamentos antic&#226;ncer antes da hospitaliza&#231;&#227;o inicial.</p>
        <p>N&#227;o houve diferen&#231;a significativa para idade, g&#234;nero, h&#225;bito de fumar (estratificado como os que nunca fumaram e os que sempre fumaram), IMC, hist&#243;rico familiar de DAC, hipertens&#227;o, diabetes e hiperlipidemia entre pacientes com c&#226;ncer de pulm&#227;o e pacientes sem c&#226;ncer. Por&#233;m, o hist&#243;rico de fumar apresentou diferen&#231;as entre o grupo com c&#226;ncer de pulm&#227;o e os pacientes controle quando o hist&#243;rico de fumar foi estratificado como os que nunca fumaram, os que fumaram no passado e os que fumam atualmente, o que foi ajustado na an&#225;lise de regress&#227;o log&#237;stica. A fra&#231;&#227;o de eje&#231;&#227;o (FE) e os dados laboratoriais foram compar&#225;veis entre os pacientes com c&#226;ncer de pulm&#227;o e os controle ( <xref ref-type="table" rid="t1">Tabela 1</xref> ).</p>
        <p>
          <table-wrap id="t1">
            <label>Tabela 1</label>
            <caption>
              <title>&#8211; Caracter&#237;sticas dos pacientes</title>
            </caption>
            <table frame="hsides" rules="groups">
              <colgroup>
                <col/>
                <col/>
                <col/>
                <col/>
              </colgroup>
              <thead>
                <tr>
                  <th align="left">Caracter&#237;stica</th>
                  <th>Grupo c&#226;ncer de pulm&#227;o (n = 75)</th>
                  <th>Grupo sem c&#226;ncer (n = 225)</th>
                  <th>Valor de p</th>
                </tr>
              </thead>
              <tbody>
                <tr>
                  <td>
                    <list list-type="simple">
                      <list-item>
                        <p>
                          <bold>G&#234;nero, n (%)</bold>
                        </p>
                      </list-item>
                      <list-item>
                        <p>Masculino</p>
                      </list-item>
                      <list-item>
                        <p>Feminino</p>
                      </list-item>
                    </list>
                  </td>
                  <td align="center">
                    <list list-type="simple">
                      <list-item>
                        <p>59 (78,7%)</p>
                      </list-item>
                      <list-item>
                        <p>16 (21,3%)</p>
                      </list-item>
                    </list>
                  </td>
                  <td align="center">
                    <list list-type="simple">
                      <list-item>
                        <p>171 (76,0%)</p>
                      </list-item>
                      <list-item>
                        <p>54 (24,0%)</p>
                      </list-item>
                    </list>
                  </td>
                  <td align="center">0,636<sup>a</sup></td>
                </tr>
                <tr>
                  <td>
                    <list list-type="simple">
                      <list-item>
                        <p>
                          <bold>Idade (Anos)</bold>
                        </p>
                      </list-item>
                      <list-item>
                        <p>&lt;65</p>
                      </list-item>
                      <list-item>
                        <p>&#8805;65</p>
                      </list-item>
                    </list>
                  </td>
                  <td align="center">
                    <list list-type="simple">
                      <list-item>
                        <p>34(45,3%)</p>
                      </list-item>
                      <list-item>
                        <p>41(54,7%)</p>
                      </list-item>
                    </list>
                  </td>
                  <td align="center">
                    <list list-type="simple">
                      <list-item>
                        <p>120 (53,3%)</p>
                      </list-item>
                      <list-item>
                        <p>105 (46,7%)</p>
                      </list-item>
                    </list>
                  </td>
                  <td align="center">0,230<sup>a</sup></td>
                </tr>
                <tr>
                  <td>
                    <list list-type="simple">
                      <list-item>
                        <p>
                          <bold>IMC, n (%)</bold>
                        </p>
                      </list-item>
                      <list-item>
                        <p>&#8804;24</p>
                      </list-item>
                      <list-item>
                        <p>&gt;24</p>
                      </list-item>
                    </list>
                  </td>
                  <td align="center">
                    <list list-type="simple">
                      <list-item>
                        <p>25 (33,30%)</p>
                      </list-item>
                      <list-item>
                        <p>50 (66,70%)</p>
                      </list-item>
                    </list>
                  </td>
                  <td align="center">
                    <list list-type="simple">
                      <list-item>
                        <p>73 (32,4%)</p>
                      </list-item>
                      <list-item>
                        <p>152 (67,6%)</p>
                      </list-item>
                    </list>
                  </td>
                  <td align="center">0,887<sup>a</sup></td>
                </tr>
                <tr>
                  <td>
                    <list list-type="simple">
                      <list-item>
                        <p>
                          <bold>Fumar, n (%)</bold>
                        </p>
                      </list-item>
                      <list-item>
                        <p>Nunca fumaram</p>
                      </list-item>
                      <list-item>
                        <p>Sempre fumaram</p>
                      </list-item>
                    </list>
                  </td>
                  <td align="center">
                    <list list-type="simple">
                      <list-item>
                        <p>27(36,0%)</p>
                      </list-item>
                      <list-item>
                        <p>48(64,0%)</p>
                      </list-item>
                    </list>
                  </td>
                  <td align="center">
                    <list list-type="simple">
                      <list-item>
                        <p>97 (43,1%)</p>
                      </list-item>
                      <list-item>
                        <p>128 (56,9%)</p>
                      </list-item>
                    </list>
                  </td>
                  <td align="center">0,279<sup>a</sup></td>
                </tr>
                <tr>
                  <td>
                    <list list-type="simple">
                      <list-item>
                        <p>
                          <bold>Fumar, n (%)</bold>
                        </p>
                      </list-item>
                      <list-item>
                        <p>Nunca fumaram</p>
                      </list-item>
                      <list-item>
                        <p>J&#225; fumaram</p>
                      </list-item>
                      <list-item>
                        <p>Fumam atualmente</p>
                      </list-item>
                    </list>
                  </td>
                  <td align="center">
                    <list list-type="simple">
                      <list-item>
                        <p>27 (36,0%)</p>
                      </list-item>
                      <list-item>
                        <p>21 (28,0%)</p>
                      </list-item>
                      <list-item>
                        <p>27 (36,0%)</p>
                      </list-item>
                    </list>
                  </td>
                  <td align="center">
                    <list list-type="simple">
                      <list-item>
                        <p>97 (43,1%)</p>
                      </list-item>
                      <list-item>
                        <p>30 (13,3%)</p>
                      </list-item>
                      <list-item>
                        <p>98 (43,6%)</p>
                      </list-item>
                    </list>
                  </td>
                  <td align="center">0,014<sup>a</sup></td>
                </tr>
                <tr>
                  <td>
                    <list list-type="simple">
                      <list-item>
                        <p>
                          <bold>Hist&#243;rico familiar de DAC, n (%)</bold>
                        </p>
                      </list-item>
                      <list-item>
                        <p>N&#227;o</p>
                      </list-item>
                      <list-item>
                        <p>Sim</p>
                      </list-item>
                    </list>
                  </td>
                  <td align="center">
                    <list list-type="simple">
                      <list-item>
                        <p>69 (92,00%)</p>
                      </list-item>
                      <list-item>
                        <p>6 (8,00%)</p>
                      </list-item>
                    </list>
                  </td>
                  <td align="center">
                    <list list-type="simple">
                      <list-item>
                        <p>196 (87,1%)</p>
                      </list-item>
                      <list-item>
                        <p>29 (12,9%)</p>
                      </list-item>
                    </list>
                  </td>
                  <td align="center">0,253<sup>a</sup></td>
                </tr>
                <tr>
                  <td>
                    <list list-type="simple">
                      <list-item>
                        <p>
                          <bold>Hipertens&#227;o, n (%)</bold>
                        </p>
                      </list-item>
                      <list-item>
                        <p>N&#227;o</p>
                      </list-item>
                      <list-item>
                        <p>Sim</p>
                      </list-item>
                    </list>
                  </td>
                  <td align="center">
                    <list list-type="simple">
                      <list-item>
                        <p>29 (38,7%)</p>
                      </list-item>
                      <list-item>
                        <p>46 (61,3%)</p>
                      </list-item>
                    </list>
                  </td>
                  <td align="center">
                    <list list-type="simple">
                      <list-item>
                        <p>84 (37,3%)</p>
                      </list-item>
                      <list-item>
                        <p>141 (62,7%)</p>
                      </list-item>
                    </list>
                  </td>
                  <td align="center">0,836<sup>a</sup></td>
                </tr>
                <tr>
                  <td>
                    <list list-type="simple">
                      <list-item>
                        <p>
                          <bold>Diabetes, n (%)</bold>
                        </p>
                      </list-item>
                      <list-item>
                        <p>N&#227;o</p>
                      </list-item>
                      <list-item>
                        <p>Sim</p>
                      </list-item>
                    </list>
                  </td>
                  <td align="center">
                    <list list-type="simple">
                      <list-item>
                        <p>40 (53,3%)</p>
                      </list-item>
                      <list-item>
                        <p>35 (46,7%)</p>
                      </list-item>
                    </list>
                  </td>
                  <td align="center">
                    <list list-type="simple">
                      <list-item>
                        <p>131 (58,2%)</p>
                      </list-item>
                      <list-item>
                        <p>94 (41,8%)</p>
                      </list-item>
                    </list>
                  </td>
                  <td align="center">0,459<sup>a</sup></td>
                </tr>
                <tr>
                  <td>
                    <list list-type="simple">
                      <list-item>
                        <p>
                          <bold>Hiperlipidemia, n (%)</bold>
                        </p>
                      </list-item>
                      <list-item>
                        <p>N&#227;o</p>
                      </list-item>
                      <list-item>
                        <p>Sim</p>
                      </list-item>
                    </list>
                  </td>
