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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">RMdCpzXRqHX9Sgp3gw6RDzc</article-id>
      <article-id specific-use="scielo-v2" pub-id-type="publisher-id">S0066-782X2024000100307</article-id>
      <article-id pub-id-type="other">00307</article-id>
      <article-id pub-id-type="doi">10.36660/abc.20230376</article-id>
      <article-categories>
        <subj-group subj-group-type="heading">
          <subject>Artigo Original</subject>
        </subj-group>
      </article-categories>
      <title-group>
        <article-title>Testes de Triagem Prevendo Met&#225;stase de C&#226;ncer na Etiologia do Derrame Peric&#225;rdico: HALP Score e PNI</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <contrib-id contrib-id-type="orcid">0000-0001-9823-1613</contrib-id>
          <name>
            <surname>Koyun</surname>
            <given-names>Emin</given-names>
          </name>
          <role>Concep&#231;&#227;o e desenho da pesquisa</role>
          <role>Obten&#231;&#227;o de dados</role>
          <role>An&#225;lise e interpreta&#231;&#227;o dos dados</role>
          <role>An&#225;lise estat&#237;stica</role>
          <role>Reda&#231;&#227;o do manuscrito e Revis&#227;o cr&#237;tica do manuscrito quanto ao conte&#250;do intelectual importante</role>
          <xref ref-type="aff" rid="aff1">
            <sup>1</sup>
          </xref>
          <xref ref-type="corresp" rid="c1"/>
        </contrib>
        <contrib contrib-type="author">
          <contrib-id contrib-id-type="orcid">0000-0003-0053-9594</contrib-id>
          <name>
            <surname>Dindas</surname>
            <given-names>Ferhat</given-names>
          </name>
          <role>Concep&#231;&#227;o e desenho da pesquisa</role>
          <role>Obten&#231;&#227;o de dados</role>
          <role>An&#225;lise e interpreta&#231;&#227;o dos dados</role>
          <role>An&#225;lise estat&#237;stica</role>
          <role>Reda&#231;&#227;o do manuscrito e Revis&#227;o cr&#237;tica do manuscrito quanto ao conte&#250;do intelectual importante</role>
          <xref ref-type="aff" rid="aff2">
            <sup>2</sup>
          </xref>
        </contrib>
        <contrib contrib-type="author">
          <contrib-id contrib-id-type="orcid">0000-0003-3416-5965</contrib-id>
          <name>
            <surname>Sahin</surname>
            <given-names>Anil</given-names>
          </name>
          <role>Concep&#231;&#227;o e desenho da pesquisa</role>
          <role>Obten&#231;&#227;o de dados</role>
          <role>An&#225;lise e interpreta&#231;&#227;o dos dados</role>
          <role>An&#225;lise estat&#237;stica</role>
          <role>Reda&#231;&#227;o do manuscrito e Revis&#227;o cr&#237;tica do manuscrito quanto ao conte&#250;do intelectual importante</role>
          <xref ref-type="aff" rid="aff1">
            <sup>1</sup>
          </xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Cerik</surname>
            <given-names>Idris Bugra</given-names>
          </name>
          <role>Concep&#231;&#227;o e desenho da pesquisa</role>
          <role>Obten&#231;&#227;o de dados</role>
          <role>An&#225;lise e interpreta&#231;&#227;o dos dados</role>
          <role>An&#225;lise estat&#237;stica</role>
          <role>Reda&#231;&#227;o do manuscrito e Revis&#227;o cr&#237;tica do manuscrito quanto ao conte&#250;do intelectual importante</role>
          <xref ref-type="aff" rid="aff3">
            <sup>3</sup>
          </xref>
        </contrib>
        <contrib contrib-type="author">
          <contrib-id contrib-id-type="orcid">0000-0002-3895-1923</contrib-id>
          <name>
            <surname>Dogdus</surname>
            <given-names>Mustafa</given-names>
          </name>
          <role>Concep&#231;&#227;o e desenho da pesquisa</role>
          <role>Obten&#231;&#227;o de dados</role>
          <role>An&#225;lise e interpreta&#231;&#227;o dos dados</role>
          <role>An&#225;lise estat&#237;stica</role>
          <role>Reda&#231;&#227;o do manuscrito e Revis&#227;o cr&#237;tica do manuscrito quanto ao conte&#250;do intelectual importante</role>
          <xref ref-type="aff" rid="aff4">
            <sup>4</sup>
          </xref>
        </contrib>
        <aff id="aff1">
          <label>1</label>
          <institution content-type="orgname">Sivas Cumhuriyet University</institution>
          <institution content-type="orgdiv1">Department of Cardiology</institution>
          <addr-line>
            <named-content content-type="city">Sivas</named-content>
          </addr-line>
          <country country="TR">Turquia</country>
          <institution content-type="original">Sivas Cumhuriyet University &#8211; Department of Cardiology, Sivas &#8211; Turquia</institution>
        </aff>
        <aff id="aff2">
          <label>2</label>
          <institution content-type="orgname">Usak University</institution>
          <institution content-type="orgdiv1">Department of Cardiology</institution>
          <addr-line>
            <named-content content-type="city">Usak</named-content>
          </addr-line>
          <country country="TR">Turquia</country>
          <institution content-type="original">Usak University &#8211; Department of Cardiology, Usak &#8211; Turquia</institution>
        </aff>
        <aff id="aff3">
          <label>3</label>
          <institution content-type="orgname">Ordu University</institution>
          <institution content-type="orgdiv1">Department of Cardiology</institution>
          <addr-line>
            <named-content content-type="city">Ordu</named-content>
          </addr-line>
          <country country="TR">Turquia</country>
          <institution content-type="original">Ordu University &#8211; Department of Cardiology, Ordu &#8211; Turquia</institution>
        </aff>
        <aff id="aff4">
          <label>4</label>
          <institution content-type="orgname">Izmir University of Economics</institution>
          <institution content-type="orgdiv1">Department of Cardiology</institution>
          <addr-line>
            <named-content content-type="city">Izmir</named-content>
          </addr-line>
          <country country="TR">Turquia</country>
          <institution content-type="original">Izmir University of Economics &#8211; Department of Cardiology, Izmir &#8211; Turquia</institution>
        </aff>
      </contrib-group>
      <author-notes>
        <corresp id="c1"><bold>Correspond&#234;ncia: Emin Koyun</bold> &#8226; Sivas Cumhuriyet University - Department of Cardiology - Cumhuriyet &#220;niversitesi T&#305;p Fak&#252;ltesi Hastanesi Kalp Hastal&#305;klar&#305; Merkezi Sivas <postal-code>58000</postal-code> &#8211; Turquia. E-mail: <email>eminkoyun.93@gmail.com</email></corresp>
        <fn fn-type="edited-by">
          <p>Editor respons&#225;vel pela revis&#227;o: Gl&#225;ucia Maria Moraes de Oliveira</p>
        </fn>
        <fn fn-type="conflict">
          <p>
            <bold>Potencial conflito de interesse</bold>
          </p>
          <p>N&#227;o h&#225; conflito com o presente artigo</p>
        </fn>
      </author-notes>
      <pub-date publication-format="electronic" date-type="pub">
        <day>04</day>
        <month>03</month>
        <year>2024</year>
      </pub-date>
      <pub-date publication-format="electronic" date-type="collection">
        <year>2024</year>
      </pub-date>
      <volume>121</volume>
      <issue>1</issue>
      <elocation-id>e20230376</elocation-id>
      <history>
        <date date-type="received">
          <day>08</day>
          <month>06</month>
          <year>2023</year>
        </date>
        <date date-type="rev-recd">
          <day>10</day>
          <month>09</month>
          <year>2023</year>
        </date>
        <date date-type="accepted">
          <day>25</day>
          <month>10</month>
          <year>2023</year>
        </date>
      </history>
      <permissions>
        <license license-type="open-access" xml:lang="en" xlink:href="https://creativecommons.org/licenses/by/4.0/">
          <license-p>This is an open-access article distributed under the terms of the Creative Commons Attribution License</license-p>
        </license>
      </permissions>
      <abstract>
        <title>Resumo</title>
        <sec>
          <title>Fundamento:</title>
          <p>A triagem do c&#226;ncer &#233; absolutamente necess&#225;ria em pacientes com derrame peric&#225;rdico, pois o c&#226;ncer &#233; uma das doen&#231;as mais graves em sua etiologia. Estudos anteriores indicaram que o &#237;ndice de inflama&#231;&#227;o imunol&#243;gica sist&#234;mica (IIS), o &#237;ndice progn&#243;stico nutricional (PNI) e o escore de hemoglobina, albumina, linf&#243;citos e plaquetas (HALP) podem ser escores relacionados ao c&#226;ncer.</p>
        </sec>
        <sec>
          <title>Objetivos:</title>
          <p>Este estudo foi iniciado considerando que esses sistemas de pontua&#231;&#227;o poderiam prever o c&#226;ncer na etiologia de pacientes com derrame peric&#225;rdico.</p>
        </sec>
        <sec>
          <title>M&#233;todos:</title>
          <p>Os pacientes submetidos &#224; pericardiocentese entre 2006 e 2022 foram analisados retrospectivamente. A pericardiocentese foi realizada em um total de 283 pacientes com derrame peric&#225;rdico ou tamponamento card&#237;aco de moderado a grande no per&#237;odo especificado. Os &#237;ndices de HALP, PNI e IIS foram calculados do sangue venoso perif&#233;rico retirado antes do procedimento de pericardiocentese. O n&#237;vel de signific&#226;ncia estat&#237;stica foi aceito em p&lt;0,05.</p>
        </sec>
        <sec>
          <title>Resultados:</title>
          <p>O escore HALP foi de 0,173 (0,125-0,175) em pacientes com c&#226;ncer. Detectou-se que em pacientes n&#227;o oncol&#243;gicos o escore foi de 0,32 (0,20-0,49; p&lt;0,001). O escore de PNI foi de 33,1&#177;5,6 em pacientes com c&#226;ncer. Detectou-se que em pacientes n&#227;o oncol&#243;gicos o escore foi 39,8&#177;4,8 (p&lt;0,001).</p>
        </sec>
        <sec>
          <title>Conclus&#227;o:</title>
          <p>Os escores HALP e PNI s&#227;o testes de triagem de c&#226;ncer f&#225;ceis e r&#225;pidos que podem prever met&#225;stases de c&#226;ncer na etiologia de pacientes com derrame peric&#225;rdico.</p>
        </sec>
      </abstract>
      <kwd-group xml:lang="pt">
        <title>Palavras-chave:</title>
        <kwd>C&#226;ncer</kwd>
        <kwd>Escore de hemoglobina, albumina, linf&#243;cito e plaqueta</kwd>
        <kwd>&#205;ndice Progn&#243;stico Nutricional</kwd>
        <kwd>Efus&#227;o Peric&#225;rdica</kwd>
      </kwd-group>
      <counts>
        <fig-count count="4"/>
        <table-count count="6"/>
        <equation-count count="0"/>
        <ref-count count="30"/>
      </counts>
    </article-meta>
  </front>
  <body>
    <fig id="f2">
      <graphic xlink:href="1678-4170-abc-121-01-e20230376-30376-gf01.tif"/></fig>
    <sec sec-type="intro">
      <title>Introdu&#231;&#227;o</title>
      <p>O ac&#250;mulo anormal de l&#237;quido no espa&#231;o peric&#225;rdico &#233; definido como derrame peric&#225;rdico.<sup><xref ref-type="bibr" rid="B1">1</xref></sup> Existem muitas causas de derrame peric&#225;rdico, como doen&#231;as infecciosas, autoimunes, neopl&#225;sicas, iatrog&#234;nicas, traum&#225;ticas, metab&#243;licas e card&#237;acas.<sup><xref ref-type="bibr" rid="B2">2</xref></sup></p>
      <p>O c&#226;ncer &#233; uma doen&#231;a com elevada morbidade e mortalidade. Sabe-se que a nutri&#231;&#227;o e o estado inflamat&#243;rio est&#227;o entre os fatores que determinam o progn&#243;stico em pacientes com c&#226;ncer.<sup><xref ref-type="bibr" rid="B3">3</xref></sup> Na literatura existem sistemas de pontua&#231;&#227;o como o escore de hemoglobina, albumina, linf&#243;citos e plaquetas (HALP), I o &#237;ndice de inflama&#231;&#227;o imunol&#243;gica sist&#234;mica (IIS) e o &#237;ndice progn&#243;stico nutricional (PNI), que est&#227;o associados a condi&#231;&#245;es nutricionais e inflamat&#243;rias e, portanto, podem ser preditivos de c&#226;ncer. O escore HALP, que consiste em quatro marcadores laboratoriais (hemoglobina, albumina, linf&#243;citos e plaquetas), est&#225; associado tanto &#224; nutri&#231;&#227;o quanto ao estado inflamat&#243;rio, e &#233; comumente usado como fator progn&#243;stico em pacientes com v&#225;rios tumores malignos, incluindo c&#226;ncer gastrointestinal<sup><xref ref-type="bibr" rid="B4">4</xref></sup> e c&#226;ncer geniturin&#225;rio.<sup><xref ref-type="bibr" rid="B5">5</xref></sup></p>