                  <td align="center">
                    <list list-type="simple">
                      <list-item>
                        <p>25(33,3%)</p>
                      </list-item>
                      <list-item>
                        <p>50(66,7%)</p>
                      </list-item>
                    </list>
                  </td>
                  <td align="center">
                    <list list-type="simple">
                      <list-item>
                        <p>95 (42,2%)</p>
                      </list-item>
                      <list-item>
                        <p>130 (57,8%)</p>
                      </list-item>
                    </list>
                  </td>
                  <td align="center">0,174<sup>a</sup></td>
                </tr>
                <tr>
                  <td>
                    <list list-type="simple">
                      <list-item>
                        <p>
                          <bold>Fra&#231;&#227;o de Eje&#231;&#227;o (%), n (%)</bold>
                        </p>
                      </list-item>
                      <list-item>
                        <p>&lt;50</p>
                      </list-item>
                      <list-item>
                        <p>&#8805;50</p>
                      </list-item>
                    </list>
                  </td>
                  <td align="center">
                    <list list-type="simple">
                      <list-item>
                        <p>5(7,0%)</p>
                      </list-item>
                      <list-item>
                        <p>66(93,0%)</p>
                      </list-item>
                    </list>
                  </td>
                  <td align="center">
                    <list list-type="simple">
                      <list-item>
                        <p>21 (11,7%)</p>
                      </list-item>
                      <list-item>
                        <p>159 (88,3%)</p>
                      </list-item>
                    </list>
                  </td>
                  <td align="center">0,279<sup>a</sup></td>
                </tr>
                <tr>
                  <td>
                    <list list-type="simple">
                      <list-item>
                        <p>
                          <bold>Dados laboratoriais</bold>
                        </p>
                      </list-item>
                      <list-item>
                        <p>Colesterol total</p>
                      </list-item>
                      <list-item>
                        <p>Triglic&#233;rides, mmol/L LDL-C , mmol/L</p>
                      </list-item>
                      <list-item>
                        <p>HDL-C, mmol/L</p>
                      </list-item>
                      <list-item>
                        <p>Glicemia de jejum, mmol/L</p>
                      </list-item>
                      <list-item>
                        <p>ALT, U/L</p>
                      </list-item>
                      <list-item>
                        <p>AST, U/L</p>
                      </list-item>
                      <list-item>
                        <p>Albumina, g/L</p>
                      </list-item>
                      <list-item>
                        <p>Creatinina s&#233;rica, &#181;mol/L</p>
                      </list-item>
                      <list-item>
                        <p>&#193;cido &#250;rico, mmol/L</p>
                      </list-item>
                      <list-item>
                        <p>Hemoglobina, g/L</p>
                      </list-item>
                    </list>
                  </td>
                  <td align="center">
                    <list list-type="simple">
                      <list-item>
                        <p>4,035&#177;0,950</p>
                      </list-item>
                      <list-item>
                        <p>1,420 (IIQ [1,055&#8211;1,780])</p>
                      </list-item>
                      <list-item>
                        <p>2,545 (IIQ [1,838&#8211;3,195])</p>
                      </list-item>
                      <list-item>
                        <p>1,070 (IIQ [0,833&#8211;1,265])</p>
                      </list-item>
                      <list-item>
                        <p>5,820 (IIQ [4,980&#8211;7,720])</p>
                      </list-item>
                      <list-item>
                        <p>20,50 (IIQ [11,70&#8211;27,20])</p>
                      </list-item>
                      <list-item>
                        <p>17,20 (IIQ [13,70&#8211;25,10])</p>
                      </list-item>
                      <list-item>
                        <p>40,589&#177;4,056</p>
                      </list-item>
                      <list-item>
                        <p>76,70 (IIQ [66,80&#8211;84,80])</p>
                      </list-item>
                      <list-item>
                        <p>328,10 (IIQ [266,00&#8211;396,70])</p>
                      </list-item>
                      <list-item>
                        <p>135,76&#177;16,647</p>
                      </list-item>
                    </list>
                  </td>
                  <td align="center">
                    <list list-type="simple">
                      <list-item>
                        <p>4,029&#177;1,015</p>
                      </list-item>
                      <list-item>
                        <p>1,360 (IIQ [1,020&#8211;1,860])</p>
                      </list-item>
                      <list-item>
                        <p>2,340 (IIQ [1,850&#8211;3,058])</p>
                      </list-item>
                      <list-item>
                        <p>0,980 (IIQ [0,830&#8211;1185])</p>
                      </list-item>
                      <list-item>
                        <p>5,710 (IIQ [4,895&#8211;7,725])</p>
                      </list-item>
                      <list-item>
                        <p>21,40 (IIQ [15,20&#8211;30,70])</p>
                      </list-item>
                      <list-item>
                        <p>18,35 (IIQ [14,70&#8211;24,55])</p>
                      </list-item>
                      <list-item>
                        <p>40,640&#177;6,459</p>
                      </list-item>
                      <list-item>
                        <p>75,50 (IIQ [64,90&#8211;89,25])</p>
                      </list-item>
                      <list-item>
                        <p>324,95 (IIQ [268,28&#8211;358,13])</p>
                      </list-item>
                      <list-item>
                        <p>139,55&#177;16,059</p>
                      </list-item>
                    </list>
                  </td>
                  <td align="center">
                    <list list-type="simple">
                      <list-item>
                        <p>0,968<sup>b</sup></p>
                      </list-item>
                      <list-item>
                        <p>0,854<sup>c</sup></p>
                      </list-item>
                      <list-item>
                        <p>0,497<sup>c</sup></p>
                      </list-item>
                      <list-item>
                        <p>0,096<sup>c</sup></p>
                      </list-item>
                      <list-item>
                        <p>0,598<sup>c</sup></p>
                      </list-item>
                      <list-item>
                        <p>0,049<sup>c</sup></p>
                      </list-item>
                      <list-item>
                        <p>0,355<sup>c</sup></p>
                      </list-item>
                      <list-item>
                        <p>0,949<sup>b</sup></p>
                      </list-item>
                      <list-item>
                        <p>0.910<sup>c</sup></p>
                      </list-item>
                      <list-item>
                        <p>0,984<sup>c</sup></p>
                      </list-item>
                      <list-item>
                        <p>0,088<sup>b</sup></p>
                      </list-item>
                    </list>
                  </td>
                </tr>
                <tr>
                  <td>
                    <list list-type="simple">
                      <list-item>
                        <p>
                          <bold>Escore SYNTAX por quartis</bold>
                        </p>
                      </list-item>
                      <list-item>
                        <p>Quartil 1 (&#8804; 4.0)</p>
                      </list-item>
                      <list-item>
                        <p>Quartil 2 (4.0-9.0)</p>
                      </list-item>
                      <list-item>
                        <p>Quartil 3 (9.0-15.0)</p>
                      </list-item>
                      <list-item>
                        <p>Quartil 4 (&gt;15.0)</p>
                      </list-item>
                    </list>
                  </td>
                  <td align="center">
                    <list list-type="simple">
                      <list-item>
                        <p>15 (20,0%)</p>
                      </list-item>
                      <list-item>
                        <p>15 (20,0%)</p>
                      </list-item>
                      <list-item>
                        <p>18 (24,0%)</p>
                      </list-item>
                      <list-item>
                        <p>27 (36,0%)</p>
                      </list-item>
                    </list>
                  </td>
                  <td align="center">
                    <list list-type="simple">
                      <list-item>
                        <p>60 (26,7%)</p>
                      </list-item>
                      <list-item>
                        <p>59 (26,2%)</p>
                      </list-item>
                      <list-item>
                        <p>58 (25,8%)</p>
                      </list-item>
                      <list-item>
                        <p>48 (21,3%)</p>
                      </list-item>
                    </list>
                  </td>
                  <td align="center">0,022<sup>d</sup></td>
                </tr>
                <tr>
                  <td>
                    <list list-type="simple">
                      <list-item>
                        <p>
                          <bold>Escore SYNTAX por maior quartil</bold>
                        </p>
                      </list-item>
                      <list-item>
                        <p>Baixo (&#8804;15)</p>
                      </list-item>
                      <list-item>
                        <p>Alto (&gt;15)</p>
                      </list-item>
                    </list>
                  </td>
                  <td align="center">
                    <list list-type="simple">
                      <list-item>
                        <p>48 (64,0%)</p>
                      </list-item>
                      <list-item>
                        <p>27 (36,0%)</p>
                      </list-item>
                    </list>
                  </td>
                  <td align="center">
                    <list list-type="simple">
                      <list-item>
                        <p>177 (78,7%)</p>
                      </list-item>
                      <list-item>
                        <p>48 (21,3%)</p>
                      </list-item>
                    </list>
                  </td>
                  <td align="center">0,011<sup>a</sup></td>
                </tr>
              </tbody>
            </table>
            <table-wrap-foot>
              <fn id="TFN1">
                <p>
                  <italic>IMC: &#205;ndice de massa corporal; LDL: lipoprote&#237;na de baixa densidade; HDL-C: lipoprote&#237;na de alta densidade; ALT: alanina aminotransferase; AST: aspartato aminotransferase; IIQ: intervalo interquartil; Quartil 1-4: quartil mais baixo para o mais alto; <sup>a</sup>teste de qui-quadrado; <sup>b</sup>teste t de amostras independentes; <sup>c</sup>teste U de Mann-Whitney n&#227;o param&#233;trico; <sup>d</sup>teste de tend&#234;ncia de Cochran-Armitage.</italic>
                </p>
              </fn>
            </table-wrap-foot>
          </table-wrap>
        </p>
        <p>Os escores SYNTAX gerais variaram de 0 a 40, com mediana de 10 [IIQ (4,0&#8211;15,0)]. Em pacientes com c&#226;ncer de pulm&#227;o, havia 20,0%; 20,0%; 24,0% e 36,0% dos pacientes nos quartis mais baixo, m&#233;dio-inferior, m&#233;dio-superior e mais alto, respectivamente. Nos pacientes controle, a porcentagem de pacientes foi de 26,7%; 26,2%; 25,8% e 21,3% do quartil mais baixo ao mais alto, respectivamente. O teste de tend&#234;ncia de Cochran-Armitage mostrou que a tend&#234;ncia de distribui&#231;&#227;o dos escores dos pacientes diferiu entre pacientes com c&#226;ncer de pulm&#227;o e os controle, e o grupo com c&#226;ncer tinham uma porcentagem significativamente mais alta de pacientes com escores SYNTAX mais alto. De acordo com a defini&#231;&#227;o de escore SYNTAX alto e baixo pelo quartil mais alto (=15), assim como o escore como o valor de corte, 75 pacientes apresentaram escore alto (&gt;15) e 225 pacientes apresentaram escore baixo (&#8804;15). A taxa de escores altos foi maior em pacientes com c&#226;ncer de pulm&#227;o do que nos pacientes controle ( <xref ref-type="table" rid="t1">Tabela 1</xref> ).</p>