      <p>A intera&#231;&#227;o entre a inflama&#231;&#227;o sist&#234;mica, que &#233; uma das caracter&#237;sticas do c&#226;ncer, e a resposta imune local desempenha um papel na forma&#231;&#227;o de v&#225;rios tipos de malignidades e no curso do c&#226;ncer.<sup><xref ref-type="bibr" rid="B6">6</xref>,<xref ref-type="bibr" rid="B7">7</xref></sup> Par&#226;metros de inflama&#231;&#227;o sist&#234;mica tamb&#233;m t&#234;m sido aceitos como fatores progn&#243;sticos em tumores s&#243;lidos malignos.<sup><xref ref-type="bibr" rid="B8">8</xref></sup> O IIS, que consiste na contagem de linf&#243;citos, neutr&#243;filos e plaquetas, tem sido relatado como um fator progn&#243;stico para pacientes com alguns tumores malignos.<sup><xref ref-type="bibr" rid="B9">9</xref></sup> No c&#226;ncer colorretal<sup><xref ref-type="bibr" rid="B10">10</xref></sup> e esof&#225;gico,<sup><xref ref-type="bibr" rid="B11">11</xref></sup> a nutri&#231;&#227;o dos pacientes e os par&#226;metros inflamat&#243;rios no sangue demonstraram ser eficazes na previs&#227;o do progn&#243;stico para esses pacientes.</p>
      <p>O PNI foi usado pela primeira vez para avaliar o risco do paciente em cirurgia para doen&#231;as gastrointestinais.<sup><xref ref-type="bibr" rid="B12">12</xref></sup> O PNI, que &#233; um sistema de pontua&#231;&#227;o que consiste na combina&#231;&#227;o do n&#237;vel de albumina no soro sangu&#237;neo e na contagem de linf&#243;citos no sangue, &#233; usado para avaliar o estado nutricional e imunol&#243;gico em pacientes com c&#226;ncer.<sup><xref ref-type="bibr" rid="B13">13</xref></sup> O PNI &#233; um escore progn&#243;stico para carcinoma de es&#244;fago e osteossarcoma.<sup><xref ref-type="bibr" rid="B14">14</xref>,<xref ref-type="bibr" rid="B15">15</xref></sup></p>
      <p>Nosso objetivo mais importante neste estudo &#233; detectar rapidamente met&#225;stases de c&#226;ncer na etiologia em pacientes com derrame peric&#225;rdico, porque a doen&#231;a mais grave na etiologia dos pacientes com derrame peric&#225;rdico &#233; o c&#226;ncer. Ao investigar a etiologia em pacientes que apresentam derrame peric&#225;rdico, partimos da hip&#243;tese de que esses sistemas de pontua&#231;&#227;o, que podem ser calculados com exames laboratoriais simples, podem prever o desenvolvimento de derrame peric&#225;rdico relacionado ao c&#226;ncer. Esses sistemas de pontua&#231;&#227;o s&#227;o simples e de f&#225;cil aplica&#231;&#227;o. Se um sistema de pontua&#231;&#227;o para derrame peric&#225;rdico for eficaz na identifica&#231;&#227;o de pacientes com c&#226;ncer, ele pode acelerar o diagn&#243;stico e o tratamento do c&#226;ncer e reduzir a morbidade e a mortalidade relacionadas ao c&#226;ncer.</p>
    </sec>
    <sec sec-type="methods">
      <title>M&#233;todos</title>
      <p>Este estudo produziu uma an&#225;lise retrospectiva de pacientes submetidos &#224; pericardiocentese entre 2006 e 2022. Foi obtida a aprova&#231;&#227;o do Comit&#234; de &#233;tica da universidade local. O n&#250;mero do parecer do comit&#234; de &#233;tica foi 2022-10/11. Os pacientes e seus familiares deram o consentimento para participar do estudo. Durante o per&#237;odo mencionado, um total de 295 pacientes com derrame peric&#225;rdico de m&#233;dio a grande porte ou tamponamento card&#237;aco foram submetidos &#224; pericardiocentese com orienta&#231;&#227;o de fluoroscopia (<xref ref-type="fig" rid="f2">Figura Central</xref>). O tamanho do derrame peric&#225;rdico dos pacientes inclu&#237;dos no estudo foi classificado de acordo com a ecocardiografia como leve (&lt;10 mm), moderado (10-20 mm) ou grande (&gt;20 mm) de acordo com o sistema de classifica&#231;&#227;o.<sup><xref ref-type="bibr" rid="B16">16</xref></sup> Todos os pacientes do presente estudo eram pacientes com derrame ou tamponamento card&#237;aco moderado a grande, classificados de acordo com o tamanho. Os procedimentos de pericardiocentese percut&#226;nea foram realizados principalmente no espa&#231;o subxifoide e raramente no espa&#231;o intercostal. Os registros m&#233;dicos de cada paciente foram analisados para obter dados demogr&#225;ficos, dados cl&#237;nicos e diagn&#243;sticos de doen&#231;as. Foram registrados dados do l&#237;quido peric&#225;rdico, par&#226;metros laboratoriais, resultados patol&#243;gicos e microbiol&#243;gicos no momento da admiss&#227;o. O derrame foi classificado como maligno ou benigno. Se a citologia do l&#237;quido peric&#225;rdico mostrasse c&#233;lulas malignas e suspeitas, o derrame era classificado como maligno. Aqueles sem achados anormais na citologia do derrame peric&#225;rdico foram classificados como benignos. Posteriormente, os pacientes foram divididos em dois grupos: aqueles com diagn&#243;stico de c&#226;ncer e aqueles sem diagn&#243;stico de c&#226;ncer. Foram determinados como crit&#233;rios de exclus&#227;o: ter idade inferior a 18 anos, ter derrame peric&#225;rdico menor que 10 mm e ter taxa de filtra&#231;&#227;o glomerular (TFG) &lt;30 ml/min/m<sup>2</sup>. O diagn&#243;stico de pericardiocentese foi feito com aparelho de ecocardiografia transtor&#225;cica. Todos os pacientes foram acompanhados com ecocardiografia transtor&#225;cica antes e ap&#243;s a pericardiocentese. Exames de sangue venoso perif&#233;rico foram realizados em todos os pacientes com diagn&#243;stico de derrame peric&#225;rdico. Par&#226;metros bioqu&#237;micos (lipoprote&#237;na de alta densidade (HDL), lipoprote&#237;na de baixa densidade (LDL), prote&#237;na C reativa (PCR), creatinina, eletr&#243;litos s&#233;ricos) foram estudados a partir das amostras de sangue coletadas. O escore IIS foi calculado com a f&#243;rmula Neutr&#243;filos 10<sup>3</sup>/uL x Plaquetas 10<sup>3</sup>/uL / Linf&#243;citos 10<sup>3</sup>/uL, o escore PNI foi calculado com a f&#243;rmula (n&#237;vel s&#233;rico de albumina g/dL &#215; 10) + (linf&#243;citos 10<sup>3</sup>/uL &#215; 0,005), e o escore HALP foi calculado com a f&#243;rmula Hemoglobina g/dL x Albumina g/dL x Linf&#243;citos 10<sup>3</sup>/uL / Plaquetas 10<sup>3</sup>/uL.</p>
      <sec>
        <title>An&#225;lise estat&#237;stica</title>
        <p>Foram utilizados histograma, gr&#225;fico Q-Q e teste de Shapiro-Wilk para avaliar se os dados violavam as suposi&#231;&#245;es de normalidade. O teste T para duas amostras e o teste U de Mann Whitney foram realizados para comparar as vari&#225;veis quantitativas entre os grupos. A an&#225;lise do qui-quadrado foi utilizada para avaliar a rela&#231;&#227;o entre vari&#225;veis categ&#243;ricas. Os dados cont&#237;nuos foram apresentados como m&#233;dia &#177; desvio padr&#227;o (DP) ou mediana (1&#176; quartil &#8211; 3&#176; quartil) com base na distribui&#231;&#227;o dos dados. As vari&#225;veis categ&#243;ricas foram expressas como n&#250;mero (n) com percentual (%). A an&#225;lise de regress&#227;o log&#237;stica foi utilizada para determinar os fatores de risco que afetam o status do c&#226;ncer. As vari&#225;veis que foram consideradas estatisticamente significativas como resultado da an&#225;lise de regress&#227;o log&#237;stica foram avaliadas com an&#225;lise de regress&#227;o log&#237;stica m&#250;ltipla. A an&#225;lise de caracter&#237;stica operacional do receptor (ROC) foi realizada para avaliar os escores HALP e PNI na previs&#227;o de c&#226;ncer. A &#225;rea sob a curva (AUC) e o valor de corte foram calculados para cada valor do escore. A sensibilidade e a especificidade foram calculadas para avaliar o desempenho do teste diagn&#243;stico de cada escore. O n&#237;vel de signific&#226;ncia estat&#237;stica foi aceito em p&lt;0,05. A an&#225;lise dos dados foi realizada no software estat&#237;stico SPSS 22.</p>
      </sec>
    </sec>
    <sec sec-type="results">
      <title>Resultados</title>
      <p>A pericardiocentese foi realizada em 295 pacientes entre 2006 e 2022. Doze pacientes foram exclu&#237;dos do estudo por falta de par&#226;metros sangu&#237;neos. Os demais 283 pacientes foram inclu&#237;dos no estudo. Enquanto 29 dos 84 pacientes submetidos &#224; pericardiocentese tinham diagn&#243;stico pr&#233;vio de c&#226;ncer, 55 pacientes foram diagnosticados com c&#226;ncer no per&#237;odo de 6 meses ap&#243;s a pericardiocentese. A doen&#231;a mais comum em pacientes oncol&#243;gicos foi o c&#226;ncer de pulm&#227;o, enquanto o c&#226;ncer de mama ficou em segundo lugar (<xref ref-type="table" rid="t1">Tabela 1</xref>).</p>
      <table-wrap id="t1">
        <label>Tabela 1</label>
        <caption>
          <title>Distribui&#231;&#227;o de pacientes com diagn&#243;stico de c&#226;ncer</title>
        </caption>
        <table frame="hsides" rules="none">
          <colgroup width="50%">
            <col/>
            <col/>
          </colgroup>
          <thead style="border-top: thin solid; border-bottom: thin solid; border-color: #000000">
            <tr style="background-color:#76B4CF">
              <th valign="middle" align="left">Tipo de c&#226;ncer</th>
              <th valign="middle" align="center">N&#250;mero de pacientes (n: 84)(%)</th>
            </tr>
          </thead>
          <tbody style="border-bottom: thin solid; border-color: #000000">
            <tr>
              <td valign="middle" align="left">C&#226;ncer de pulm&#227;o</td>
              <td valign="middle" align="center">45 (% 53,57)</td>
            </tr>
            <tr style="background-color:#C7DFEC">
              <td valign="middle" align="left">C&#226;ncer de mama</td>
              <td valign="middle" align="center">11 (% 13)</td>
            </tr>
            <tr>
              <td valign="middle" align="left">C&#226;ncer g&#225;strico</td>
              <td valign="middle" align="center">8 (% 9,52)</td>
            </tr>
            <tr style="background-color:#C7DFEC">
              <td valign="middle" align="left">Leucemia</td>
              <td valign="middle" align="center">4 (% 4,76)</td>
            </tr>
            <tr>
              <td valign="middle" align="left">C&#226;ncer de pr&#243;stata</td>
              <td valign="middle" align="center">4 (% 4,76)</td>
            </tr>
            <tr style="background-color:#C7DFEC">
              <td valign="middle" align="left">Linfoma</td>
              <td valign="middle" align="center">3 (% 3,57)</td>
            </tr>
            <tr>
              <td valign="middle" align="left">C&#226;ncer renal</td>
              <td valign="middle" align="center">2 (% 2,38)</td>
            </tr>
            <tr style="background-color:#C7DFEC">
              <td valign="middle" align="left">C&#226;ncer de colo</td>
              <td valign="middle" align="center">2 (% 2,38)</td>
            </tr>
            <tr>
              <td valign="middle" align="left">C&#226;ncer de test&#237;culo</td>
              <td valign="middle" align="center">2 (% 2,38)</td>
            </tr>
            <tr style="background-color:#C7DFEC">
              <td valign="middle" align="left">C&#226;ncer de bexiga</td>
              <td valign="middle" align="center">1 (% 1,19)</td>
            </tr>
            <tr>
              <td valign="middle" align="left">C&#226;ncer de tecidos moles</td>
              <td valign="middle" align="center">1 (% 1,19)</td>
            </tr>
            <tr style="background-color:#C7DFEC">
              <td valign="middle" align="left">C&#226;ncer de tireoide</td>
              <td valign="middle" align="center">1 (% 1,19)</td>
            </tr>
          </tbody>
        </table>
      </table-wrap>
      <p>A incid&#234;ncia de c&#226;ncer foi maior no sexo masculino. Entre os par&#226;metros laboratoriais comparados, os valores de hemoglobina, albumina e linf&#243;citos foram encontrados em n&#237;veis mais baixos em pacientes com c&#226;ncer, enquanto o valor de PCR foi encontrado em n&#237;veis mais elevados. Na compara&#231;&#227;o entre os sistemas de pontua&#231;&#227;o, os escores HALP e PNI foram menores em pacientes com c&#226;ncer, enquanto o valor do IIS foi maior. N&#227;o houve diferen&#231;a significativa entre os dois grupos, exceto nos par&#226;metros sexo, hemoglobina, albumina, linf&#243;citos, PCR, HALP, IIS e PNI (<xref ref-type="table" rid="t2">Tabela 2</xref>).</p>
      <table-wrap id="t2">
        <label>Tabela 2</label>
        <caption>
          <title>Compara&#231;&#227;o do estado do c&#226;ncer e diversas vari&#225;veis</title>
        </caption>
        <table frame="hsides" rules="none">
          <colgroup width="24%">
            <col width="1%"/>
            <col/>
            <col/>
            <col/>
            <col/>
          </colgroup>
          <thead style="border-top: thin solid; border-bottom: thin solid; border-color: #000000">
            <tr style="background-color:#76B4CF">
              <th valign="middle" align="left" colspan="2" rowspan="2">Vari&#225;veis</th>
              <th valign="middle" align="center" colspan="2" style="border-bottom: thin solid; border-top: thin solid; border-color: #000000">C&#226;ncer</th>
              <th valign="middle" align="left" rowspan="2">p-valor</th>
            </tr>
            <tr style="background-color:#76B4CF">
              <th valign="middle" align="center">N&#227;o<break/> (n=199)</th>
              <th valign="middle" align="center">Sim<break/> (n=84)</th>
            </tr>
          </thead>
          <tbody style="border-bottom: thin solid; border-color: #000000">
            <tr>
              <td valign="middle" align="left" colspan="2">Idade (anos)</td>