      </sec>
      <sec>
        <title>Associa&#231;&#227;o entre a gravidade da DAC e o c&#226;ncer de pulm&#227;o</title>
        <p>A associa&#231;&#227;o entre o escore SYNTAX e o c&#226;ncer de pulm&#227;o foi analisada por quartis do escore. Associa&#231;&#245;es significativas foram demonstradas entre o aumento do escore SYNTAX e o risco de desenvolver c&#226;ncer de pulm&#227;o (P-trend=0,016). Ap&#243;s ajustes diferentes por idade, IMC, g&#234;nero e o h&#225;bito de fumar (os que nunca fumaram, os que j&#225; fumaram e os que fumam atualmente), o escore esteve correlacionado ao risco de c&#226;ncer de pulm&#227;o (P-trend=0,024; P-trend=0,024; P-trend=0,029; P-trend=0,028, respectivamente). A raz&#227;o de chances para c&#226;ncer de pulm&#227;o (vs. o primeiro quartil do escore SYNTAX) foi 1.017 (IC95%: 0,457 a 2.265) para o segundo quartil, e 1.241 (IC95%: 0,572 a 2.693) para o terceiro quartil. O maior quartil do escore demonstrou risco significativamente maior de c&#226;ncer de pulm&#227;o em compara&#231;&#227;o ao quartil mais baixo (OR: 2.250; IC95%: 1.077 a 4.699). Ap&#243;s ajuste por idade, IMC, g&#234;nero e h&#225;bito de fumar, os pacientes no maior quartil do escore tinham mais chances de desenvolver c&#226;ncer de pulm&#227;o do que aqueles no quartil mais baixo do escore (OR: 2.149, IC95%: 1.008 a 4.584) ( <xref ref-type="table" rid="t2">Tabela 2</xref> ).</p>
        <p>
          <table-wrap id="t2">
            <label>Tabela 2</label>
            <caption>
              <title>&#8211; OR e IC95% para c&#226;ncer de pulm&#227;o por quartis do escore SYNTAX</title>
            </caption>
            <table frame="hsides" rules="groups">
              <colgroup>
                <col/>
                <col/>
                <col/>
                <col/>
                <col/>
                <col/>
              </colgroup>
              <thead>
                <tr>
                  <th align="left" rowspan="2" style="font-weight:normal"> </th>
                  <th colspan="5">Quartis do Escore SYNTAX</th>
                </tr>
                <tr>
                  <th>Quartil 1 (Refer&#234;ncia) (&#8804; 4,0)</th>
                  <th>Quartil 2 (4,0-9,0)</th>
                  <th>Quartil 3 (9,0-15,0)</th>
                  <th>Quartil 4 (&gt;15,0)</th>
                  <th><italic>P</italic> -trend<sup>*</sup></th>
                </tr>
              </thead>
              <tbody>
                <tr>
                  <td>Mediana do Escore Syntax</td>
                  <td align="center">2,0</td>
                  <td align="center">7,0</td>
                  <td align="center">12,0</td>
                  <td align="center">22,5</td>
                  <td> </td>
                </tr>
                <tr>
                  <td>N&#186; de c&#226;ncer de pulm&#227;o / controles (Total)</td>
                  <td align="center">15/60</td>
                  <td align="center">15/59</td>
                  <td align="center">18/58</td>
                  <td align="center">27/48</td>
                  <td> </td>
                </tr>
                <tr>
                  <td>Modelo 1: OR (IC95%)</td>
                  <td align="center">1</td>
                  <td align="center">1,017 (0,457-2,265)</td>
                  <td align="center">1,241 (0,572-2,693)</td>
                  <td align="center">2,250 (1,077-4,699)</td>
                  <td align="center">0,016</td>
                </tr>
                <tr>
                  <td>Modelo 2: OR (IC95%)</td>
                  <td align="center">1</td>
                  <td align="center">1,007 (0,451-2,245)</td>
                  <td align="center">1,233 (0,568-2,677)</td>
                  <td align="center">2,151 (1,021-4,530)</td>
                  <td align="center">0,024</td>
                </tr>
                <tr>
                  <td>Modelo 3: OR (IC95%)</td>
                  <td align="center">1</td>
                  <td align="center">1,011 (0,453-2,258)</td>
                  <td align="center">1,230 (0,566-2,672)</td>
                  <td align="center">2,165 (1,024-4,545)</td>
                  <td align="center">0,024</td>
                </tr>
                <tr>
                  <td>Modelo 4: OR (IC95%)</td>
                  <td align="center">1</td>
                  <td align="center">1,010 (0,452-2,255)</td>
                  <td align="center">1,215 (0,557-2,653)</td>
                  <td align="center">2,133(1,002-4,540)</td>
                  <td align="center">0,029</td>
                </tr>
                <tr>
                  <td>Modelo 5: OR (IC95%)</td>
                  <td align="center">1</td>
                  <td align="center">1,019 (0,455-2,279)</td>
                  <td align="center">1,227 (0,561-2,285)</td>
                  <td align="center">2,149 (1,008-4,584)</td>
                  <td align="center">0,028</td>
                </tr>
              </tbody>
            </table>
            <table-wrap-foot>
              <fn id="TFN2">
                <p>
                  <italic>Modelo 1: modelo bruto; Modelo 2: ajustado por idade; Modelo 3: ajustado por idade, IMC; Modelo 4: ajustado por idade, IMC, g&#234;nero; Modelo 5: ajustado por idade, IMC, g&#234;nero, h&#225;bito de fumar (nunca fumaram, j&#225; fumaram e fumam atualmente). Quartis 1-4: do mais baixo para o mais alto. *Teste de tend&#234;ncia com base em vari&#225;veis contendo valor mediano para cada quartil.</italic>
                </p>
              </fn>
            </table-wrap-foot>
          </table-wrap>
        </p>
        <p>Depois, a an&#225;lise de regress&#227;o log&#237;stica mostrou mais riscos de escore alto para c&#226;ncer de pulm&#227;o em compara&#231;&#227;o ao escore baixo. A an&#225;lise univariada de regress&#227;o log&#237;stica mostrou que o escore alto aumentou o risco de c&#226;ncer de pulm&#227;o em 2.074 vezes (IC95%: 1.174-3.665). Ajustando por idade, a an&#225;lise multivariada de regress&#227;o log&#237;stica mostrou que pacientes com escore alto tinham 1.994 mais chances de desenvolver c&#226;ncer de pulm&#227;o (IC95%: 1.119-3.551). Depois, ajustando por idade, IMC, g&#234;nero e h&#225;bito de fumar (os que nunca fumaram, os que j&#225; fumaram e os que fumam atualmente), pacientes com escore alto tinham 1.985 mais chances de desenvolver c&#226;ncer de pulm&#227;o (IC95%: 1.105-3.563) em compara&#231;&#227;o aos pacientes com escore baixo ( <xref ref-type="table" rid="t3">Tabela 3</xref> ).</p>
        <p>
          <table-wrap id="t3">
            <label>Tabela 3</label>
            <caption>
              <title>&#8211; OR e IC95% do escore SYNTAX alto para c&#226;ncer de pulm&#227;o</title>
            </caption>
            <table frame="hsides" rules="groups">
              <colgroup>
                <col/>
                <col/>
                <col/>
                <col/>
              </colgroup>
              <thead>
                <tr>
                  <th align="left">Modelo</th>
                  <th>OR</th>
                  <th>IC95%</th>
                  <th>Valor de p</th>
                </tr>
              </thead>
              <tbody>
                <tr>
                  <td>Modelo 1</td>
                  <td align="center">2,074</td>
                  <td align="center">1,174-3,665</td>
                  <td align="center">0,012</td>
                </tr>
                <tr>
                  <td>Modelo 2</td>
                  <td align="center">1,994</td>
                  <td align="center">1,119-3,551</td>
                  <td align="center">0,019</td>
                </tr>
                <tr>
                  <td>Modelo 3</td>
                  <td align="center">2,007</td>
                  <td align="center">1,123-3,588</td>
                  <td align="center">0,019</td>
                </tr>
                <tr>
                  <td>Modelo 4</td>
                  <td align="center">1,983</td>
                  <td align="center">1,105-3,558</td>
                  <td align="center">0,022</td>
                </tr>
                <tr>
                  <td>Modelo 5</td>
                  <td align="center">1,985</td>
                  <td align="center">1,105-3,563</td>
                  <td align="center">0,022</td>
                </tr>
              </tbody>
            </table>
            <table-wrap-foot>
              <fn id="TFN3">
                <p>
                  <italic>Modelo 1: modelo bruto; Modelo 2: ajustado por idade; Modelo 3: ajustado por idade, IMC; Modelo 4: ajustado por idade, IMC, g&#234;nero; Modelo 5: ajustado por idade, IMC, g&#234;nero, h&#225;bito de fumar (nunca fumaram, j&#225; fumaram e fumam atualmente).</italic>
                </p>
              </fn>
            </table-wrap-foot>
          </table-wrap>
        </p>
      </sec>
    </sec>
    <sec sec-type="discussion">
      <title>Discuss&#227;o</title>
      <p>Tanto a DAC quanto o c&#226;ncer de pulm&#227;o s&#227;o doen&#231;as que costumam afetar a sa&#250;de do ser humano. A doen&#231;a isqu&#234;mica do cora&#231;&#227;o padronizada por idade e o c&#226;ncer de pulm&#227;o foram a segunda e a terceira principais causas de anos potenciais perdidos de vida na China, em 2017.<sup><xref ref-type="bibr" rid="B16">16</xref></sup> A DAC raramente est&#225; associada ao c&#226;ncer de pulm&#227;o rec&#233;m-diagnosticado. At&#233; onde sabemos, este estudo &#233; o primeiro a investigar a associa&#231;&#227;o direta entre a gravidade anat&#244;mica da DAC e o c&#226;ncer de pulm&#227;o. Os resultados demonstraram que a gravidade da DAC est&#225; associada ao risco aumentado de c&#226;ncer de pulm&#227;o. Ap&#243;s diferentes ajustes, a DAC grave ainda esteve significativamente associada ao risco de c&#226;ncer de pulm&#227;o. Dada a import&#226;ncia da DAC e do c&#226;ncer de pulm&#227;o na sa&#250;de, os resultados deste estudo s&#227;o extremamente significativos.</p>
      <p>A cardio-oncologia &#233; um campo m&#233;dico emergente que foca na cardiotoxicidade induzida pelo tratamento antic&#226;ncer.<sup><xref ref-type="bibr" rid="B3">3</xref> , <xref ref-type="bibr" rid="B17">17</xref> , <xref ref-type="bibr" rid="B18">18</xref></sup> Por&#233;m, a rela&#231;&#227;o direta entre o c&#226;ncer e a doen&#231;a card&#237;aca ainda &#233; amplamente desconhecida. Neste estudo, avaliamos a gravidade da DAC utilizando o escore SYNTAX com base nos angiogramas coron&#225;rios de pacientes com c&#226;ncer de pulm&#227;o e controle. Os resultados demonstraram que havia associa&#231;&#245;es significativas entre o aumento do escore e o risco de c&#226;ncer de pulm&#227;o. A DAC e o c&#226;ncer de pulm&#227;o s&#227;o considerados grandes problemas de sa&#250;de p&#250;blica, crescendo em import&#226;ncia em termos globais. Os resultados deste estudo demonstraram que pacientes com DAC e escore SYNTAX alto tinham mais riscos de desenvolver c&#226;ncer de pulm&#227;o em compara&#231;&#227;o a pacientes com escore baixo, o que indica que &#233; importante fazer a triagem de c&#226;ncer de pulm&#227;o em pacientes com DAC grave. Deve-se mencionar que o fato de ambas as doen&#231;as estarem em uma rela&#231;&#227;o de causa e efeito, ou de que elas coexistam em um ambiente comum, n&#227;o p&#244;de ser determinado neste estudo. &#201; necess&#225;rio esclarecer melhor a corre&#231;&#227;o entre a DAC e o c&#226;ncer de pulm&#227;o em an&#225;lises futuras.</p>
      <p>O mecanismo por tr&#225;s da associa&#231;&#227;o entre a DAC e o c&#226;ncer n&#227;o &#233; bem conhecido, e isso pode se dever a v&#225;rios aspectos: fatores de risco compartilhados, status inflamat&#243;rio e vias fisiopatol&#243;gicas compartilhadas.<sup><xref ref-type="bibr" rid="B9">9</xref> , <xref ref-type="bibr" rid="B10">10</xref> , <xref ref-type="bibr" rid="B19">19</xref></sup> Este estudo mostra que a associa&#231;&#227;o entre a DAC e o c&#226;ncer de pulm&#227;o &#233; independente dos fatores de risco cardiovasculares e do c&#226;ncer, incluindo idade, IMC, g&#234;nero e o h&#225;bito de fumar. Muitos estudos demonstraram que a inflama&#231;&#227;o impacta a patog&#234;nese do c&#226;ncer e da DAC.<sup><xref ref-type="bibr" rid="B20">20</xref> - <xref ref-type="bibr" rid="B23">23</xref></sup> Dados cl&#237;nicos e experimentais t&#234;m papel essencial na inflama&#231;&#227;o da aterotrombose, incluindo a DAC.<sup><xref ref-type="bibr" rid="B24">24</xref></sup> As inflama&#231;&#245;es relacionadas ao c&#226;ncer podem estar presentes antes que ocorra uma mudan&#231;a maligna, o que pode levar ao desenvolvimento de tumores.<sup><xref ref-type="bibr" rid="B20">20</xref></sup> Foi reportado que ratos com tumores t&#234;m uma resposta pr&#243;-inflamat&#243;ria robusta aos tumores.<sup><xref ref-type="bibr" rid="B25">25</xref> , <xref ref-type="bibr" rid="B26">26</xref></sup> O estudo Canakinumab Anti-inflammatory Thrombosis Outcomes Study (CANTOS) mostra que o tratamento anti-inflamat&#243;rio com Canaquinumabe pode reduzir significativamente a incid&#234;ncia de c&#226;ncer de pulm&#227;o e sua mortalidade, al&#233;m de diminuir as taxas de eventos cardiovasculares recorrentes entre pacientes com infarto do mioc&#225;rdio pr&#233;vio.<sup><xref ref-type="bibr" rid="B24">24</xref> , <xref ref-type="bibr" rid="B27">27</xref></sup> Com base em estudos anteriores, &#233; razo&#225;vel inferir que a inflama&#231;&#227;o traz uma rela&#231;&#227;o consider&#225;vel entre a DAC e o c&#226;ncer de pulm&#227;o. A prote&#237;na C-reativa &#233; o marcador inflamat&#243;rio mais aceito.<sup><xref ref-type="bibr" rid="B21">21</xref> , <xref ref-type="bibr" rid="B28">28</xref></sup> No estudo retrospectivo, mais de um ter&#231;o dos pacientes n&#227;o tinham sido testados para a prote&#237;na C-reativa, ent&#227;o n&#227;o pudemos analisar o papel da inflama&#231;&#227;o na associa&#231;&#227;o entre a DAC e o c&#226;ncer de pulm&#227;o neste estudo. Vamos determinar o impacto da inflama&#231;&#227;o na rela&#231;&#227;o direta entre a DAC e o c&#226;ncer em novas an&#225;lises.</p>
      <p>Al&#233;m da inflama&#231;&#227;o, a doen&#231;a aterotromb&#243;tica e os neoplasmas compartilham muitas vias fisiopatol&#243;gicas, incluindo estresse oxidativo, apoptose, prolifera&#231;&#227;o celular e neoangiog&#234;nese.<sup><xref ref-type="bibr" rid="B19">19</xref></sup> As micropart&#237;culas de RNA foram um grande mecanismo fisiopatol&#243;gico entre o c&#226;ncer e a aterosclerose.<sup><xref ref-type="bibr" rid="B19">19</xref></sup> O receptor 1 de Lipoprote&#237;na de Baixa Densidade Oxidada (LOX-1) &#233; um receptor para lipoprote&#237;nas de baixa densidade oxidadas (ox-LDL) primariamente expressas nas c&#233;lulas endoteliais e nos &#243;rg&#227;os ricos em vasos sangu&#237;neos. O LOX-1 demonstrou ser efetivo durante o processo de aterog&#234;nese e tumorig&#234;nese, e poderia ser uma conex&#227;o importante entre essas duas doen&#231;as. Indiv&#237;duos com placas ateroscler&#243;ticas e altos n&#237;veis de express&#227;o de ox-LDL e LOX-1 parecem ser mais suscet&#237;veis a desenvolver c&#226;ncer.<sup><xref ref-type="bibr" rid="B29">29</xref></sup> A associa&#231;&#227;o entre DAC e c&#226;ncer pode ser explicada pela sobreposi&#231;&#227;o mec&#226;nica na fisiopatologia da aterog&#234;nese e tumorig&#234;nese; por&#233;m, mais estudos s&#227;o necess&#225;rios para esclarecer o mecanismo por tr&#225;s da associa&#231;&#227;o entre a DAC e o c&#226;ncer de pulm&#227;o.</p>
      <sec>
        <title>Limita&#231;&#245;es do estudo</title>
        <p>As limita&#231;&#245;es incluem, primeiramente, o pequeno tamanho da amostra. Resultados de uma popula&#231;&#227;o espec&#237;fica e pequena de pacientes de um &#250;nico centro da China podem ser divergentes. Por&#233;m, o vi&#233;s da inclus&#227;o no estudo foi minimizado com base na escolha dos pacientes. Inclu&#237;mos todos os pacientes eleg&#237;veis com c&#226;ncer de pulm&#227;o que n&#227;o tinham recebido tratamentos antic&#226;ncer, e inclu&#237;mos aleatoriamente os pacientes controle, com base nos escores de propens&#227;o, dentre 49.141 pacientes.</p>
        <p>Em segundo lugar, o mecanismo por tr&#225;s da associa&#231;&#227;o entre a DAC e o c&#226;ncer de pulm&#227;o n&#227;o ficou claro, embora a inflama&#231;&#227;o possa ter um papel importante para o risco aumentado de DAC grave e c&#226;ncer de pulm&#227;o. Vamos avaliar mais a associa&#231;&#227;o entre DAC e c&#226;ncer e o mecanismo por tr&#225;s disso com base no estudo piloto.</p>
      </sec>
    </sec>
    <sec sec-type="conclusions">
      <title>Conclus&#245;es</title>
      <p>Este estudo promove uma nova perspectiva na rela&#231;&#227;o entre a DAC e o c&#226;ncer de pulm&#227;o. Demonstramos que a gravidade anat&#244;mica da DAC e o c&#226;ncer de pulm&#227;o est&#227;o associados ao risco do c&#226;ncer de pulm&#227;o. Os resultados nos alertam de que possa valer a pena fazer uma triagem mais detalhada de c&#226;ncer de pulm&#227;o em pacientes com DAC grave. Vale ilustrar a conex&#227;o direta entre a DAC e o c&#226;ncer de pulm&#227;o e esclarecer o mecanismo deste processo no futuro, em ensaios cl&#237;nicos de larga escala e estudos b&#225;sicos.</p>
    </sec>
  </body>
  <back>
    <ack>
      <title>Agradecimentos</title>
      <p>Este estudo &#233; apoiado por recursos da National Natural Science Foundation of China (no. 81770237). Os financiadores n&#227;o tiveram nenhum papel no desenho do estudo, coleta e an&#225;lise de dados, decis&#227;o de publica&#231;&#227;o ou prepara&#231;&#227;o do manuscrito.</p>
    </ack>
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    <fn-group>
      <fn fn-type="other">
        <p>Vincula&#231;&#227;o acad&#234;mica</p>
        <p>Os pacientes do estudo do artigo fizeram parte da disserta&#231;&#227;o de mestrado apresentada por Qian Yang. Mingzhuang Sun investigou mais profundamente os pacientes e obteve novos resultados que foram inclu&#237;dos no artigo</p>
      </fn>
      <fn fn-type="other">
        <p>Aprova&#231;&#227;o &#233;tica e consentimento informado</p>
        <p>Este estudo foi aprovado pelo Comit&#234; de &#201;tica do Hospital Geral Chinese PLA sob o n&#250;mero de protocolo S2019-223-02. Todos os procedimentos envolvidos nesse estudo est&#227;o de acordo com a Declara&#231;&#227;o de Helsinki de 1975, atualizada em 2013. O consentimento informado foi obtido de todos os participantes inclu&#237;dos no estudo.</p>
      </fn>
    </fn-group>
    <fn-group>
      <fn fn-type="financial-disclosure" id="fn6">
        <p>Fontes de financiamento: O presente estudo foi parcialmente financiado pela National Natural Science Foundation of China. (No. 81770237).</p>
      </fn>
    </fn-group>
  </back>
  <sub-article article-type="translation" id="TRen" xml:lang="en">
    <front-stub>
      <article-categories>
        <subj-group subj-group-type="heading">
          <subject>Original Article</subject>
        </subj-group>
      </article-categories>
      <title-group>
        <article-title>Association between the Severity of Coronary Artery Disease and Lung Cancer: A Pilot Cross-Sectional Study</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <name>
            <surname>Sun</surname>
            <given-names>Mingzhuang</given-names>
          </name>
          <xref ref-type="fn" rid="fn_ast1001">
            <sup>*</sup>
          </xref>
          <xref ref-type="aff" rid="aff1001">
            <sup>1</sup>
          </xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Yang</surname>
            <given-names>Qian</given-names>
          </name>
          <xref ref-type="fn" rid="fn_ast1001">
            <sup>*</sup>
          </xref>
          <xref ref-type="aff" rid="aff1001">
            <sup>1</sup>
          </xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Li</surname>
            <given-names>Meng</given-names>
          </name>
          <xref ref-type="aff" rid="aff2001">
            <sup>2</sup>
          </xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Jing</surname>
            <given-names>Jing</given-names>
          </name>
          <xref ref-type="aff" rid="aff1001">
            <sup>1</sup>
          </xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Zhou</surname>
            <given-names>Hao</given-names>
          </name>
          <xref ref-type="aff" rid="aff1001">
            <sup>1</sup>
          </xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Chen</surname>
            <given-names>Yundai</given-names>
          </name>
          <xref ref-type="aff" rid="aff1001">
            <sup>1</sup>
          </xref>
        </contrib>
        <contrib contrib-type="author">
          <contrib-id contrib-id-type="orcid">0000-0002-8738-7417</contrib-id>
          <name>
            <surname>Hu</surname>
            <given-names>Shunying</given-names>
          </name>
          <xref ref-type="aff" rid="aff1001">
            <sup>1</sup>
          </xref>
        </contrib>
      </contrib-group>
      <aff id="aff1001">
        <label>1</label>
        <country country="CN">China</country>
        <institution content-type="original">Chinese PLA General Hospital - Department of Cardiology, Beijing &#8211; China</institution>
      </aff>
      <aff id="aff2001">
        <label>2</label>
        <country country="CN">China</country>
        <institution content-type="original">Chinese PLA General Hospital - Department of Medical Records Management, Beijing &#8211; China</institution>
      </aff>
      <author-notes>
        <corresp id="c01001">Mailing Address: Shunying Hu &#8226; Department of Cardiology, Chinese PLA General Hospital - 28 Fuxing Road Beijing 100853 &#8211; China E-mail: hsylily@163.com</corresp>
        <fn fn-type="other" id="fn_ast1001">
          <label>*</label>
          <p>The authors equally contributed to this study</p>
        </fn>
        <fn fn-type="con">
          <p>Author Contributions</p>
          <p>Conception and design of the research: Chen Y, Hu S; Acquisition of data: Sun M, Yang Q, Li M, Jing J, Zhou H, Hu S; Analysis and interpretation of the data: Sun M, Yang Q, Zhou H, Hu S; Statistical analysis: Sun M, Hu S; Obtaining financing and Writing of the manuscript: Hu S; Critical revision of the manuscript for intellectual content: Sun M, Chen Y, Hu S.</p>
        </fn>
        <fn fn-type="conflict">
          <p>Potential Conflict of Interest</p>
          <p>No potential conflict of interest relevant to this article was reported.</p>
        </fn>
      </author-notes>
      <abstract>
        <title>Abstract</title>
        <sec>
          <title>Background</title>
          <p>The direct relationship between coronary artery disease (CAD) and lung cancer is not well known.</p>
        </sec>
        <sec>
          <title>Objective</title>
          <p>To investigate the association between the anatomical severity of CAD and lung cancer.</p>
        </sec>
        <sec>
          <title>Methods</title>
          <p>Three-hundred study patients, including 75 recently diagnosed lung cancer patients and 225 matched non-cancer patients, underwent coronary angiography during hospitalization without previous percutaneous coronary intervention (PCI) or coronary artery bypass grafting (CABG). The SYNTAX score (SXscore) was used to assess the severity of CAD. A high SXscore (SXhigh) grade was defined as SXscore &gt; 15 (the highest quartile of the SXscore). The Cochran-Armitage test for trend was used to assess the distribution of patients&#8217; SXscores. Logistic regression analysis was used to assess the association between the severity of CAD and lung cancer. P-values were set when significance level was 5%.</p>
        </sec>
        <sec>
          <title>Results</title>
          <p>The distribution trend of patients&#8217; SXscore by quartiles was different between lung cancer patients and control patients (from the lowest to the highest quartile: 20.0%, 20.0%, 24.0%, 36.0% vs. 26.7%, 26.2%, 25.8%, 21.3%, p=0.022). The SX high rate was higher in lung cancer patients than in control patients (36.0% vs. 21.3%, p=0.011).The highest quartile of the SXscore showed higher risk of lung cancer in comparison to the lowest quartile (OR: 2,250, 95%CI: 1,077 to 4,699 ; P-trend= 0.016). After adjustment, patients in the highest quartile of the SXscore had higher risk of lung cancer (OR: 2,149, 95%CI: 1,008 to 4,584; P-trend= 0.028). Patients with high SXscore (&gt; 15) had 1,985 times more chances of having lung cancer (95%CI: 1,105&#8211;3,563, P= 0.022).</p>
        </sec>
        <sec>
          <title>Conclusions</title>
          <p>The anatomical severity of CAD is associated with the risk of lung cancer, which indicates that a thorough lung cancer screening may be significant among severe CAD patients.</p>
        </sec>
      </abstract>
      <kwd-group xml:lang="en">
        <kwd>Coronary Artery Disease/complications</kwd>
        <kwd>Lung Neoplasms/complications</kwd>
        <kwd>Coronary Angiography/methods</kwd>
        <kwd>Severity of Illness Index</kwd>
        <kwd>Percutaneous Coronary Intervention/methods</kwd>
      </kwd-group>
    </front-stub>
    <body>
      <sec sec-type="intro">
        <title>Introduction</title>
        <p>Both cancer and heart diseases are critical health problems for human beings worldwide.<sup><xref ref-type="bibr" rid="B1">1</xref> , <xref ref-type="bibr" rid="B2">2</xref></sup> Anticancer therapy-induced cardiovascular toxicity has led to the new interdisciplinary field of cardio-oncology.<sup><xref ref-type="bibr" rid="B2">2</xref> - <xref ref-type="bibr" rid="B5">5</xref></sup> At present, oncologists and cardiologists mostly pay more attention to anticancer therapy-related heart diseases among cancer survivors.<sup><xref ref-type="bibr" rid="B6">6</xref> , <xref ref-type="bibr" rid="B7">7</xref></sup> Some studies show there is a direct interactional relationship between heart diseases and cancer.<sup><xref ref-type="bibr" rid="B8">8</xref></sup></p>