              <td valign="middle" align="center">63&#177;15,9</td>
              <td valign="middle" align="center">60,6&#177;16</td>
              <td valign="middle" align="center">0,26</td>
            </tr>
            <tr style="background-color:#C7DFEC">
              <td valign="middle" align="left" colspan="2">Sexo, n (%)</td>
              <td valign="middle" align="center"/>
              <td valign="middle" align="center"/>
              <td valign="middle" align="center"/>
            </tr>
            <tr style="background-color:#C7DFEC">
              <td valign="middle" align="left"/>
              <td valign="middle" align="left">Feminino</td>
              <td valign="middle" align="center">114 (57,2)</td>
              <td valign="middle" align="center">36 (42,8)</td>
              <td valign="middle" align="center">0,028</td>
            </tr>
            <tr style="background-color:#C7DFEC">
              <td valign="middle" align="left"/>
              <td valign="middle" align="left">Masculino</td>
              <td valign="middle" align="center">85 (42,8)</td>
              <td valign="middle" align="center">48 (57,2)</td>
              <td valign="middle" align="center"/>
            </tr>
            <tr>
              <td valign="middle" align="left" colspan="2">FEVE (%)</td>
              <td valign="middle" align="center">50,7&#177;12,8</td>
              <td valign="middle" align="center">51&#177;13,4</td>
              <td valign="middle" align="center">0,64</td>
            </tr>
            <tr style="background-color:#C7DFEC">
              <td valign="middle" align="left" colspan="2">HT, n(%)</td>
              <td valign="middle" align="center">47 (23,6)</td>
              <td valign="middle" align="center">16 (19)</td>
              <td valign="middle" align="center">0,44</td>
            </tr>
            <tr>
              <td valign="middle" align="left" colspan="2">DAC, n (%)</td>
              <td valign="middle" align="center">14(7)</td>
              <td valign="middle" align="center">3 (3,6)</td>
              <td valign="middle" align="center">0,411</td>
            </tr>
            <tr style="background-color:#C7DFEC">
              <td valign="middle" align="left" colspan="2">Hemoglobina (g/dL)</td>
              <td valign="middle" align="center">13,1&#177;1,9</td>
              <td valign="middle" align="center">11&#177;1,7</td>
              <td valign="middle" align="center">&lt;0,001</td>
            </tr>
            <tr>
              <td valign="middle" align="left" colspan="2">RBC (10<sup>6</sup>/uL)</td>
              <td valign="middle" align="center">4,45&#177;0,79</td>
              <td valign="middle" align="center">4,29&#177;0,82</td>
              <td valign="middle" align="center">0,14</td>
            </tr>
            <tr style="background-color:#C7DFEC">
              <td valign="middle" align="left" colspan="2">WBC (10<sup>3</sup>/uL)</td>
              <td valign="middle" align="center">9,3&#177;4,3</td>
              <td valign="middle" align="center">8,6&#177;4,7</td>
              <td valign="middle" align="center">0,2</td>
            </tr>
            <tr>
              <td valign="middle" align="left" colspan="2">LDL (mg/dL)</td>
              <td valign="middle" align="center">97,2&#177;40</td>
              <td valign="middle" align="center">90,7&#177;38,2</td>
              <td valign="middle" align="center">0,25</td>
            </tr>
            <tr style="background-color:#C7DFEC">
              <td valign="middle" align="left" colspan="2">HDL (mg/dL)</td>
              <td valign="middle" align="center">35,9&#177;14,8</td>
              <td valign="middle" align="center">34&#177;14,3</td>
              <td valign="middle" align="center">0,35</td>
            </tr>
            <tr>
              <td valign="middle" align="left" colspan="2">DM, n (%)</td>
              <td valign="middle" align="center">33 (18,0)</td>
              <td valign="middle" align="center">8 (11,3)</td>
              <td valign="middle" align="center">0,138</td>
            </tr>
            <tr style="background-color:#C7DFEC">
              <td valign="middle" align="left" colspan="2">&#193;cido &#250;rico (mg/dL)</td>
              <td valign="middle" align="center">6,27&#177;2,4</td>
              <td valign="middle" align="center">6,15&#177;2,3</td>
              <td valign="middle" align="center">0,76</td>
            </tr>
            <tr>
              <td valign="middle" align="left" colspan="2">NUS (mg/dL)</td>
              <td valign="middle" align="center">20,4&#177;14,6</td>
              <td valign="middle" align="center">19,7&#177;11,7</td>
              <td valign="middle" align="center">0,672</td>
            </tr>
            <tr style="background-color:#C7DFEC">
              <td valign="middle" align="left" colspan="2">Creatinina (mg/dL)</td>
              <td valign="middle" align="center">0,8 (0,7-1,0)</td>
              <td valign="middle" align="center">0,9 (0,7-1,0)</td>
              <td valign="middle" align="center">0,128</td>
            </tr>
            <tr>
              <td valign="middle" align="left" colspan="2">TFG (ml/min/m&#178;)</td>
              <td valign="middle" align="center">79,7&#177;21,9</td>
              <td valign="middle" align="center">83,2&#177;17,4</td>
              <td valign="middle" align="center">0,15</td>
            </tr>
            <tr style="background-color:#C7DFEC">
              <td valign="middle" align="left" colspan="2">BASO (10<sup>3</sup>/uL)</td>
              <td valign="middle" align="center">0,02 (0,01-0,04)</td>
              <td valign="middle" align="center">0,02 (0,01-0,05)</td>
              <td valign="middle" align="center">0,16</td>
            </tr>
            <tr>
              <td valign="middle" align="left" colspan="2">EO (10<sup>3</sup>/uL)</td>
              <td valign="middle" align="center">0,08 (0,01-0,18)</td>
              <td valign="middle" align="center">0,07 (0,02-0,16)</td>
              <td valign="middle" align="center">0,78</td>
            </tr>
            <tr style="background-color:#C7DFEC">
              <td valign="middle" align="left" colspan="2">HCT (%)</td>
              <td valign="middle" align="center">38,3&#177;5,9</td>
              <td valign="middle" align="center">37,4&#177;7</td>
              <td valign="middle" align="center">0,271</td>
            </tr>
            <tr>
              <td valign="middle" align="left" colspan="2">HCM</td>
              <td valign="middle" align="center">28,3&#177;4,7</td>
              <td valign="middle" align="center">28,3&#177;2,6</td>
              <td valign="middle" align="center">0,91</td>
            </tr>
            <tr style="background-color:#C7DFEC">
              <td valign="middle" align="left" colspan="2">VCM (fL)</td>
              <td valign="middle" align="center">85,8&#177;8,10</td>
              <td valign="middle" align="center">86,8&#177;8,1</td>
              <td valign="middle" align="center">0,61</td>
            </tr>
            <tr>
              <td valign="middle" align="left" colspan="2">MONO (10<sup>3</sup>/uL)</td>
              <td valign="middle" align="center">0,55 (0,40-0,80)</td>
              <td valign="middle" align="center">0,55 (0,38-0,80)</td>
              <td valign="middle" align="center">0,37</td>
            </tr>
            <tr style="background-color:#C7DFEC">
              <td valign="middle" align="left" colspan="2">VPM (fL)</td>
              <td valign="middle" align="center">9,3&#177;1,26</td>
              <td valign="middle" align="center">9,3&#177;1,46</td>
              <td valign="middle" align="center">0,34</td>
            </tr>
            <tr>
              <td valign="middle" align="left" colspan="2">NEUT (10<sup>3</sup>/uL)</td>
              <td valign="middle" align="center">7,4&#177;4,6</td>
              <td valign="middle" align="center">7,2&#177;4,4</td>
              <td valign="middle" align="center">0,69</td>
            </tr>
            <tr style="background-color:#C7DFEC">
              <td valign="middle" align="left" colspan="2">PCT (%)</td>
              <td valign="middle" align="center">0,24&#177;0,11</td>
              <td valign="middle" align="center">0,23&#177;0,15</td>
              <td valign="middle" align="center">0,36</td>
            </tr>
            <tr>
              <td valign="middle" align="left" colspan="2">PDW (%)</td>
              <td valign="middle" align="center">19,55&#177;11,6</td>
              <td valign="middle" align="center">18,2&#177;10,3</td>
              <td valign="middle" align="center">0,37</td>
            </tr>
            <tr style="background-color:#C7DFEC">
              <td valign="middle" align="left" colspan="2">RDW (%)</td>
              <td valign="middle" align="center">15,5&#177;2,6</td>
              <td valign="middle" align="center">15,5&#177;2,6</td>
              <td valign="middle" align="center">0,37</td>
            </tr>
            <tr>
              <td valign="middle" align="left" colspan="2">Albumina (mg/dL)</td>
              <td valign="middle" align="center">3,92&#177;0,45</td>
              <td valign="middle" align="center">3,3&#177;0,56</td>
              <td valign="middle" align="center">&lt;0,001</td>
            </tr>
            <tr style="background-color:#C7DFEC">
              <td valign="middle" align="left" colspan="2">Linf&#243;citos (10<sup>3</sup>/uL)</td>
              <td valign="middle" align="center">1,84&#177;0,66</td>
              <td valign="middle" align="center">1,29&#177;0,81</td>
              <td valign="middle" align="center">&lt;0,001</td>
            </tr>
            <tr>
              <td valign="middle" align="left" colspan="2">Plaquetas (10<sup>3</sup>/uL)</td>
              <td valign="middle" align="center">234&#177;88,7</td>
              <td valign="middle" align="center">259,7&#177;122,00</td>
              <td valign="middle" align="center">0,095</td>
            </tr>
            <tr style="background-color:#C7DFEC">
              <td valign="middle" align="left" colspan="2">Colesterol total</td>
              <td valign="middle" align="center">162,4&#177;52,00</td>
              <td valign="middle" align="center">152,6&#177;47,8</td>
              <td valign="middle" align="center">0,18</td>
            </tr>
            <tr>
              <td valign="middle" align="left" colspan="2">PCR (mg/dL)</td>
              <td valign="middle" align="center">24,7 (8,4-81,2)</td>
              <td valign="middle" align="center">56,0 (15,0-119,0)</td>
              <td valign="middle" align="center">0,006</td>
            </tr>
            <tr style="background-color:#C7DFEC">
              <td valign="middle" align="left" colspan="2">HALP</td>
              <td valign="middle" align="center">0,32 (0,20-0,49)</td>
              <td valign="middle" align="center">0,173 (0,125-0,175)</td>
              <td valign="middle" align="center">&lt;0,001</td>
            </tr>
            <tr>
              <td valign="middle" align="left" colspan="2">IIS</td>
              <td valign="middle" align="center">857,8 (528-1664)</td>
              <td valign="middle" align="center">1329,8 (697-2272,2)</td>
              <td valign="middle" align="center">&lt;0,001</td>
            </tr>
            <tr style="background-color:#C7DFEC">
              <td valign="middle" align="left" colspan="2">PNI</td>
              <td valign="middle" align="center">39,8&#177;4,8</td>
              <td valign="middle" align="center">33,1&#177;5,6</td>
              <td valign="middle" align="center">&lt;0,001</td>
            </tr>
          </tbody>
        </table>
        <table-wrap-foot>
          <fn id="TFN1">
            <p>Os dados est&#227;o expressos em n (%), m&#233;dia &#177; desvio padr&#227;o, mediana (1&#176; quartil - 3&#176; quartil). FEVE: fra&#231;&#227;o de eje&#231;&#227;o ventricular esquerda; HT: hipertens&#227;o; DAC: doen&#231;a arterial coronariana; RBC: hem&#225;cias; WBC: leuc&#243;citos; LDL: lipoprote&#237;na de baixa densidade; HDL: lipoprote&#237;na de alta densidade; DM: diabetes mellitus; NUS: nitrog&#234;nio ureico no sangue; TFG: taxa de filtra&#231;&#227;o glomerular; BASO: bas&#243;filos; EO: eosin&#243;filos; HCT: hemat&#243;critos; HCM: hemoglobina corpuscular m&#233;dia; VCM: volume corpuscular m&#233;dio; MONO: mon&#243;citos; VPM: volume plaquet&#225;rio m&#233;dio; NEUT: neutr&#243;filos; PCT: procalcitonina; PDW: amplitude de distribui&#231;&#227;o de plaquetas; RDW: amplitude de distribui&#231;&#227;o de hem&#225;cias; PCR: prote&#237;na C-reativa; IIS: &#237;ndice de inflama&#231;&#227;o imune sist&#234;mica; PNI: &#237;ndice progn&#243;stico nutricional.</p>
          </fn>
        </table-wrap-foot>
      </table-wrap>
      <p>Na an&#225;lise de regress&#227;o log&#237;stica m&#250;ltipla, o HALP e o PNI foram preditores independentes de met&#225;stase de c&#226;ncer em pacientes com derrame peric&#225;rdico (<xref ref-type="table" rid="t3">Tabela 3</xref>).</p>
      <table-wrap id="t3">