        <p>Coronary artery disease (CAD) and cancer share common risk factors and pathophysiological mechanisms.<sup><xref ref-type="bibr" rid="B9">9</xref> - <xref ref-type="bibr" rid="B11">11</xref></sup> There is increasing evidence showing that cancer patients were at increased risk of cardiovascular diseases. A Swedish study showed that cancers were associated with an increased risk of CAD; however, in that case, the study patients had been administered anticancer therapies, so the study could not demonstrate whether or not there was a direct association between CAD and cancer.<sup><xref ref-type="bibr" rid="B2">2</xref></sup> Whether or not the severity of CAD is directly associated with cancer has been rarely reported until now. It is essential to elucidate if there is a potential direct link between CAD and cancer in order to provide better understanding and better management for these two important diseases.</p>
        <p>Lung cancer is the most common cancer and the leading cause of cancer death.<sup><xref ref-type="bibr" rid="B12">12</xref></sup> It is worth investigating the association between CAD and lung cancer. A meta-analysis showed that lung cancer was associated with significantly increased risk of CAD during follow-up compared with non-lung cancer.<sup><xref ref-type="bibr" rid="B13">13</xref></sup> In the study, the included lung cancer patients were followed-up for more than one year after being diagnosed, so they were more likely to have received anticancer therapies, which could not exclude the effect of anticancer treatments on CAD. The direct relationship between CAD and lung cancer is not well understood until the present time. The hypothesis that the severity of CAD is associated with lung cancer has not been reported.</p>
        <p>We conducted a cross-sectional study to investigate the direct association between the anatomical severity of CAD and lung cancer. All of the lung cancer patients had been recently diagnosed and did not receive any anticancer treatments. The control patients were non-lung cancer patients enrolled by propensity score matching to lung cancer patients. All of the study patients underwent coronary angiography (CAG) during index hospitalization. The anatomical severity of CAD was assessed using the SYNTAX score (SXscore) based on coronary angiograms.<sup><xref ref-type="bibr" rid="B14">14</xref></sup> The objective of the present study was to determine whether or not the anatomical severity of CAD is related to the risk of lung cancer.</p>
      </sec>
      <sec sec-type="methods">
        <title>Patients and Methods</title>
        <sec>
          <title>Study patients</title>
          <p>In Chinese PLA General Hospital, all data of inpatients are stored in the medical record system, including coronary angiograms. There were 173 patients with lung cancer (ICD-10 code 34), and 48,968 without any cancers who underwent CAG (ICD-9-CM codes 88.5, 88.55, 88.56, and 88.57) in the department of cardiology from January 1st, 2009, to July 31, 2019.</p>
          <p>Lung cancer diagnoses were validated according to the pathological diagnosis. Of the 173 lung cancer patients, 75 who had been recently diagnosed without being administered any anticancer treatments were enrolled in this study, excluding 31 with a history of anticancer therapy and 67 who were previously undergoing percutaneous coronary intervention (PCI) or coronary artery bypass grafting (CABG). Among the 48,968 non-cancer patients, 225 were enrolled as control patients by propensity score matching to the lung cancer patients (1:3 ratio), according to age, gender, family history of CAD, body mass index (BMI), smoking, hypertension, diabetes, and hyperlipidemia. None of the included patients had a history of connective tissue or other inflammatory diseases, nor of PCI or CABG before the index hospitalization. A flowchart of the study patient enrollment process is shown in <xref ref-type="fig" rid="f01001">Figure 1</xref> .</p>
          <p>
            <fig id="f01001">
              <label>Figure 1</label>
              <caption>
                <title>&#8211; <italic>Flowchart of study patients.</italic></title>
              </caption>
              <graphic xlink:href=""/>
            </fig>
          </p>
          <p>We calculated sample size using the PASS software. According to parameters including a= 0.05, b = 0.20, OR= 2 and the case-control ratio= 1:3, the sample size of the lung cancer group was 74, and the sample size of the non-lung cancer group was 222. In this study, we enrolled 300 patients (75 lung cancer patients and 225 non-lung cancer patients) who met the sample size requirement.</p>
        </sec>
        <sec>
          <title>SXscores of CAD based on CAG</title>
          <p>The severity of CAD was evaluated using the SXscore algorithm (described in full elsewhere).<sup><xref ref-type="bibr" rid="B14">14</xref> , <xref ref-type="bibr" rid="B15">15</xref></sup> All of the angiographic variables related to the SXscore calculation were computed by two blinded experienced interventional cardiologists. When the SXscore of each patient was different between the two cardiologists, they would discuss the angiograms and reach a common SXscore. Final SXscores were calculated per patient and saved in a dedicated database. The SXscore of 15 was the highest quartile in the study. A low SXscore (SXlow) was defined as SXscore &#8804;15, and a high SXscore (SXhigh) as SXscore &gt;15. In the logistic regression analysis, we defined SXhigh (&gt; 15) as positive.</p>
        </sec>
        <sec>
          <title>Statistical analysis</title>
          <p>Descriptive statistics are presented as frequency and percentage rates for categorical variables, and mean &#177; standard deviation (SD) and medians [interquartile range (IQR)] for continuous variables, according to normality of the data. We assessed the normality of the data using the Skewness and Kurtosis normality tests. We used Independent-Samples t-test to compare means between groups when variables were normally distributed. The Mann-Whitney U non-parametric statistical test was used for continuous variables without normal distribution, including triglycerides, low-density lipoprotein cholesterol, high density lipoprotein cholesterol, fasting blood-glucose, alanine aminotransferase, aspartate aminotransferase, serum creatinine and uric acid. The chi-square or Fisher exact tests were used to examine differences for categorical measures.</p>
          <p>The SXscore was divided into quartiles based on the distribution of the score in all of the study subjects, being the first quartile used as a reference. SXscore values for quartiles 1, 2, 3, and 4 were <italic>&lt;</italic> 4.0, 4.0&#8211;9.0, 9.0&#8211;15.0, and <italic>&gt;</italic> 15.0, respectively. The Cochran-Armitage test for trend was used to assess the distribution of the patients&#8217; SXscores. We assessed the relationship between CAD severity (SXscore stratified by quartiles) and lung cancer by using the logistic-regression analysis, adjusting for common related risk factors, including age, BMI, gender, and smoking. Odds ratio (OR) and 95% confidence intervals (CI) were calculated. P-values were two-tailed, and we set the level of significance at 5%. Statistical analyses were performed using the SPSS software, version 23 (SPSS, Inc. Chicago, IL, USA), and the SAS software (SAS Institute, Cary, Carolina do Norte).</p>
        </sec>
      </sec>
      <sec sec-type="results">
        <title>Results</title>
        <sec>
          <title>Patients&#8217; characteristics</title>
          <p>The study patients were a specific population from the Chinese PLA general hospital. The mean age of the 300 study patients was 63.5&#177;9.7 years, and 70 (23.3%) were female. All of the included 75 lung cancer patients had pathological evidence of cancer; 69 (92%) were diagnosed with non-small cell lung cancer; and the other 6 patients (8%), with small cell lung cancer. Forty-eight patients (75%) were at stage I or II; 12 patients (16%) were at stage III; 4 patients (5.3%) were at stage IV; and it was not possible to confirm the disease stage for the other 11 patients (14.7%). Four patients (5.3%) were metastatic. Lung cancer patients had not received any anticancer treatments before the index hospitalization.</p>
          <p>There was no significant difference for age, gender, smoking (stratified as never-smokers and ever-smokers), BMI, family history of CAD, hypertension, diabetes, and hyperlipidemia between lung cancer patients and non-lung cancer patients. However, history of smoking is different between the lung cancer group and the control groups when history of smoking was stratified as never-smokers, former-smokers and current-smokers, which was adjusted in the logistic regression analysis. Ejection fraction (EF) and laboratory data were comparable between lung cancer patients and control patients ( <xref ref-type="table" rid="t1001">Table 1</xref> ).</p>
          <p>
            <table-wrap id="t1001">
              <label>Table 1</label>
              <caption>
                <title>&#8211; Patients&#8217; characteristics</title>
              </caption>
              <table frame="hsides" rules="groups">
                <colgroup>
                  <col/>
                  <col/>
                  <col/>
                  <col/>
                </colgroup>
                <thead>
                  <tr>
                    <th align="left">Characteristic</th>
                    <th>Lung cancer group (n = 75)</th>
                    <th>Non-cancer group (n = 225)</th>
                    <th>p-value</th>
                  </tr>
                </thead>
                <tbody>
                  <tr>
                    <td>
                      <list list-type="simple">
                        <list-item>
                          <p>
                            <bold>Gender, n (%)</bold>
                          </p>
                        </list-item>
                        <list-item>
                          <p>Male</p>
                        </list-item>
                        <list-item>
                          <p>Female</p>
                        </list-item>
                      </list>
                    </td>
                    <td align="center">
                      <list list-type="simple">
                        <list-item>
                          <p>59 (78.7%)</p>
                        </list-item>
                        <list-item>
                          <p>16 (21.3%)</p>
                        </list-item>
                      </list>
                    </td>
                    <td align="center">
                      <list list-type="simple">
                        <list-item>
                          <p>171 (76.0%)</p>
                        </list-item>
                        <list-item>
                          <p>54 (24.0%)</p>
                        </list-item>
                      </list>
                    </td>
                    <td align="center">0.636<sup>a</sup></td>
                  </tr>
                  <tr>
                    <td>
                      <list list-type="simple">
                        <list-item>
                          <p>
                            <bold>Age (years)</bold>
                          </p>
                        </list-item>
                        <list-item>
                          <p>&lt;65</p>
                        </list-item>
                        <list-item>
                          <p>&#8805;65</p>
                        </list-item>
                      </list>
                    </td>
                    <td align="center">
                      <list list-type="simple">
                        <list-item>
                          <p>34(45.3%)</p>
                        </list-item>
                        <list-item>
                          <p>41(54.7%)</p>
                        </list-item>
                      </list>
                    </td>
                    <td align="center">
                      <list list-type="simple">
                        <list-item>
                          <p>120 (53.3%)</p>
                        </list-item>
                        <list-item>
                          <p>105 (46.7%)</p>
                        </list-item>
                      </list>
                    </td>
                    <td align="center">0.230<sup>a</sup></td>
                  </tr>
                  <tr>
                    <td>
                      <list list-type="simple">
                        <list-item>
                          <p>
                            <bold>BMI, n (%)</bold>
                          </p>
                        </list-item>
                        <list-item>
                          <p>&#8804;24</p>
                        </list-item>
                        <list-item>
                          <p>&gt;24</p>
                        </list-item>
                      </list>
                    </td>
                    <td align="center">
                      <list list-type="simple">
                        <list-item>
                          <p>25 (33.30%)</p>