        <label>Tabela 3</label>
        <caption>
          <title>Avalia&#231;&#227;o de fatores de risco que podem afetar o status definitivo do c&#226;ncer</title>
        </caption>
        <table frame="hsides" rules="none">
          <colgroup width="19%">
            <col width="1%"/>
            <col/>
            <col/>
            <col/>
            <col/>
            <col/>
          </colgroup>
          <thead style="border-top: thin solid; border-bottom: thin solid; border-color: #000000">
            <tr style="background-color:#76B4CF">
              <th valign="middle" align="left" colspan="2" rowspan="3">Vari&#225;veis</th>
              <th valign="middle" align="center" colspan="4" style="border-bottom: thin solid; border-top: thin solid; border-color: #000000">C&#226;ncer</th>
            </tr>
            <tr style="background-color:#76B4CF">
              <th valign="middle" align="center" colspan="2">An&#225;lises univariadas</th>
              <th valign="middle" align="center" colspan="2">An&#225;lises multivariadas</th>
            </tr>
            <tr style="background-color:#76B4CF">
              <th valign="middle" align="center">Raz&#227;o de chance (IC 95%)</th>
              <th valign="middle" align="center">p</th>
              <th valign="middle" align="center">Raz&#227;o de chance (IC 95%)</th>
              <th valign="middle" align="center">p</th>
            </tr>
          </thead>
          <tbody style="border-bottom: thin solid; border-color: #000000">
            <tr>
              <td valign="middle" align="left" colspan="2">Sexo, n (%)</td>
              <td valign="middle" align="center"/>
              <td valign="middle" align="center"/>
              <td valign="middle" align="center"/>
              <td valign="middle" align="center" rowspan="3"/>
            </tr>
            <tr>
              <td valign="middle" align="left"/>
              <td valign="middle" align="left">Feminino</td>
              <td valign="middle" align="center">1</td>
              <td valign="middle" align="center">0,027</td>
              <td valign="middle" align="center"/>
            </tr>
            <tr>
              <td valign="middle" align="left"/>
              <td valign="middle" align="left">Masculino</td>
              <td valign="middle" align="center">1,788 (1,068-2,994)</td>
              <td valign="middle" align="center"/>
              <td valign="middle" align="center"/>
            </tr>
            <tr style="background-color:#C7DFEC">
              <td valign="middle" align="left" colspan="2">Hemoglobina (g/dL)</td>
              <td valign="middle" align="center">0,514 (0,427-0,619)</td>
              <td valign="middle" align="center">&lt;0,001</td>
              <td valign="middle" align="center"/>
              <td valign="middle" align="center"/>
            </tr>
            <tr>
              <td valign="middle" align="left" colspan="2">Albumina (mg/dL)</td>
              <td valign="middle" align="center">0,066 (0,027-0,158)</td>
              <td valign="middle" align="center">&lt;0,001</td>
              <td valign="middle" align="center"/>
              <td valign="middle" align="center"/>
            </tr>
            <tr style="background-color:#C7DFEC">
              <td valign="middle" align="left" colspan="2">Linf&#243;citos (10<sup>3</sup>/uL)</td>
              <td valign="middle" align="center">0,318 (0,174-0,583)</td>
              <td valign="middle" align="center">&lt;0,001</td>
              <td valign="middle" align="center"/>
              <td valign="middle" align="center"/>
            </tr>
            <tr>
              <td valign="middle" align="left" colspan="2">HALP</td>
              <td valign="middle" align="center">0,003 (0,001-0,041)</td>
              <td valign="middle" align="center">&lt;0,001</td>
              <td valign="middle" align="center">0,006 (0,001-0,090)</td>
              <td valign="middle" align="center">&lt;0,001</td>
            </tr>
            <tr style="background-color:#C7DFEC">
              <td valign="middle" align="left" colspan="2">PNI</td>
              <td valign="middle" align="center">0,831 (0,773-0,894)</td>
              <td valign="middle" align="center">&lt;0,001</td>
              <td valign="middle" align="center">0,825 (0,763-0,893)</td>
              <td valign="middle" align="center">&lt;0,001</td>
            </tr>
            <tr>
              <td valign="middle" align="left" colspan="2">Idade (anos)</td>
              <td valign="middle" align="center">991 (975-1007)</td>
              <td valign="middle" align="center">0,262</td>
              <td valign="middle" align="center"/>
              <td valign="middle" align="center"/>
            </tr>
            <tr style="background-color:#C7DFEC">
              <td valign="middle" align="left" colspan="2">DM, n (%)</td>
              <td valign="middle" align="center">515 (227-1172)</td>
              <td valign="middle" align="center">0,114</td>
              <td valign="middle" align="center"/>
              <td valign="middle" align="center"/>
            </tr>
            <tr>
              <td valign="middle" align="left" colspan="2">Creatinina (mg/dL)</td>
              <td valign="middle" align="center">848 (646-1113)</td>
              <td valign="middle" align="center">0,236</td>
              <td valign="middle" align="center"/>
              <td valign="middle" align="center"/>
            </tr>
            <tr style="background-color:#C7DFEC">
              <td valign="middle" align="left" colspan="2">Plaquetas (10<sup>3</sup>/uL)</td>
              <td valign="middle" align="center">1002 (1000-1005)</td>
              <td valign="middle" align="center">0,059</td>
              <td valign="middle" align="center"/>
              <td valign="middle" align="center"/>
            </tr>
            <tr>
              <td valign="middle" align="left" colspan="2">PCR (mg/dL)</td>
              <td valign="middle" align="center">1005 (1002-1009)</td>
              <td valign="middle" align="center">0,004</td>
              <td valign="middle" align="center"/>
              <td valign="middle" align="center"/>
            </tr>
            <tr style="background-color:#C7DFEC">
              <td valign="middle" align="left" colspan="2">IIS</td>
              <td valign="middle" align="center">1000 (1000-1001)</td>
              <td valign="middle" align="center">&lt;0,001</td>
              <td valign="middle" align="center"/>
              <td valign="middle" align="center"/>
            </tr>
          </tbody>
        </table>
        <table-wrap-foot>
          <fn id="TFN2">
            <p>IC: intervalo de confian&#231;a; HALP: escore de hemoglobina, albumina, linf&#243;cito e plaqueta; PNI: &#237;ndice progn&#243;stico nutricional; DM: diabetes mellitus; PCR: prote&#237;na C reativa; IIS: &#237;ndice de inflama&#231;&#227;o imunol&#243;gica sist&#234;mica.</p>
          </fn>
        </table-wrap-foot>
      </table-wrap>
      <p>A an&#225;lise ROC foi realizada para encontrar os valores de corte ideais de HALP e PNI para prever met&#225;stase de c&#226;ncer em pacientes com derrame peric&#225;rdico. Um valor HALP &lt;0,2524 tem sensibilidade de 80% e especificidade de 81,4% para prever met&#225;stases de c&#226;ncer em pacientes com derrame peric&#225;rdico. Um valor de PNI &lt;36,18 tem sensibilidade de 74% e especificidade de 74,9% na previs&#227;o de met&#225;stase de c&#226;ncer em pacientes com derrame peric&#225;rdico. A AUC do HALP foi maior que a AUC do PNI na previs&#227;o de met&#225;stase de c&#226;ncer em pacientes com derrame peric&#225;rdico (<xref ref-type="fig" rid="f1">Figura 1</xref>).</p>
      <fig id="f1">
        <label>Figura 1</label>
        <caption>
          <title>Gr&#225;ficos ROC dos escores HALP e PNI. HALP: escore de hemoglobina, albumina, linf&#243;cito e plaqueta; PNI: &#237;ndice progn&#243;stico nutricional.</title>
        </caption>
        <graphic xlink:href="1678-4170-abc-121-01-e20230376-30376-gf02.tif"/></fig>
    </sec>
    <sec sec-type="discussion">
      <title>Discuss&#227;o</title>
      <p>At&#233; onde sabemos, este &#233; o primeiro estudo a comparar os escores HALP, IIS e PNI na pesquisa do c&#226;ncer em pacientes com derrame peric&#225;rdico submetidos &#224; pericardiocentese e a observar o efeito desses sistemas de pontua&#231;&#227;o no desenvolvimento do c&#226;ncer. Neste estudo, descobriu-se que o HALP tem maior poder preditivo de met&#225;stase de c&#226;ncer do que o PNI e o IIS. O HALP pode ser usado para prever o c&#226;ncer em pacientes submetidos a pesquisas sobre c&#226;ncer, porque &#233; um biomarcador f&#225;cil, r&#225;pido e eficiente. O escore HALP em c&#226;nceres gastrointestinais, incluindo c&#226;ncer g&#225;strico,<sup><xref ref-type="bibr" rid="B17">17</xref></sup> c&#226;ncer de c&#233;lulas escamosas de es&#244;fago,<sup><xref ref-type="bibr" rid="B18">18</xref></sup> c&#226;ncer colorretal avan&#231;ado,<sup><xref ref-type="bibr" rid="B4">4</xref></sup> bem como em c&#226;nceres geniturin&#225;rios, incluindo c&#226;ncer de bexiga,<sup><xref ref-type="bibr" rid="B5">5</xref></sup> carcinoma de c&#233;lulas renais,<sup><xref ref-type="bibr" rid="B19">19</xref></sup> demonstrou ter um papel progn&#243;stico. &#201; tamb&#233;m um &#237;ndice muito abrangente que mostra o estado nutricional e imunol&#243;gico dos pacientes. Estudos anteriores demonstraram que um alto escore HALP em outros tumores prediz bons desfechos terap&#234;uticos e progn&#243;sticos.<sup><xref ref-type="bibr" rid="B4">4</xref>,<xref ref-type="bibr" rid="B17">17</xref>,<xref ref-type="bibr" rid="B19">19</xref></sup></p>
      <p>Os escores HALP e PNI t&#234;m desempenho diagn&#243;stico bastante semelhante na determina&#231;&#227;o do status de met&#225;stase do c&#226;ncer, mas o escore HALP parece ser mais forte que o PNI. Muitos estudos mostraram que o PNI desempenha um papel no progn&#243;stico do c&#226;ncer.<sup><xref ref-type="bibr" rid="B13">13</xref></sup> A raz&#227;o mais importante pela qual o PNI pode apresentar uma previs&#227;o confi&#225;vel para o progn&#243;stico em pacientes com c&#226;ncer &#233; que os linf&#243;citos ajudam o sistema imunol&#243;gico e impedem a prolifera&#231;&#227;o e a met&#225;stase nas c&#233;lulas cancer&#237;genas.<sup><xref ref-type="bibr" rid="B13">13</xref></sup> A albumina s&#233;rica, outro componente do PNI, pode prever o progn&#243;stico ao refletir o estado nutricional do organismo, fator determinante nas rea&#231;&#245;es imunol&#243;gicas das c&#233;lulas cancer&#237;genas.<sup><xref ref-type="bibr" rid="B13">13</xref></sup> Em muitos estudos, o PNI de baixo n&#237;vel tem sido associado a desfechos como c&#226;ncer com caracter&#237;sticas tumorais negativas no c&#226;ncer de pulm&#227;o, c&#226;ncer pouco diferenciado, c&#226;ncer de grande porte e met&#225;stase.<sup><xref ref-type="bibr" rid="B20">20</xref></sup> Demonstrou-se que, quanto menor o n&#237;vel de PNI, mais agressivo e pior o progn&#243;stico do c&#226;ncer de pulm&#227;o.<sup><xref ref-type="bibr" rid="B21">21</xref></sup> Em nosso estudo, o n&#237;vel de PNI foi baixo em pacientes com met&#225;stase de c&#226;ncer.</p>
      <p>Entre os fatores mais importantes na via de inflama&#231;&#227;o do c&#226;ncer est&#227;o as quimiocinas e citocinas, pequenas prote&#237;nas inflamat&#243;rias que possibilitam a comunica&#231;&#227;o intracelular no microambiente tumoral. A conex&#227;o e a comunica&#231;&#227;o entre c&#233;lulas s&#227;o muito importantes para invas&#227;o, angiog&#234;nese, crescimento tumoral e met&#225;stase. Al&#233;m disso, a necrose tumoral e a ativa&#231;&#227;o do fator de transcri&#231;&#227;o mediada por citocinas t&#234;m pap&#233;is importantes.<sup><xref ref-type="bibr" rid="B6">6</xref></sup> O processo inflamat&#243;rio no derrame peric&#225;rdico ocorre independentemente do processo patol&#243;gico. Consequentemente, a produ&#231;&#227;o de fluido na &#225;rea peric&#225;rdica aumenta. O IIS nos mostra o equil&#237;brio entre o inflamat&#243;rio e o imune.<sup><xref ref-type="bibr" rid="B22">22</xref></sup> O IIS revelou-se um &#237;ndice promissor para carcinoma hepatocelular, c&#226;ncer g&#225;strico, c&#226;ncer do pulm&#227;o de pequenas c&#233;lulas e c&#226;ncer de pr&#243;stata.<sup><xref ref-type="bibr" rid="B23">23</xref></sup> Um alto n&#237;vel de IIS indica altera&#231;&#245;es que favorecem o in&#237;cio, a progress&#227;o e a met&#225;stase do c&#226;ncer em pacientes oncol&#243;gicos.<sup><xref ref-type="bibr" rid="B8">8</xref></sup> Isso pode ser explicado pelo fato de os n&#237;veis de IIS do grupo dos pacientes com c&#226;ncer serem mais elevados do que os pacientes do grupo sem c&#226;ncer.</p>
      <p>Em nosso estudo, o c&#226;ncer mais comum que causou derrame peric&#225;rdico foi o c&#226;ncer de pulm&#227;o, seguido pelo c&#226;ncer de mama e o de est&#244;mago. Em todo o mundo, o c&#226;ncer de pr&#243;stata e colorretal em homens e o c&#226;ncer de mama e colorretal em mulheres s&#227;o comuns, assim como &#233; o c&#226;ncer de pulm&#227;o. Por&#233;m, observou-se que esses tipos de c&#226;ncer n&#227;o causavam tanto derrame peric&#225;rdico quanto o c&#226;ncer de pulm&#227;o. Isso pode estar relacionado ao fato de o c&#226;ncer de pulm&#227;o metastatizar mais para o peric&#225;rdio.<sup><xref ref-type="bibr" rid="B21">21</xref></sup> Al&#233;m disso, neste estudo, a propor&#231;&#227;o do sexo masculino foi maior entre os pacientes com c&#226;ncer. De acordo com o relat&#243;rio Global Cancer Statistics, a incid&#234;ncia e as taxas de mortalidade por c&#226;ncer de pulm&#227;o s&#227;o aproximadamente 2 vezes maiores em homens do que em mulheres.<sup><xref ref-type="bibr" rid="B21">21</xref></sup> Conforme os dados obtidos do Projeto Mapa do C&#226;ncer de Pulm&#227;o da Turquia, 90,4% dos pacientes com c&#226;ncer de pulm&#227;o s&#227;o do sexo masculino.<sup><xref ref-type="bibr" rid="B24">24</xref></sup> O fato de o c&#226;ncer de pulm&#227;o ser mais comum em homens pode explicar o alto &#237;ndice de c&#226;ncer em homens em nosso estudo. Al&#233;m disso, o baixo n&#250;mero de pessoas diagnosticadas com c&#226;ncer pode ter feito com que nossos resultados fossem assim. Portanto, s&#227;o necess&#225;rios grandes estudos com altos n&#250;meros de pacientes.</p>
      <p>A anemia, que est&#225; entre as comorbidades relacionadas ao c&#226;ncer, &#233; frequentemente observada no momento do diagn&#243;stico<sup><xref ref-type="bibr" rid="B25">25</xref></sup> e geralmente &#233; causada por inflama&#231;&#227;o cr&#244;nica associada ao c&#226;ncer.<sup><xref ref-type="bibr" rid="B26">26</xref></sup> Em nosso estudo, o baixo n&#237;vel de hemoglobina em pacientes diagnosticado com c&#226;ncer pode ser explicado por inflama&#231;&#227;o cr&#244;nica. Entretanto, como a etiologia da anemia em pacientes oncol&#243;gicos n&#227;o foi investigado em detalhes, os casos de hemoglobina baixa ainda n&#227;o foram bem esclarecidos.</p>
      <p>Em pacientes com c&#226;ncer, a hipoalbuminemia tem sido associada a uma rea&#231;&#227;o inflamat&#243;ria sist&#234;mica e &#224; desnutri&#231;&#227;o dos pacientes.<sup><xref ref-type="bibr" rid="B27">27</xref></sup> N&#237;veis aumentados de PCR t&#234;m sido associados &#224; diminui&#231;&#227;o da resposta dos linf&#243;citos T &#224;s c&#233;lulas cancer&#237;genas.<sup><xref ref-type="bibr" rid="B28">28</xref></sup> Neste estudo, os valores altos de PCR e baixos de albumina em pacientes oncol&#243;gicos podem ser explicados dessa forma.</p>
      <p>Estudos recentes mostram-nos que uma resposta inflamat&#243;ria sist&#234;mica pode desempenhar um papel importante no desenvolvimento e progress&#227;o do c&#226;ncer.<sup><xref ref-type="bibr" rid="B29">29</xref></sup> A inflama&#231;&#227;o sist&#234;mica relacionada ao c&#226;ncer causa linfopenia nos pacientes.<sup><xref ref-type="bibr" rid="B30">30</xref></sup> &#201; assim que podemos explicar os baixos n&#237;veis de linf&#243;citos nos pacientes com c&#226;ncer no presente estudo.</p>
      <sec>
        <title>Limita&#231;&#245;es</title>
        <p>Este estudo tem v&#225;rias limita&#231;&#245;es. &#201; um estudo retrospectivo. Portanto, n&#227;o seria poss&#237;vel comentar o progn&#243;stico porque os pacientes n&#227;o foram acompanhados. S&#227;o necess&#225;rios mais estudos multic&#234;ntricos em larga escala com acompanhamento para definir o papel do HALP e do PNI na fisiopatologia do c&#226;ncer. Embora este estudo tenha identificado a associa&#231;&#227;o entre esses escores e derrame peric&#225;rdico maligno, esses escores t&#234;m como objetivo determinar o progn&#243;stico naqueles que j&#225; foram diagnosticados com c&#226;ncer. Esses scores podem ser elevados em qualquer doen&#231;a cr&#244;nica, e isso pode levar a resultados enganosos.</p>
      </sec>
    </sec>
    <sec sec-type="conclusions">
      <title>Conclus&#227;o</title>
      <p>O HALP e o PNI s&#227;o sistemas de pontua&#231;&#227;o com alto poder preditivo de met&#225;stases de c&#226;ncer. Esses sistemas de pontua&#231;&#227;o s&#227;o testes f&#225;ceis, r&#225;pidos e eficazes que podem ser usados na triagem de c&#226;ncer.</p>
    </sec>
  </body>
  <back>
    <fn-group>
      <fn fn-type="financial-disclosure" id="fn1">
        <p>
          <bold>Fontes de financiamento</bold>
        </p>
        <p>O presente estudo n&#227;o teve fontes de financiamento externas.</p>
      </fn>
      <fn fn-type="other" id="fn2">
        <p>
          <bold>Vincula&#231;&#227;o acad&#234;mica</bold>
        </p>
        <p>N&#227;o h&#225; vincula&#231;&#227;o deste estudo a programas de p&#243;s-gradua&#231;&#227;o.</p>
      </fn>
      <fn fn-type="other" id="fn3">
        <p>
          <bold>Aprova&#231;&#227;o &#233;tica e consentimento informado</bold>
        </p>
        <p>Este estudo foi aprovado pelo Comit&#234; de &#201;tica do Sivas Cumhuriyet University Ethics Committee sob o n&#250;mero de protocolo 2022-10/11. 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>
    <ref-list>
      <title>Refer&#234;ncias</title>
      <ref id="B1">
        <label>1</label>
        <element-citation publication-type="journal">
          <person-group person-group-type="author">
            <name>
              <surname>Adler</surname>
              <given-names>Y</given-names>
            </name>
            <name>
              <surname>Charron</surname>
              <given-names>P</given-names>
            </name>
            <name>
              <surname>Imazio</surname>
              <given-names>M</given-names>
            </name>
            <name>
              <surname>Badano</surname>
              <given-names>L</given-names>
            </name>
            <name>
              <surname>Bar&#243;n-Esquivias</surname>
              <given-names>G</given-names>
            </name>
            <name>
              <surname>Bogaert</surname>
              <given-names>J</given-names>
            </name>
            <etal/>
          </person-group>
          <article-title>2015 ESC Guidelines for the Diagnosis and Management of Pericardial Diseases: The Task Force for the Diagnosis and Management of Pericardial Diseases of the European Society of Cardiology (ESC)Endorsed by: The European Association for Cardio-Thoracic Surgery (EACTS)</article-title>
          <source>Eur Heart J</source>
          <year>2015</year>
          <volume>36</volume>
          <issue>42</issue>
          <fpage>2921</fpage>
          <lpage>2964</lpage>
          <pub-id pub-id-type="doi">10.1093/eurheartj/ehv318</pub-id>
        </element-citation>
        <mixed-citation>1 Adler Y, Charron P, Imazio M, Badano L, Bar&#243;n-Esquivias G, Bogaert J, et al. 2015 ESC Guidelines for the Diagnosis and Management of Pericardial Diseases: The Task Force for the Diagnosis and Management of Pericardial Diseases of the European Society of Cardiology (ESC)Endorsed by: The European Association for Cardio-Thoracic Surgery (EACTS). Eur Heart J. 2015;36(42):2921-64. doi: 10.1093/eurheartj/ehv318.</mixed-citation>
      </ref>
      <ref id="B2">
        <label>2</label>
        <element-citation publication-type="journal">
          <person-group person-group-type="author">
            <name>
              <surname>Corey</surname>
              <given-names>GR</given-names>
            </name>
            <name>
              <surname>Campbell</surname>
              <given-names>PT</given-names>
            </name>
            <name>
              <surname>Van Trigt</surname>
              <given-names>P</given-names>
            </name>
            <name>
              <surname>Kenney</surname>
              <given-names>RT</given-names>
            </name>
            <name>
              <surname>O'Connor</surname>
              <given-names>CM</given-names>
            </name>
            <name>
              <surname>Sheikh</surname>
              <given-names>KH</given-names>
            </name>
            <etal/>
          </person-group>
          <article-title>Etiology of Large Pericardial Effusions</article-title>
          <source>Am J Med</source>
          <year>1993</year>
          <volume>95</volume>
          <issue>2</issue>
          <fpage>209</fpage>
          <lpage>213</lpage>
          <pub-id pub-id-type="doi">10.1016/0002-9343(93)90262-n</pub-id>
        </element-citation>
        <mixed-citation>2 Corey GR, Campbell PT, Van Trigt P, Kenney RT, O'Connor CM, Sheikh KH, et al. Etiology of Large Pericardial Effusions. Am J Med. 1993;95(2):209-13. doi: 10.1016/0002-9343(93)90262-n.</mixed-citation>
      </ref>
      <ref id="B3">
        <label>3</label>
        <element-citation publication-type="journal">
          <person-group person-group-type="author">
            <name>
              <surname>Shen</surname>
              <given-names>XB</given-names>
            </name>
            <name>
              <surname>Zhang</surname>
              <given-names>YX</given-names>
            </name>
            <name>
              <surname>Wang</surname>
              <given-names>W</given-names>
            </name>
            <name>
              <surname>Pan</surname>
              <given-names>YY</given-names>
            </name>
          </person-group>
          <article-title>The Hemoglobin, Albumin, Lymphocyte, and Platelet (HALP) Score in Patients with Small Cell Lung Cancer Before First-Line Treatment with Etoposide and Progression-Free Survival</article-title>
          <source>Med Sci Monit</source>
          <year>2019</year>
          <volume>25</volume>
          <fpage>5630</fpage>
          <lpage>5639</lpage>
          <pub-id pub-id-type="doi">10.12659/MSM.917968</pub-id>
        </element-citation>
        <mixed-citation>3 Shen XB, Zhang YX, Wang W, Pan YY. The Hemoglobin, Albumin, Lymphocyte, and Platelet (HALP) Score in Patients with Small Cell Lung Cancer Before First-Line Treatment with Etoposide and Progression-Free Survival. Med Sci Monit. 2019;25:5630-9. doi: 10.12659/MSM.917968.</mixed-citation>
      </ref>
      <ref id="B4">
        <label>4</label>
        <element-citation publication-type="journal">
          <person-group person-group-type="author">
            <name>
              <surname>Jiang</surname>
              <given-names>H</given-names>
            </name>
            <name>
              <surname>Li</surname>
              <given-names>H</given-names>
            </name>
            <name>
              <surname>Li</surname>
              <given-names>A</given-names>
            </name>
            <name>
              <surname>Tang</surname>
              <given-names>E</given-names>
            </name>
            <name>
              <surname>Xu</surname>
              <given-names>D</given-names>
            </name>
            <name>
              <surname>Chen</surname>
              <given-names>Y</given-names>
            </name>
            <etal/>
          </person-group>
          <article-title>Preoperative Combined Hemoglobin, Albumin, Lymphocyte and Platelet Levels Predict Survival in Patients with Locally Advanced Colorectal Cancer</article-title>
          <source>Oncotarget</source>
          <year>2016</year>
          <volume>7</volume>
          <issue>44</issue>
          <fpage>72076</fpage>
          <lpage>72083</lpage>
          <pub-id pub-id-type="doi">10.18632/oncotarget.12271</pub-id>
        </element-citation>
        <mixed-citation>4 Jiang H, Li H, Li A, Tang E, Xu D, Chen Y, et al. Preoperative Combined Hemoglobin, Albumin, Lymphocyte and Platelet Levels Predict Survival in Patients with Locally Advanced Colorectal Cancer. Oncotarget. 2016;7(44):72076-83. doi: 10.18632/oncotarget.12271.</mixed-citation>
      </ref>
      <ref id="B5">
        <label>5</label>
        <element-citation publication-type="journal">
          <person-group person-group-type="author">
            <name>
              <surname>Peng</surname>
              <given-names>D</given-names>
            </name>
            <name>
              <surname>Zhang</surname>
              <given-names>CJ</given-names>
            </name>
            <name>
              <surname>Gong</surname>
              <given-names>YQ</given-names>
            </name>
            <name>
              <surname>Hao</surname>
              <given-names>H</given-names>
            </name>
            <name>
              <surname>Guan</surname>
              <given-names>B</given-names>
            </name>
            <name>
              <surname>Li</surname>
              <given-names>XS</given-names>
            </name>
            <etal/>
          </person-group>
          <article-title>Prognostic Significance of HALP (Hemoglobin, Albumin, Lymphocyte and Platelet) in Patients with Bladder Cancer After Radical Cystectomy</article-title>
          <source>Sci Rep</source>
          <year>2018</year>
          <volume>8</volume>
          <issue>1</issue>
          <fpage>794</fpage>
          <lpage>794</lpage>