                        </list-item>
                        <list-item>
                          <p>50 (66.70%)</p>
                        </list-item>
                      </list>
                    </td>
                    <td align="center">
                      <list list-type="simple">
                        <list-item>
                          <p>73 (32.4%)</p>
                        </list-item>
                        <list-item>
                          <p>152 (67.6%)</p>
                        </list-item>
                      </list>
                    </td>
                    <td align="center">0.887<sup>a</sup></td>
                  </tr>
                  <tr>
                    <td>
                      <list list-type="simple">
                        <list-item>
                          <p>
                            <bold>Smoking, n (%)</bold>
                          </p>
                        </list-item>
                        <list-item>
                          <p>Never-smokers</p>
                        </list-item>
                        <list-item>
                          <p>Ever-smokers</p>
                        </list-item>
                      </list>
                    </td>
                    <td align="center">
                      <list list-type="simple">
                        <list-item>
                          <p>27(36.0%)</p>
                        </list-item>
                        <list-item>
                          <p>48(64.0%)</p>
                        </list-item>
                      </list>
                    </td>
                    <td align="center">
                      <list list-type="simple">
                        <list-item>
                          <p>97 (43.1%)</p>
                        </list-item>
                        <list-item>
                          <p>128 (56.9%)</p>
                        </list-item>
                      </list>
                    </td>
                    <td align="center">0.279<sup>a</sup></td>
                  </tr>
                  <tr>
                    <td>
                      <list list-type="simple">
                        <list-item>
                          <p>
                            <bold>Smoking, n (%)</bold>
                          </p>
                        </list-item>
                        <list-item>
                          <p>Never-smokers</p>
                        </list-item>
                        <list-item>
                          <p>Former-smokers</p>
                        </list-item>
                        <list-item>
                          <p>Current-smokers</p>
                        </list-item>
                      </list>
                    </td>
                    <td align="center">
                      <list list-type="simple">
                        <list-item>
                          <p>27 (36.0%)</p>
                        </list-item>
                        <list-item>
                          <p>21 (28.0%)</p>
                        </list-item>
                        <list-item>
                          <p>27 (36.0%)</p>
                        </list-item>
                      </list>
                    </td>
                    <td align="center">
                      <list list-type="simple">
                        <list-item>
                          <p>97 (43.1%)</p>
                        </list-item>
                        <list-item>
                          <p>30 (13.3%)</p>
                        </list-item>
                        <list-item>
                          <p>98 (43.6%)</p>
                        </list-item>
                      </list>
                    </td>
                    <td align="center">0.014<sup>a</sup></td>
                  </tr>
                  <tr>
                    <td>
                      <list list-type="simple">
                        <list-item>
                          <p>
                            <bold>Family history of CAD, n (%)</bold>
                          </p>
                        </list-item>
                        <list-item>
                          <p>No</p>
                        </list-item>
                        <list-item>
                          <p>Yes</p>
                        </list-item>
                      </list>
                    </td>
                    <td align="center">
                      <list list-type="simple">
                        <list-item>
                          <p>69 (92.00%)</p>
                        </list-item>
                        <list-item>
                          <p>6 (8.00%)</p>
                        </list-item>
                      </list>
                    </td>
                    <td align="center">
                      <list list-type="simple">
                        <list-item>
                          <p>196 (87.1%)</p>
                        </list-item>
                        <list-item>
                          <p>29 (12.9%)</p>
                        </list-item>
                      </list>
                    </td>
                    <td align="center">0.253<sup>a</sup></td>
                  </tr>
                  <tr>
                    <td>
                      <list list-type="simple">
                        <list-item>
                          <p>
                            <bold>Hypertension, n (%)</bold>
                          </p>
                        </list-item>
                        <list-item>
                          <p>No</p>
                        </list-item>
                        <list-item>
                          <p>Yes</p>
                        </list-item>
                      </list>
                    </td>
                    <td align="center">
                      <list list-type="simple">
                        <list-item>
                          <p>29 (38.7%)</p>
                        </list-item>
                        <list-item>
                          <p>46 (61.3%)</p>
                        </list-item>
                      </list>
                    </td>
                    <td align="center">
                      <list list-type="simple">
                        <list-item>
                          <p>84 (37.3%)</p>
                        </list-item>
                        <list-item>
                          <p>141 (62.7%)</p>
                        </list-item>
                      </list>
                    </td>
                    <td align="center">0.836<sup>a</sup></td>
                  </tr>
                  <tr>
                    <td>
                      <list list-type="simple">
                        <list-item>
                          <p>
                            <bold>Diabetes, n (%)</bold>
                          </p>
                        </list-item>
                        <list-item>
                          <p>No</p>
                        </list-item>
                        <list-item>
                          <p>Yes</p>
                        </list-item>
                      </list>
                    </td>
                    <td align="center">
                      <list list-type="simple">
                        <list-item>
                          <p>40 (53.3%)</p>
                        </list-item>
                        <list-item>
                          <p>35 (46.7%)</p>
                        </list-item>
                      </list>
                    </td>
                    <td align="center">
                      <list list-type="simple">
                        <list-item>
                          <p>131 (58.2%)</p>
                        </list-item>
                        <list-item>
                          <p>94 (41.8%)</p>
                        </list-item>
                      </list>
                    </td>
                    <td align="center">0.459<sup>a</sup></td>
                  </tr>
                  <tr>
                    <td>
                      <list list-type="simple">
                        <list-item>
                          <p>
                            <bold>Hyperlipidemia, n (%)</bold>
                          </p>
                        </list-item>
                        <list-item>
                          <p>No</p>
                        </list-item>
                        <list-item>
                          <p>Yes</p>
                        </list-item>
                      </list>
                    </td>
                    <td align="center">
                      <list list-type="simple">
                        <list-item>
                          <p>25(33.3%)</p>
                        </list-item>
                        <list-item>
                          <p>50(66.7%)</p>
                        </list-item>
                      </list>
                    </td>
                    <td align="center">
                      <list list-type="simple">
                        <list-item>
                          <p>95 (42.2%)</p>
                        </list-item>
                        <list-item>
                          <p>130 (57.8%)</p>
                        </list-item>
                      </list>
                    </td>
                    <td align="center">0.174<sup>a</sup></td>
                  </tr>
                  <tr>
                    <td>
                      <list list-type="simple">
                        <list-item>
                          <p>
                            <bold>Ejection fraction (%), n (%)</bold>
                          </p>
                        </list-item>
                        <list-item>
                          <p>&lt;50</p>
                        </list-item>
                        <list-item>
                          <p>&#8805;50</p>
                        </list-item>
                      </list>
                    </td>
                    <td align="center">
                      <list list-type="simple">
                        <list-item>
                          <p>5(7.0%)</p>
                        </list-item>
                        <list-item>
                          <p>66(93.0%)</p>
                        </list-item>
                      </list>
                    </td>
                    <td align="center">
                      <list list-type="simple">
                        <list-item>
                          <p>21 (11.7%)</p>
                        </list-item>
                        <list-item>
                          <p>159 (88.3%)</p>
                        </list-item>
                      </list>
                    </td>
                    <td align="center">0.279<sup>a</sup></td>
                  </tr>
                  <tr>
                    <td>
                      <list list-type="simple">
                        <list-item>
                          <p>
                            <bold>Laboratory data</bold>
                          </p>
                        </list-item>
                        <list-item>
                          <p>Total cholesterol</p>
                        </list-item>
                        <list-item>
                          <p>Triglyceride, mmol/L</p>
                        </list-item>
                        <list-item>
                          <p>LDL-C , mmol/L</p>
                        </list-item>
                        <list-item>
                          <p>HDL-C, mmol/L</p>
                        </list-item>
                        <list-item>
                          <p>FBG, mmol/L</p>
                        </list-item>
                        <list-item>
                          <p>ALT, U/L</p>
                        </list-item>
                        <list-item>
                          <p>AST, U/L</p>
                        </list-item>
                        <list-item>
                          <p>Albumin, g/L</p>
                        </list-item>
                        <list-item>
                          <p>Serum creatinine, &#181;mol/L</p>
                        </list-item>
                        <list-item>
                          <p>Uric acid, mmol/L</p>
                        </list-item>
                        <list-item>
                          <p>Hemoglobin, g/L</p>
                        </list-item>
                      </list>
                    </td>
                    <td align="center">
                      <list list-type="simple">
                        <list-item>
                          <p>4.035&#177;0.950</p>
                        </list-item>
                        <list-item>
                          <p>1.420 (IQR [1.055&#8211;1.780])</p>
                        </list-item>
                        <list-item>
                          <p>2.545 (IQR [1.838&#8211;3.195])</p>
                        </list-item>
                        <list-item>
                          <p>1.070 (IQR [0.833&#8211;1.265])</p>
                        </list-item>
                        <list-item>