          <pub-id pub-id-type="doi">10.1038/s41598-018-19146-y</pub-id>
        </element-citation>
        <mixed-citation>5 Peng D, Zhang CJ, Gong YQ, Hao H, Guan B, Li XS, et al. Prognostic Significance of HALP (Hemoglobin, Albumin, Lymphocyte and Platelet) in Patients with Bladder Cancer After Radical Cystectomy. Sci Rep. 2018;8(1):794. doi: 10.1038/s41598-018-19146-y.</mixed-citation>
      </ref>
      <ref id="B6">
        <label>6</label>
        <element-citation publication-type="journal">
          <person-group person-group-type="author">
            <name>
              <surname>Diakos</surname>
              <given-names>CI</given-names>
            </name>
            <name>
              <surname>Charles</surname>
              <given-names>KA</given-names>
            </name>
            <name>
              <surname>McMillan</surname>
              <given-names>DC</given-names>
            </name>
            <name>
              <surname>Clarke</surname>
              <given-names>SJ</given-names>
            </name>
          </person-group>
          <article-title>Cancer-Related &#304;nflammation and Treatment Effectiveness</article-title>
          <source>Lancet Oncol</source>
          <year>2014</year>
          <volume>15</volume>
          <issue>11</issue>
          <fpage>e493</fpage>
          <lpage>e503</lpage>
          <pub-id pub-id-type="doi">10.1016/S1470-2045(14)70263-3</pub-id>
        </element-citation>
        <mixed-citation>6 Diakos CI, Charles KA, McMillan DC, Clarke SJ. Cancer-Related &#304;nflammation and Treatment Effectiveness. Lancet Oncol. 2014;15(11):e493-503. doi: 10.1016/S1470-2045(14)70263-3.</mixed-citation>
      </ref>
      <ref id="B7">
        <label>7</label>
        <element-citation publication-type="journal">
          <person-group person-group-type="author">
            <name>
              <surname>Crusz</surname>
              <given-names>SM</given-names>
            </name>
            <name>
              <surname>Balkwill</surname>
              <given-names>FR</given-names>
            </name>
          </person-group>
          <article-title>Inflammation and Cancer: Advances and New Agents</article-title>
          <source>Nat Rev Clin Oncol</source>
          <year>2015</year>
          <volume>12</volume>
          <issue>10</issue>
          <fpage>584</fpage>
          <lpage>596</lpage>
          <pub-id pub-id-type="doi">10.1038/nrclinonc.2015.105</pub-id>
        </element-citation>
        <mixed-citation>7 Crusz SM, Balkwill FR. Inflammation and Cancer: Advances and New Agents. Nat Rev Clin Oncol. 2015;12(10):584-96. doi: 10.1038/nrclinonc.2015.105.</mixed-citation>
      </ref>
      <ref id="B8">
        <label>8</label>
        <element-citation publication-type="journal">
          <person-group person-group-type="author">
            <name>
              <surname>Chen</surname>
              <given-names>JH</given-names>
            </name>
            <name>
              <surname>Zhai</surname>
              <given-names>ET</given-names>
            </name>
            <name>
              <surname>Yuan</surname>
              <given-names>YJ</given-names>
            </name>
            <name>
              <surname>Wu</surname>
              <given-names>KM</given-names>
            </name>
            <name>
              <surname>Xu</surname>
              <given-names>JB</given-names>
            </name>
            <name>
              <surname>Peng</surname>
              <given-names>JJ</given-names>
            </name>
            <etal/>
          </person-group>
          <article-title>Systemic &#304;mmune-&#304;nflammation &#304;ndex for Predicting Prognosis of Colorectal Cancer</article-title>
          <source>World J Gastroenterol</source>
          <year>2017</year>
          <volume>23</volume>
          <issue>34</issue>
          <fpage>6261</fpage>
          <lpage>6272</lpage>
          <pub-id pub-id-type="doi">10.3748/wjg.v23.i34.6261</pub-id>
        </element-citation>
        <mixed-citation>8 Chen JH, Zhai ET, Yuan YJ, Wu KM, Xu JB, Peng JJ, et al. Systemic &#304;mmune-&#304;nflammation &#304;ndex for Predicting Prognosis of Colorectal Cancer. World J Gastroenterol. 2017;23(34):6261-72. doi: 10.3748/wjg.v23.i34.6261.</mixed-citation>
      </ref>
      <ref id="B9">
        <label>9</label>
        <element-citation publication-type="journal">
          <person-group person-group-type="author">
            <name>
              <surname>Hu</surname>
              <given-names>B</given-names>
            </name>
            <name>
              <surname>Yang</surname>
              <given-names>XR</given-names>
            </name>
            <name>
              <surname>Xu</surname>
              <given-names>Y</given-names>
            </name>
            <name>
              <surname>Sun</surname>
              <given-names>YF</given-names>
            </name>
            <name>
              <surname>Sun</surname>
              <given-names>C</given-names>
            </name>
            <name>
              <surname>Guo</surname>
              <given-names>W</given-names>
            </name>
            <etal/>
          </person-group>
          <article-title>Systemic &#304;mmune-&#304;nflammation &#304;ndex Predicts Prognosis of Patients After Curative Resection for Hepatocellular Carcinoma</article-title>
          <source>Clin Cancer Res</source>
          <year>2014</year>
          <volume>20</volume>
          <issue>23</issue>
          <fpage>6212</fpage>
          <lpage>6222</lpage>
          <pub-id pub-id-type="doi">10.1158/1078-0432.CCR-14-0442</pub-id>
        </element-citation>
        <mixed-citation>9 Hu B, Yang XR, Xu Y, Sun YF, Sun C, Guo W, et al. Systemic &#304;mmune-&#304;nflammation &#304;ndex Predicts Prognosis of Patients After Curative Resection for Hepatocellular Carcinoma. Clin Cancer Res. 2014;20(23):6212-22. doi: 10.1158/1078-0432.CCR-14-0442.</mixed-citation>
      </ref>
      <ref id="B10">
        <label>10</label>
        <element-citation publication-type="journal">
          <person-group person-group-type="author">
            <name>
              <surname>Tokunaga</surname>
              <given-names>R</given-names>
            </name>
            <name>
              <surname>Sakamoto</surname>
              <given-names>Y</given-names>
            </name>
            <name>
              <surname>Nakagawa</surname>
              <given-names>S</given-names>
            </name>
            <name>
              <surname>Miyamoto</surname>
              <given-names>Y</given-names>
            </name>
            <name>
              <surname>Yoshida</surname>
              <given-names>N</given-names>
            </name>
            <name>
              <surname>Oki</surname>
              <given-names>E</given-names>
            </name>
            <etal/>
          </person-group>
          <article-title>Prognostic Nutritional Index Predicts Severe Complications, Recurrence, and Poor Prognosis in Patients with Colorectal Cancer Undergoing Primary Tumor Resection</article-title>
          <source>Dis Colon Rectum</source>
          <year>2015</year>
          <volume>58</volume>
          <issue>11</issue>
          <fpage>1048</fpage>
          <lpage>1057</lpage>
          <pub-id pub-id-type="doi">10.1097/DCR.0000000000000458</pub-id>
        </element-citation>
        <mixed-citation>10 Tokunaga R, Sakamoto Y, Nakagawa S, Miyamoto Y, Yoshida N, Oki E, et al. Prognostic Nutritional Index Predicts Severe Complications, Recurrence, and Poor Prognosis in Patients with Colorectal Cancer Undergoing Primary Tumor Resection. Dis Colon Rectum. 2015;58(11):1048-57. doi: 10.1097/DCR.0000000000000458.</mixed-citation>
      </ref>
      <ref id="B11">
        <label>11</label>
        <element-citation publication-type="journal">
          <person-group person-group-type="author">
            <name>
              <surname>Okadome</surname>
              <given-names>K</given-names>
            </name>
            <name>
              <surname>Baba</surname>
              <given-names>Y</given-names>
            </name>
            <name>
              <surname>Yagi</surname>
              <given-names>T</given-names>
            </name>
            <name>
              <surname>Kiyozumi</surname>
              <given-names>Y</given-names>
            </name>
            <name>
              <surname>Ishimoto</surname>
              <given-names>T</given-names>
            </name>
            <name>
              <surname>Iwatsuki</surname>
              <given-names>M</given-names>
            </name>
            <etal/>
          </person-group>
          <article-title>Prognostic Nutritional Index, Tumor-infiltrating Lymphocytes, and Prognosis in Patients with Esophageal Cancer</article-title>
          <source>Ann Surg</source>
          <year>2020</year>
          <volume>271</volume>
          <issue>4</issue>
          <fpage>693</fpage>
          <lpage>700</lpage>
          <pub-id pub-id-type="doi">10.1097/SLA.0000000000002985</pub-id>
        </element-citation>
        <mixed-citation>11 Okadome K, Baba Y, Yagi T, Kiyozumi Y, Ishimoto T, Iwatsuki M, et al. Prognostic Nutritional Index, Tumor-infiltrating Lymphocytes, and Prognosis in Patients with Esophageal Cancer. Ann Surg. 2020;271(4):693-700. doi: 10.1097/SLA.0000000000002985.</mixed-citation>
      </ref>
      <ref id="B12">
        <label>12</label>
        <element-citation publication-type="journal">
          <person-group person-group-type="author">
            <name>
              <surname>Buzby</surname>
              <given-names>GP</given-names>
            </name>
            <name>
              <surname>Mullen</surname>
              <given-names>JL</given-names>
            </name>
            <name>
              <surname>Matthews</surname>
              <given-names>DC</given-names>
            </name>
            <name>
              <surname>Hobbs</surname>
              <given-names>CL</given-names>
            </name>
            <name>
              <surname>Rosato</surname>
              <given-names>EF</given-names>
            </name>
          </person-group>
          <article-title>Prognostic Nutritional Index in Gastrointestinal Surgery</article-title>
          <source>Am J Surg</source>
          <year>1980</year>
          <volume>139</volume>
          <issue>1</issue>
          <fpage>160</fpage>
          <lpage>167</lpage>
          <pub-id pub-id-type="doi">10.1016/0002-9610(80)90246-9</pub-id>
        </element-citation>
        <mixed-citation>12 Buzby GP, Mullen JL, Matthews DC, Hobbs CL, Rosato EF. Prognostic Nutritional Index in Gastrointestinal Surgery. Am J Surg. 1980;139(1):160-7. doi: 10.1016/0002-9610(80)90246-9.</mixed-citation>
      </ref>
      <ref id="B13">
        <label>13</label>
        <element-citation publication-type="journal">
          <person-group person-group-type="author">
            <name>
              <surname>Wang</surname>
              <given-names>D</given-names>
            </name>
            <name>
              <surname>Hu</surname>
              <given-names>X</given-names>
            </name>
            <name>
              <surname>Xiao</surname>
              <given-names>L</given-names>
            </name>
            <name>
              <surname>Long</surname>
              <given-names>G</given-names>
            </name>
            <name>
              <surname>Yao</surname>
              <given-names>L</given-names>
            </name>
            <name>
              <surname>Wang</surname>
              <given-names>Z</given-names>
            </name>
            <etal/>
          </person-group>
          <article-title>Prognostic Nutritional Index and Systemic Immune-Inflammation Index Predict the Prognosis of Patients with HCC</article-title>
          <source>J Gastrointest Surg</source>
          <year>2021</year>
          <volume>25</volume>
          <issue>2</issue>
          <fpage>421</fpage>
          <lpage>427</lpage>
          <pub-id pub-id-type="doi">10.1007/s11605-019-04492-7</pub-id>
        </element-citation>
        <mixed-citation>13 Wang D, Hu X, Xiao L, Long G, Yao L, Wang Z, et al. Prognostic Nutritional Index and Systemic Immune-Inflammation Index Predict the Prognosis of Patients with HCC. J Gastrointest Surg. 2021;25(2):421-7. doi: 10.1007/s11605-019-04492-7.</mixed-citation>
      </ref>
      <ref id="B14">
        <label>14</label>
        <element-citation publication-type="journal">
          <person-group person-group-type="author">
            <name>
              <surname>Zhang</surname>
              <given-names>H</given-names>
            </name>
            <name>
              <surname>Shang</surname>
              <given-names>X</given-names>
            </name>
            <name>
              <surname>Ren</surname>
              <given-names>P</given-names>
            </name>
            <name>