                          <p>5.820 (IQR [4.980&#8211;7.720])</p>
                        </list-item>
                        <list-item>
                          <p>20.50 (IQR [11.70&#8211;27.20])</p>
                        </list-item>
                        <list-item>
                          <p>17.20 (IQR [13.70&#8211;25.10])</p>
                        </list-item>
                        <list-item>
                          <p>40.589&#177;4.056</p>
                        </list-item>
                        <list-item>
                          <p>76.70 (IQR [66.80&#8211;84.80])</p>
                        </list-item>
                        <list-item>
                          <p>328.10 (IQR [266.00&#8211;396.70])</p>
                        </list-item>
                        <list-item>
                          <p>135.76&#177;16.647</p>
                        </list-item>
                      </list>
                    </td>
                    <td align="center">
                      <list list-type="simple">
                        <list-item>
                          <p>4.029&#177;1.015</p>
                        </list-item>
                        <list-item>
                          <p>1.360 (IQR [1.020&#8211;1.860])</p>
                        </list-item>
                        <list-item>
                          <p>2.340 (IQR [1.850&#8211;3.058])</p>
                        </list-item>
                        <list-item>
                          <p>0.980 (IQR [0.830&#8211;1185])</p>
                        </list-item>
                        <list-item>
                          <p>5.710 (IQR [4.895&#8211;7.725])</p>
                        </list-item>
                        <list-item>
                          <p>21.40 (IQR [15.20&#8211;30.70])</p>
                        </list-item>
                        <list-item>
                          <p>18.35 (IQR [14.70&#8211;24.55])</p>
                        </list-item>
                        <list-item>
                          <p>40.640&#177;6.459</p>
                        </list-item>
                        <list-item>
                          <p>75.50 (IQR [64.90&#8211;89.25])</p>
                        </list-item>
                        <list-item>
                          <p>324.95 (IQR [268.28&#8211;358.13])</p>
                        </list-item>
                        <list-item>
                          <p>139.55&#177;16.059</p>
                        </list-item>
                      </list>
                    </td>
                    <td align="center">
                      <list list-type="simple">
                        <list-item>
                          <p>0.968<sup>b</sup></p>
                        </list-item>
                        <list-item>
                          <p>0.854<sup>c</sup></p>
                        </list-item>
                        <list-item>
                          <p>0.497<sup>c</sup></p>
                        </list-item>
                        <list-item>
                          <p>0.096<sup>c</sup></p>
                        </list-item>
                        <list-item>
                          <p>0.598<sup>c</sup></p>
                        </list-item>
                        <list-item>
                          <p>0.049<sup>c</sup></p>
                        </list-item>
                        <list-item>
                          <p>0.355<sup>c</sup></p>
                        </list-item>
                        <list-item>
                          <p>0.949<sup>b</sup></p>
                        </list-item>
                        <list-item>
                          <p>0.910<sup>c</sup></p>
                        </list-item>
                        <list-item>
                          <p>0.984<sup>c</sup></p>
                        </list-item>
                        <list-item>
                          <p>0.088<sup>b</sup></p>
                        </list-item>
                      </list>
                    </td>
                  </tr>
                  <tr>
                    <td>
                      <list list-type="simple">
                        <list-item>
                          <p>
                            <bold>SXscore grades by quartiles</bold>
                          </p>
                        </list-item>
                        <list-item>
                          <p>Quartile 1 (&#8804; 4.0)</p>
                        </list-item>
                        <list-item>
                          <p>Quartile 2 (4.0-9.0)</p>
                        </list-item>
                        <list-item>
                          <p>Quartile 3 (9.0-15.0)</p>
                        </list-item>
                        <list-item>
                          <p>Quartile 4 (&gt;15.0)</p>
                        </list-item>
                      </list>
                    </td>
                    <td align="center">
                      <list list-type="simple">
                        <list-item>
                          <p>15 (20.0%)</p>
                        </list-item>
                        <list-item>
                          <p>15 (20.0%)</p>
                        </list-item>
                        <list-item>
                          <p>18 (24.0%)</p>
                        </list-item>
                        <list-item>
                          <p>27 (36.0%)</p>
                        </list-item>
                      </list>
                    </td>
                    <td align="center">
                      <list list-type="simple">
                        <list-item>
                          <p>60 (26.7%)</p>
                        </list-item>
                        <list-item>
                          <p>59 (26.2%)</p>
                        </list-item>
                        <list-item>
                          <p>58 (25.8%)</p>
                        </list-item>
                        <list-item>
                          <p>48 (21.3%)</p>
                        </list-item>
                      </list>
                    </td>
                    <td align="center">0.022<sup>d</sup></td>
                  </tr>
                  <tr>
                    <td>
                      <list list-type="simple">
                        <list-item>
                          <p>
                            <bold>SXscore grades by highest quartile</bold>
                          </p>
                        </list-item>
                        <list-item>
                          <p>SXlow (&#8804;15)</p>
                        </list-item>
                        <list-item>
                          <p>SXhigh (&gt;15)</p>
                        </list-item>
                      </list>
                    </td>
                    <td align="center">
                      <list list-type="simple">
                        <list-item>
                          <p>48 (64.0%)</p>
                        </list-item>
                        <list-item>
                          <p>27 (36.0%)</p>
                        </list-item>
                      </list>
                    </td>
                    <td align="center">
                      <list list-type="simple">
                        <list-item>
                          <p>177 (78.7%)</p>
                        </list-item>
                        <list-item>
                          <p>48 (21.3%)</p>
                        </list-item>
                      </list>
                    </td>
                    <td align="center">0.011<sup>a</sup></td>
                  </tr>
                </tbody>
              </table>
              <table-wrap-foot>
                <fn id="TFN1001">
                  <p>
                    <italic>BMI: body mass index; LDL-C:low-density lipoprotein cholesterol; HDL-C: high density lipoprotein cholesterol; FBG: fasting blood-glucose; ALT: alanine aminotransferase; AST: aspartate aminotransferase; IQR: interquartile range; Quartile1-4 = lowest quartile to highest quartile;<sup>a</sup>Chi-squared test;<sup>b</sup>Independent-Samples t test;<sup>c</sup>Mann-Whitney U non-parametric statistical test;<sup>d</sup>Cochran&#8211;Armitage trend test.</italic>
                  </p>
                </fn>
              </table-wrap-foot>
            </table-wrap>
          </p>
          <p>Overall SXscores ranged from 0 to 40, with a median of 10 [IQR (4.0&#8211;15.0)]. In lung cancer patients, there were 20.0%, 20.0%, 24.0%, and 36.0% of patients in the lowest, lower-middle, upper-middle, and highest quartile, respectively. In control patients, the percentage of patients was 26.7%, 26.2%, 25.8%, and 21.3% from the lowest to the highest quartile, respectively. The Cochran-Armitage test for trend showed that the distribution trend of the patients&#8217; SXscore was different between lung cancer and control patients, and the lung cancer group had a significantly higher percentage of patients with higher SXscore. According to the definition of SXhigh and SXlow by the highest quartile (SXscore=15), of SXscores as the cut-off value, 75 patients presented with SXhigh (&gt;15), and 225 patients with SXlow (&#8804;15). The rate of SXhigh was higher in lung cancer patients than in control patients ( <xref ref-type="table" rid="t1001">Table 1</xref> ).</p>
        </sec>
        <sec>
          <title>Association between severity of CAD and lung cancer</title>
          <p>The association between the SXscore and lung cancer was analyzed by quartiles of SXscore. Significant associations were shown between the increasing SXscore and the risk of lung cancer (P-trend=0.016). After different adjustments for age, BMI, gender and smoking (never smokers, former smokers and current smokers), the SXscore was correlated with the risk of lung cancer (P-trend=0.024; P-trend=0.024; P-trend=0.029; P-trend=0.028, respectively). The OR for lung cancer (vs. the first quartile of the SXscore) was 1,017 (95%CI: 0,457 to 2,265) for the second quartile of SXscore, and was 1.241 (95% CI: 0.572 to 2.693) for the third quartile of the SXscore. The highest quartile of the SXscore showed significantly higher risk of lung cancer compared to the lowest quartile (OR: 2.250; 95%CI: 1,077 to 4,699). After adjusting for age, BMI, gender and smoking, patients in the highest quartile of the SXscore had higher risk of lung cancer than those in the lowest quartile of the SXscore (OR: 2,149, 95%CI: 1,008 to 4,584 ) ( <xref ref-type="table" rid="t2001">Table 2</xref> ).</p>
          <p>
            <table-wrap id="t2001">
              <label>Table 2</label>
              <caption>
                <title>&#8211; ORs and 95%CIs for lung cancer by quartiles of the SXscore</title>
              </caption>
              <table frame="hsides" rules="groups">
                <colgroup>
                  <col/>
                  <col/>
                  <col/>
                  <col/>
                  <col/>
                  <col/>
                </colgroup>
                <thead>
                  <tr>
                    <th align="left" rowspan="2" style="font-weight:normal"> </th>
                    <th colspan="5">Quartile of SXscore</th>
                  </tr>
                  <tr>
                    <th>Quartile 1 (Reference) (&#8804; 4.0)</th>
                    <th>Quartile 2 (4.0-9.0)</th>
                    <th>Quartile 3 (9.0-15.0)</th>
                    <th>Quartile 4 (&gt;15.0)</th>
                    <th><italic>P</italic> for trend<sup>*</sup></th>
                  </tr>
                </thead>
                <tbody>
                  <tr>
                    <td>Median of SXscore</td>
                    <td align="center">2.0</td>
                    <td align="center">7.0</td>
                    <td align="center">12.0</td>
                    <td align="center">22.5</td>
                    <td> </td>
                  </tr>
                  <tr>
                    <td>No. of lung cancer/control (Total)</td>
                    <td align="center">15/60</td>
                    <td align="center">15/59</td>
                    <td align="center">18/58</td>
                    <td align="center">27/48</td>
                    <td> </td>
                  </tr>
                  <tr>
                    <td>Model 1: OR (95% CI)</td>
                    <td align="center">1</td>
                    <td align="center">1.017 (0.457-2.265)</td>
                    <td align="center">1.241 (0.572-2.693)</td>
                    <td align="center">2.250 (1.077-4.699)</td>
                    <td align="center">0.016</td>
                  </tr>
                  <tr>
                    <td>Model 2: OR (95% CI)</td>
                    <td align="center">1</td>
                    <td align="center">1.007 (0.451-2.245)</td>
                    <td align="center">1.233 (0.568-2.677)</td>
                    <td align="center">2.151 (1.021-4.530)</td>
                    <td align="center">0.024</td>
                  </tr>
                  <tr>
                    <td>Model 3: OR (95% CI)</td>
                    <td align="center">1</td>