              <surname>Gong</surname>
              <given-names>L</given-names>
            </name>
            <name>
              <surname>Ahmed</surname>
              <given-names>A</given-names>
            </name>
            <name>
              <surname>Ma</surname>
              <given-names>Z</given-names>
            </name>
            <etal/>
          </person-group>
          <article-title>The Predictive Value of a Preoperative Systemic &#304;mmune-&#304;nflammation &#304;ndex and Prognostic Nutritional &#304;ndex in Patients with Esophageal Squamous Cell Carcinoma</article-title>
          <source>J Cell Physiol</source>
          <year>2019</year>
          <volume>234</volume>
          <issue>2</issue>
          <fpage>1794</fpage>
          <lpage>1802</lpage>
          <pub-id pub-id-type="doi">10.1002/jcp.27052</pub-id>
        </element-citation>
        <mixed-citation>14 Zhang H, Shang X, Ren P, Gong L, Ahmed A, Ma Z, et al. The Predictive Value of a Preoperative Systemic &#304;mmune-&#304;nflammation &#304;ndex and Prognostic Nutritional &#304;ndex in Patients with Esophageal Squamous Cell Carcinoma. J Cell Physiol. 2019;234(2):1794-802. doi: 10.1002/jcp.27052.</mixed-citation>
      </ref>
      <ref id="B15">
        <label>15</label>
        <element-citation publication-type="journal">
          <person-group person-group-type="author">
            <name>
              <surname>Huang</surname>
              <given-names>X</given-names>
            </name>
            <name>
              <surname>Hu</surname>
              <given-names>H</given-names>
            </name>
            <name>
              <surname>Zhang</surname>
              <given-names>W</given-names>
            </name>
            <name>
              <surname>Shao</surname>
              <given-names>Z</given-names>
            </name>
          </person-group>
          <article-title>Prognostic Value of Prognostic Nutritional Index and Systemic Immune-Inflammation index in Patients with Osteosarcoma</article-title>
          <source>J Cell Physiol</source>
          <year>2019</year>
          <volume>234</volume>
          <issue>10</issue>
          <fpage>18408</fpage>
          <lpage>18414</lpage>
          <pub-id pub-id-type="doi">10.1002/jcp.28476</pub-id>
        </element-citation>
        <mixed-citation>15 Huang X, Hu H, Zhang W, Shao Z. Prognostic Value of Prognostic Nutritional Index and Systemic Immune-Inflammation index in Patients with Osteosarcoma. J Cell Physiol. 2019;234(10):18408-14. doi: 10.1002/jcp.28476.</mixed-citation>
      </ref>
      <ref id="B16">
        <label>16</label>
        <element-citation publication-type="journal">
          <person-group person-group-type="author">
            <name>
              <surname>Imazio</surname>
              <given-names>M</given-names>
            </name>
            <name>
              <surname>Adler</surname>
              <given-names>Y</given-names>
            </name>
          </person-group>
          <article-title>Management of Pericardial Effusion</article-title>
          <source>Eur Heart J</source>
          <year>2013</year>
          <volume>34</volume>
          <issue>16</issue>
          <fpage>1186</fpage>
          <lpage>1197</lpage>
          <pub-id pub-id-type="doi">10.1093/eurheartj/ehs372</pub-id>
        </element-citation>
        <mixed-citation>16 Imazio M, Adler Y. Management of Pericardial Effusion. Eur Heart J. 2013;34(16):1186-97. doi: 10.1093/eurheartj/ehs372.</mixed-citation>
      </ref>
      <ref id="B17">
        <label>17</label>
        <element-citation publication-type="journal">
          <person-group person-group-type="author">
            <name>
              <surname>Chen</surname>
              <given-names>XL</given-names>
            </name>
            <name>
              <surname>Xue</surname>
              <given-names>L</given-names>
            </name>
            <name>
              <surname>Wang</surname>
              <given-names>W</given-names>
            </name>
            <name>
              <surname>Chen</surname>
              <given-names>HN</given-names>
            </name>
            <name>
              <surname>Zhang</surname>
              <given-names>WH</given-names>
            </name>
            <name>
              <surname>Liu</surname>
              <given-names>K</given-names>
            </name>
            <etal/>
          </person-group>
          <article-title>Prognostic Significance of the Combination of Preoperative Hemoglobin, Albumin, Lymphocyte and Platelet in Patients with Gastric Carcinoma: A Retrospective Cohort Study</article-title>
          <source>Oncotarget</source>
          <year>2015</year>
          <volume>6</volume>
          <issue>38</issue>
          <fpage>41370</fpage>
          <lpage>41382</lpage>
          <pub-id pub-id-type="doi">10.18632/oncotarget.5629</pub-id>
        </element-citation>
        <mixed-citation>17 Chen XL, Xue L, Wang W, Chen HN, Zhang WH, Liu K, et al. Prognostic Significance of the Combination of Preoperative Hemoglobin, Albumin, Lymphocyte and Platelet in Patients with Gastric Carcinoma: A Retrospective Cohort Study. Oncotarget. 2015;6(38):41370-82. doi: 10.18632/oncotarget.5629.</mixed-citation>
      </ref>
      <ref id="B18">
        <label>18</label>
        <element-citation publication-type="journal">
          <person-group person-group-type="author">
            <name>
              <surname>Cong</surname>
              <given-names>L</given-names>
            </name>
            <name>
              <surname>Hu</surname>
              <given-names>L</given-names>
            </name>
          </person-group>
          <article-title>The Value of the Combination of Hemoglobin, Albumin, Lymphocyte and Platelet in Predicting Platinum-Based Chemoradiotherapy Response in Male Patients with Esophageal Squamous Cell Carcinoma</article-title>
          <source>Int Immunopharmacol</source>
          <year>2017</year>
          <volume>46</volume>
          <fpage>75</fpage>
          <lpage>79</lpage>
          <pub-id pub-id-type="doi">10.1016/j.intimp.2017.02.027</pub-id>
        </element-citation>
        <mixed-citation>18 Cong L, Hu L. The Value of the Combination of Hemoglobin, Albumin, Lymphocyte and Platelet in Predicting Platinum-Based Chemoradiotherapy Response in Male Patients with Esophageal Squamous Cell Carcinoma. Int Immunopharmacol. 2017;46:75-9. doi: 10.1016/j.intimp.2017.02.027.</mixed-citation>
      </ref>
      <ref id="B19">
        <label>19</label>
        <element-citation publication-type="journal">
          <person-group person-group-type="author">
            <name>
              <surname>Peng</surname>
              <given-names>D</given-names>
            </name>
            <name>
              <surname>Zhang</surname>
              <given-names>CJ</given-names>
            </name>
            <name>
              <surname>Tang</surname>
              <given-names>Q</given-names>
            </name>
            <name>
              <surname>Zhang</surname>
              <given-names>L</given-names>
            </name>
            <name>
              <surname>Yang</surname>
              <given-names>KW</given-names>
            </name>
            <name>
              <surname>Yu</surname>
              <given-names>XT</given-names>
            </name>
            <etal/>
          </person-group>
          <article-title>Prognostic Significance of the Combination of Preoperative Hemoglobin and Albumin Levels and Lymphocyte and Platelet Counts (HALP) in Patients with Renal Cell Carcinoma After Nephrectomy</article-title>
          <source>BMC Urol</source>
          <year>2018</year>
          <volume>18</volume>
          <issue>1</issue>
          <fpage>20</fpage>
          <lpage>20</lpage>
          <pub-id pub-id-type="doi">10.1186/s12894-018-0333-8</pub-id>
        </element-citation>
        <mixed-citation>19 Peng D, Zhang CJ, Tang Q, Zhang L, Yang KW, Yu XT, et al. Prognostic Significance of the Combination of Preoperative Hemoglobin and Albumin Levels and Lymphocyte and Platelet Counts (HALP) in Patients with Renal Cell Carcinoma After Nephrectomy. BMC Urol. 2018;18(1):20. doi: 10.1186/s12894-018-0333-8.</mixed-citation>
      </ref>
      <ref id="B20">
        <label>20</label>
        <element-citation publication-type="journal">
          <person-group person-group-type="author">
            <name>
              <surname>Chen</surname>
              <given-names>P</given-names>
            </name>
            <name>
              <surname>Wang</surname>
              <given-names>C</given-names>
            </name>
            <name>
              <surname>Cheng</surname>
              <given-names>B</given-names>
            </name>
            <name>
              <surname>Nesa</surname>
              <given-names>EU</given-names>
            </name>
            <name>
              <surname>Liu</surname>
              <given-names>Y</given-names>
            </name>
            <name>
              <surname>Jia</surname>
              <given-names>Y</given-names>
            </name>
            <etal/>
          </person-group>
          <article-title>Plasma Fibrinogen and Serum Albumin Levels (FA Score) Act as a Promising Prognostic &#304;ndicator in Non-Small Cell Lung Cancer</article-title>
          <source>Onco Targets Ther</source>
          <year>2017</year>
          <volume>10</volume>
          <fpage>3107</fpage>
          <lpage>3118</lpage>
          <pub-id pub-id-type="doi">10.2147/OTT.S138854</pub-id>
        </element-citation>
        <mixed-citation>20 Chen P, Wang C, Cheng B, Nesa EU, Liu Y, Jia Y, et al. Plasma Fibrinogen and Serum Albumin Levels (FA Score) Act as a Promising Prognostic &#304;ndicator in Non-Small Cell Lung Cancer. Onco Targets Ther. 2017;10:3107-18. doi: 10.2147/OTT.S138854.</mixed-citation>
      </ref>
      <ref id="B21">
        <label>21</label>
        <element-citation publication-type="journal">
          <person-group person-group-type="author">
            <name>
              <surname>Sung</surname>
              <given-names>H</given-names>
            </name>
            <name>
              <surname>Ferlay</surname>
              <given-names>J</given-names>
            </name>
            <name>
              <surname>Siegel</surname>
              <given-names>RL</given-names>
            </name>
            <name>
              <surname>Laversanne</surname>
              <given-names>M</given-names>
            </name>
            <name>
              <surname>Soerjomataram</surname>
              <given-names>I</given-names>
            </name>
            <name>
              <surname>Jemal</surname>
              <given-names>A</given-names>
            </name>
            <etal/>
          </person-group>
          <article-title>Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries</article-title>
          <source>CA Cancer J Clin</source>
          <year>2021</year>
          <volume>71</volume>
          <issue>3</issue>
          <fpage>209</fpage>
          <lpage>249</lpage>
          <pub-id pub-id-type="doi">10.3322/caac.21660</pub-id>
        </element-citation>
        <mixed-citation>21 Sung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, et al. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA Cancer J Clin. 2021;71(3):209-49. doi: 10.3322/caac.21660.</mixed-citation>
      </ref>
      <ref id="B22">
        <label>22</label>
        <element-citation publication-type="journal">
          <person-group person-group-type="author">
            <name>
              <surname>Y&#305;lmaz</surname>
              <given-names>A</given-names>
            </name>
            <name>
              <surname>Tekin</surname>
              <given-names>S</given-names>
            </name>
            <name>
              <surname>Bilici</surname>
              <given-names>M</given-names>
            </name>
            <name>
              <surname>Y&#305;lmaz</surname>
              <given-names>H</given-names>
            </name>
          </person-group>
          <article-title>Clinical Significance of Inflammatory Indexes in Patients with Epithelial Ovarian Cancer</article-title>
          <source>Acta Oncol Tur</source>
          <year>2020</year>
          <volume>53</volume>
          <issue>3</issue>
          <fpage>402</fpage>
          <lpage>409</lpage>
          <pub-id pub-id-type="doi">10.5505/aot.2020.38981</pub-id>
          <comment>53(3): 402-09</comment>
        </element-citation>
        <mixed-citation>22 Y&#305;lmaz A, Tekin S, Bilici M, Y&#305;lmaz H. Clinical Significance of Inflammatory Indexes in Patients with Epithelial Ovarian Cancer. Acta Oncol Tur. 2020; 53(3): 402-9. doi: 10.5505/aot.2020.38981. 53(3): 402-09</mixed-citation>
      </ref>
      <ref id="B23">
        <label>23</label>
        <element-citation publication-type="journal">
          <person-group person-group-type="author">