                    <td align="center">1.011 (0.453-2.258)</td>
                    <td align="center">1.230 (0.566-2.672)</td>
                    <td align="center">2.165 (1.024-4.545)</td>
                    <td align="center">0.024</td>
                  </tr>
                  <tr>
                    <td>Model 4: OR (95% CI)</td>
                    <td align="center">1</td>
                    <td align="center">1.010 (0.452-2.255)</td>
                    <td align="center">1.215 (0.557-2.653)</td>
                    <td align="center">2.133(1.002-4.540)</td>
                    <td align="center">0.029</td>
                  </tr>
                  <tr>
                    <td>Model 5: OR (95% CI)</td>
                    <td align="center">1</td>
                    <td align="center">1.019 (0.455-2.279)</td>
                    <td align="center">1.227 (0.561-2.285)</td>
                    <td align="center">2.149 (1.008-4.584)</td>
                    <td align="center">0.028</td>
                  </tr>
                </tbody>
              </table>
              <table-wrap-foot>
                <fn id="TFN2001">
                  <p>
                    <italic>Model 1: crude model; Model 2: adjusted for age; Model 3: adjusted for age, BMI; Model 4: adjusted for age, BMI, gender; Model 5: adjusted for age, BMI, gender, smoking (never smokers, former smokers and current smokers). Quartile 1-4 = lowest quartile to highest quartile. *Test for trend based on variable containing median value for each quartile.</italic>
                  </p>
                </fn>
              </table-wrap-foot>
            </table-wrap>
          </p>
          <p>Then, a logistic regression analysis showed higher risk of SXhigh for lung cancer compared with SXlow. Univariate logistic regression analysis showed that SXhigh increased the risk of lung cancer by 2,074 times (95%CI: 1,174&#8211;3,665). Adjusting for age, the multivariate logistic regression analysis showed that patients with SXhigh had 1,994 more chances of developing lung cancer (95%CI: 1,119&#8211;3,551). Then, adjusting for age, BMI, gender and smoking (never smokers, former smokers and current smokers), patients with SXhigh were more likely to have lung cancer by 1,985 times (95%CI: 1,105&#8211;3,563) compared to patients with SXlow ( <xref ref-type="table" rid="t3001">Table 3</xref> ).</p>
          <p>
            <table-wrap id="t3001">
              <label>Table 3</label>
              <caption>
                <title>&#8211; ORs and 95%CIs of SXhigh for lung cancer</title>
              </caption>
              <table frame="hsides" rules="groups">
                <colgroup>
                  <col/>
                  <col/>
                  <col/>
                  <col/>
                </colgroup>
                <thead>
                  <tr>
                    <th align="left">Model</th>
                    <th>OR</th>
                    <th>95%CI</th>
                    <th>p-value</th>
                  </tr>
                </thead>
                <tbody>
                  <tr>
                    <td>Model 1</td>
                    <td align="center">2.074</td>
                    <td align="center">1.174-3.665</td>
                    <td align="center">0.012</td>
                  </tr>
                  <tr>
                    <td>Model 2</td>
                    <td align="center">1.994</td>
                    <td align="center">1.119-3.551</td>
                    <td align="center">0.019</td>
                  </tr>
                  <tr>
                    <td>Model 3</td>
                    <td align="center">2.007</td>
                    <td align="center">1.123-3.588</td>
                    <td align="center">0.019</td>
                  </tr>
                  <tr>
                    <td>Model 4</td>
                    <td align="center">1.983</td>
                    <td align="center">1.105-3.558</td>
                    <td align="center">0.022</td>
                  </tr>
                  <tr>
                    <td>Model 5</td>
                    <td align="center">1.985</td>
                    <td align="center">1.105-3.563</td>
                    <td align="center">0.022</td>
                  </tr>
                </tbody>
              </table>
              <table-wrap-foot>
                <fn id="TFN3001">
                  <p>
                    <italic>Model 1: crude model; Model 2: adjusted for age; Model 3: adjusted for age, BMI; Model 4: adjusted for age, BMI, gender; Model 5: adjusted for age, BMI, gender, smoking (never smokers, former smokers and current smokers).</italic>
                  </p>
                </fn>
              </table-wrap-foot>
            </table-wrap>
          </p>
        </sec>
      </sec>
      <sec sec-type="discussion">
        <title>Discussion</title>
        <p>Both CAD and lung cancer are diseases that usually affect human health. Age standardized ischemic heart disease and lung cancer were the second and third leading causes of years of life lost in China in 2017.<sup><xref ref-type="bibr" rid="B16">16</xref></sup> CAD is rarely directly associated with recently-diagnosed lung cancer. To the best of our knowledge, the current study is the first to investigate the direct association between the anatomical severity of CAD and lung cancer. The results showed that the severity of CAD is associated with increased risk of lung cancer. After different adjustments, severe CAD was still significantly associated with the risk of lung cancer. Given the importance of CAD and lung cancer to human health, the results of this study are of great significance.</p>
        <p>Cardio-oncology is an emerging medical field that focuses on cardiotoxicity induced by anticancer therapy.<sup><xref ref-type="bibr" rid="B3">3</xref> , <xref ref-type="bibr" rid="B17">17</xref> , <xref ref-type="bibr" rid="B18">18</xref></sup> However, the direct relationship between cancer and heart disease remains largely unknown. In this study, we evaluated the severity of CAD using the SXscore based on coronary angiograms of lung cancer patients and non-lung cancer patients. The results showed there were significant associations between increasing SXscore and the risk of lung cancer. CAD and lung cancer are considered as significant public health problems, growing in importance, globally. The results of the present study demonstrated that CAD patients with high SXscore were at higher risk of lung cancer compared with patients with low SXscore, which indicates that it would be preferable to screen lung cancer among severe CAD patients. It should be pointed out that the fact that both diseases are in a cause-effect relationship or that they coexist in a common environment could not be determined in the current study. It is necessary to further clarify the correlation between CAD and lung cancer in future analyses.</p>
        <p>The mechanism underlying the association between CAD and cancer is not well known, and that may be owed to several possible aspects: shared risk factors, inflammatory status and shared pathophysiological pathways.<sup><xref ref-type="bibr" rid="B9">9</xref> , <xref ref-type="bibr" rid="B10">10</xref> , <xref ref-type="bibr" rid="B19">19</xref></sup> This study shows that the association between CAD and lung cancer is independent from common cardiovascular and cancer risk factors, including age, BMI, gender and smoking. A great number of studies showed that inflammation plays a key role in the pathogenesis of cancer and CAD.<sup><xref ref-type="bibr" rid="B20">20</xref> - <xref ref-type="bibr" rid="B23">23</xref></sup> Clinical and experimental data support a critical role for inflammation in atherothrombosis, including CAD.<sup><xref ref-type="bibr" rid="B24">24</xref></sup> Cancer-related inflammations can be present before a malignant change occurs, which can lead to the development of tumors.<sup><xref ref-type="bibr" rid="B20">20</xref></sup> It has been reported that tumor-bearing mice have a robust proinflammatory response to tumors.<sup><xref ref-type="bibr" rid="B25">25</xref> , <xref ref-type="bibr" rid="B26">26</xref></sup> The Canakinumab Anti-inflammatory Thrombosis Outcomes Study (CANTOS) shows that anti-inflammatory therapy with Canakinumab could significantly reduce the incidence of lung cancer and lung cancer mortality, in addition to significantly reducing the rate of recurrent cardiovascular events among patients with previous myocardial infarction.<sup><xref ref-type="bibr" rid="B24">24</xref> , <xref ref-type="bibr" rid="B27">27</xref></sup> Based on previous studies, it is reasonable to infer that inflammation is an important link between CAD and lung cancer. The C-reactive protein is the most extensively accepted inflammatory marker.<sup><xref ref-type="bibr" rid="B21">21</xref> , <xref ref-type="bibr" rid="B28">28</xref></sup> In the retrospective study, more than one-third of the study patients had not been tested for C-reactive protein, so we could not further analyze the role of inflammation in the association between CAD and lung cancer in the present study. We will determine the impact of inflammation on the direct relationship between CAD and cancer in future studies.</p>
        <p>Apart from inflammation, atherothrombotic disease and neoplasms share many pathophysiologic pathways, including oxidative stress, apoptosis, Cell proliferation, and neoangiogenesis.<sup><xref ref-type="bibr" rid="B19">19</xref></sup> RNA microparticles were a major pathophysiologic mechanism between cancer and atherosclerosis.<sup><xref ref-type="bibr" rid="B19">19</xref></sup> Lectin-like oxidized low-density lipoprotein receptor-1 (LOX-1) is a lectin-like receptor for oxidized low-density lipoproteins (ox-LDL) primarily expressed in endothelial cells and blood vessel rich organs. LOX-1 has demonstrated to be effective during the process of atherogenesis and tumorigenesis, and could be a potential link between these two diseases. Individuals with atherosclerotic plaques and high levels of circulating ox-LDL and LOX-1 expression seem to be more prone to developing cancer.<sup><xref ref-type="bibr" rid="B29">29</xref></sup> The association of CAD and cancer can be explained by the mechanistic overlap in the pathophysiology of atherogenesis and tumorigenesis; however, more studies are necessary to further elucidate the mechanism underlying the association between CAD and cancer.</p>
        <sec>
          <title>Study limitations</title>
          <p>The limitations include, firstly, the small sample size. Results from a specific small-sized population of patients from a single center of China might be deviant. However, the enrollment bias was as minimized as possible based on the choice of study patients. We enrolled all eligible lung cancer patients who had not received any anticancer treatments, and randomly enrolled propensity score matched control patients among 49,141 patients. Secondly, the underlying mechanism of the association between CAD and lung cancer was not clarified, although inflammation may play an important role for the increased risk of severe CAD with lung cancer. We will further investigate the association between CAD and cancer and the underlying mechanism on the basis of the pilot study.</p>
        </sec>
      </sec>
      <sec sec-type="conclusions">
        <title>Conclusions</title>
        <p>This study provides a new perspective on the relationship between CAD and lung cancer. We demonstrate that the anatomical severity of CAD and lung cancer is associated with the risk of lung cancer. The results warns us that it may be worth it to closely screen lung cancer among patients with severe CAD. It is significant to further illustrate the direct link between CAD and lung cancer and to elucidate the underlying mechanism in future, larger-scale clinical trials and basic studies.</p>
      </sec>
    </body>
    <back>
      <ack>
        <title>Acknowledgments</title>
        <p>This work is supported by grants from the National Natural Science Foundation of China (no. 81770237). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.</p>
      </ack>
      <fn-group>
        <fn fn-type="other">
          <p>Study Association</p>
          <p>The study patients of the article were part of the thesis of master submitted by Qian Yang. Mingzhuang Sun further investigated the patients and got new results which were written into the article.</p>
        </fn>
        <fn fn-type="other">
          <p>Ethics approval and consent to participate</p>
          <p>This study was approved by the Ethics Committee of the Chinese PLA General Hospital under the protocol number S2019-223-02. All the procedures in this study were in accordance with the 1975 Helsinki Declaration, updated in 2013. Informed consent was obtained from all participants included in the study.</p>
        </fn>
      </fn-group>
      <fn-group>
        <fn fn-type="financial-disclosure">
          <p>Sources of Funding: This study was partially funded by National Natural Science Foundation of China. (No. 81770237).</p>
        </fn>
      </fn-group>
    </back>
  </sub-article>
</article>