            <name>
              <surname>Hong</surname>
              <given-names>X</given-names>
            </name>
            <name>
              <surname>Cui</surname>
              <given-names>B</given-names>
            </name>
            <name>
              <surname>Wang</surname>
              <given-names>M</given-names>
            </name>
            <name>
              <surname>Yang</surname>
              <given-names>Z</given-names>
            </name>
            <name>
              <surname>Wang</surname>
              <given-names>L</given-names>
            </name>
            <name>
              <surname>Xu</surname>
              <given-names>Q</given-names>
            </name>
          </person-group>
          <article-title>Systemic Immune-&#304;nflammation Index, Based on Platelet Counts and Neutrophil-Lymphocyte Ratio, &#305;s Useful for Predicting Prognosis in Small Cell Lung Cancer</article-title>
          <source>Tohoku J Exp Med</source>
          <year>2015</year>
          <volume>236</volume>
          <issue>4</issue>
          <fpage>297</fpage>
          <lpage>304</lpage>
          <pub-id pub-id-type="doi">10.1620/tjem.236.297</pub-id>
        </element-citation>
        <mixed-citation>23 Hong X, Cui B, Wang M, Yang Z, Wang L, Xu Q. Systemic Immune-&#304;nflammation Index, Based on Platelet Counts and Neutrophil-Lymphocyte Ratio, &#305;s Useful for Predicting Prognosis in Small Cell Lung Cancer. Tohoku J Exp Med. 2015;236(4):297-304. doi: 10.1620/tjem.236.297.</mixed-citation>
      </ref>
      <ref id="B24">
        <label>24</label>
        <element-citation publication-type="book">
          <person-group person-group-type="author">
            <collab>Turkish Thoracic Society</collab>
          </person-group>
          <source>Basic Lung Health Problems and Solution Suggestions in Turkey</source>
          <publisher-loc>Ancara</publisher-loc>
          <publisher-name>Turkish Thoracic Society</publisher-name>
          <year>2010</year>
        </element-citation>
        <mixed-citation>24 Turkish Thoracic Society. Basic Lung Health Problems and Solution Suggestions in Turkey. Ancara: Turkish Thoracic Society; 2010.</mixed-citation>
      </ref>
      <ref id="B25">
        <label>25</label>
        <element-citation publication-type="journal">
          <person-group person-group-type="author">
            <name>
              <surname>Madeddu</surname>
              <given-names>C</given-names>
            </name>
            <name>
              <surname>Gramignano</surname>
              <given-names>G</given-names>
            </name>
            <name>
              <surname>Astara</surname>
              <given-names>G</given-names>
            </name>
            <name>
              <surname>Demontis</surname>
              <given-names>R</given-names>
            </name>
            <name>
              <surname>Sanna</surname>
              <given-names>E</given-names>
            </name>
            <name>
              <surname>Atzeni</surname>
              <given-names>V</given-names>
            </name>
            <etal/>
          </person-group>
          <article-title>Pathogenesis and Treatment Options of Cancer Related Anemia: Perspective for a Targeted Mechanism-Based Approach</article-title>
          <source>Front Physiol</source>
          <year>2018</year>
          <volume>9</volume>
          <fpage>1294</fpage>
          <lpage>1294</lpage>
          <pub-id pub-id-type="doi">10.3389/fphys.2018.01294</pub-id>
        </element-citation>
        <mixed-citation>25 Madeddu C, Gramignano G, Astara G, Demontis R, Sanna E, Atzeni V, et al. Pathogenesis and Treatment Options of Cancer Related Anemia: Perspective for a Targeted Mechanism-Based Approach. Front Physiol. 2018;9:1294. doi: 10.3389/fphys.2018.01294.</mixed-citation>
      </ref>
      <ref id="B26">
        <label>26</label>
        <element-citation publication-type="journal">
          <person-group person-group-type="author">
            <name>
              <surname>Macci&#242;</surname>
              <given-names>A</given-names>
            </name>
            <name>
              <surname>Madeddu</surname>
              <given-names>C</given-names>
            </name>
            <name>
              <surname>Gramignano</surname>
              <given-names>G</given-names>
            </name>
            <name>
              <surname>Mulas</surname>
              <given-names>C</given-names>
            </name>
            <name>
              <surname>Tanca</surname>
              <given-names>L</given-names>
            </name>
            <name>
              <surname>Cherchi</surname>
              <given-names>MC</given-names>
            </name>
            <etal/>
          </person-group>
          <article-title>The Role of Inflammation, Iron, and Nutritional Status in Cancer-Related Anemia: Results of a Large, Prospective, Observational Study</article-title>
          <source>Haematologica</source>
          <year>2015</year>
          <volume>100</volume>
          <issue>1</issue>
          <fpage>124</fpage>
          <lpage>132</lpage>
          <pub-id pub-id-type="doi">10.3324/haematol.2014.112813</pub-id>
        </element-citation>
        <mixed-citation>26 Macci&#242; A, Madeddu C, Gramignano G, Mulas C, Tanca L, Cherchi MC, et al. The Role of Inflammation, Iron, and Nutritional Status in Cancer-Related Anemia: Results of a Large, Prospective, Observational Study. Haematologica. 2015;100(1):124-32. doi: 10.3324/haematol.2014.112813.</mixed-citation>
      </ref>
      <ref id="B27">
        <label>27</label>
        <element-citation publication-type="journal">
          <person-group person-group-type="author">
            <name>
              <surname>McMillan</surname>
              <given-names>DC</given-names>
            </name>
            <name>
              <surname>Elahi</surname>
              <given-names>MM</given-names>
            </name>
            <name>
              <surname>Sattar</surname>
              <given-names>N</given-names>
            </name>
            <name>
              <surname>Angerson</surname>
              <given-names>WJ</given-names>
            </name>
            <name>
              <surname>Johnstone</surname>
              <given-names>J</given-names>
            </name>
            <name>
              <surname>McArdle</surname>
              <given-names>CS</given-names>
            </name>
          </person-group>
          <article-title>Measurement of the Systemic &#304;nflammatory Response Predicts Cancer-Specific and Non-Cancer Survival in Patients with Cancer</article-title>
          <source>Nutr Cancer</source>
          <year>2001</year>
          <volume>41</volume>
          <issue>1-2</issue>
          <fpage>64</fpage>
          <lpage>69</lpage>
          <pub-id pub-id-type="doi">10.1080/01635581.2001.9680613</pub-id>
        </element-citation>
        <mixed-citation>27 McMillan DC, Elahi MM, Sattar N, Angerson WJ, Johnstone J, McArdle CS. Measurement of the Systemic &#304;nflammatory Response Predicts Cancer-Specific and Non-Cancer Survival in Patients with Cancer. Nutr Cancer. 2001;41(1-2):64-9. doi: 10.1080/01635581.2001.9680613.</mixed-citation>
      </ref>
      <ref id="B28">
        <label>28</label>
        <element-citation publication-type="journal">
          <person-group person-group-type="author">
            <name>
              <surname>Schumacher</surname>
              <given-names>K</given-names>
            </name>
            <name>
              <surname>Haensch</surname>
              <given-names>W</given-names>
            </name>
            <name>
              <surname>R&#246;efzaad</surname>
              <given-names>C</given-names>
            </name>
            <name>
              <surname>Schlag</surname>
              <given-names>PM</given-names>
            </name>
          </person-group>
          <article-title>Prognostic Significance of Activated CD8(+) T Cell Infiltrations Within Esophageal Carcinomas</article-title>
          <source>Cancer Res</source>
          <year>2001</year>
          <volume>61</volume>
          <issue>10</issue>
          <fpage>3932</fpage>
          <lpage>3936</lpage>
        </element-citation>
        <mixed-citation>28 Schumacher K, Haensch W, R&#246;efzaad C, Schlag PM. Prognostic Significance of Activated CD8(+) T Cell Infiltrations Within Esophageal Carcinomas. Cancer Res. 2001;61(10):3932-6.</mixed-citation>
      </ref>
      <ref id="B29">
        <label>29</label>
        <element-citation publication-type="journal">
          <person-group person-group-type="author">
            <name>
              <surname>Huang</surname>
              <given-names>WY</given-names>
            </name>
            <name>
              <surname>Berndt</surname>
              <given-names>SI</given-names>
            </name>
            <name>
              <surname>Shiels</surname>
              <given-names>MS</given-names>
            </name>
            <name>
              <surname>Katki</surname>
              <given-names>HA</given-names>
            </name>
            <name>
              <surname>Chaturvedi</surname>
              <given-names>AK</given-names>
            </name>
            <name>
              <surname>Wentzensen</surname>
              <given-names>N</given-names>
            </name>
            <etal/>
          </person-group>
          <article-title>Circulating Inflammation Markers and Colorectal Adenoma Risk</article-title>
          <source>Carcinogenesis</source>
          <year>2019</year>
          <volume>40</volume>
          <issue>6</issue>
          <fpage>765</fpage>
          <lpage>770</lpage>
          <pub-id pub-id-type="doi">10.1093/carcin/bgz027</pub-id>
        </element-citation>
        <mixed-citation>29 Huang WY, Berndt SI, Shiels MS, Katki HA, Chaturvedi AK, Wentzensen N, et al. Circulating Inflammation Markers and Colorectal Adenoma Risk. Carcinogenesis. 2019;40(6):765-70. doi: 10.1093/carcin/bgz027.</mixed-citation>
      </ref>
      <ref id="B30">
        <label>30</label>
        <element-citation publication-type="journal">
          <person-group person-group-type="author">
            <name>
              <surname>Milner</surname>
              <given-names>JD</given-names>
            </name>
            <name>
              <surname>Ward</surname>
              <given-names>JM</given-names>
            </name>
            <name>
              <surname>Keane-Myers</surname>
              <given-names>A</given-names>
            </name>
            <name>
              <surname>Paul</surname>
              <given-names>WE</given-names>
            </name>
          </person-group>
          <article-title>Lymphopenic Mice Reconstituted with Limited Repertoire T Cells Develop Severe, Multiorgan, Th2-Associated &#304;nflammatory Disease</article-title>
          <source>Proc Natl Acad Sci U S A</source>
          <year>2007</year>
          <volume>104</volume>
          <issue>2</issue>
          <fpage>576</fpage>
          <lpage>581</lpage>
          <pub-id pub-id-type="doi">10.1073/pnas.0610289104</pub-id>
        </element-citation>
        <mixed-citation>30 Milner JD, Ward JM, Keane-Myers A, Paul WE. Lymphopenic Mice Reconstituted with Limited Repertoire T Cells Develop Severe, Multiorgan, Th2-Associated &#304;nflammatory Disease. Proc Natl Acad Sci U S A. 2007;104(2):576-81. doi: 10.1073/pnas.0610289104.</mixed-citation>
      </ref>
    </ref-list>
  </back>
  <sub-article article-type="translation" id="S01" 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>Screening Tests Predicting Cancer Metastasis in the Etiology of Pericardial Effusion: HALP Score and PNI</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <contrib-id contrib-id-type="orcid">0000-0001-9823-1613</contrib-id>
          <name>
            <surname>Koyun</surname>
            <given-names>Emin</given-names>
          </name>
          <role>Conception and design of the research</role>
          <role>Acquisition of data</role>
          <role>Analysis and interpretation of the data</role>
          <role>Statistical analysis</role>
          <role>Writing of the manuscript and Critical revision of the manuscript for important intellectual content</role>
          <xref ref-type="aff" rid="aff5">
            <sup>1</sup>
          </xref>
          <xref ref-type="corresp" rid="c2"/>
        </contrib>
        <contrib contrib-type="author">
          <contrib-id contrib-id-type="orcid">0000-0003-0053-9594</contrib-id>
          <name>
            <surname>Dindas</surname>
            <given-names>Ferhat</given-names>
          </name>
          <role>Conception and design of the research</role>
          <role>Acquisition of data</role>
          <role>Analysis and interpretation of the data</role>
          <role>Statistical analysis</role>
          <role>Writing of the manuscript and Critical revision of the manuscript for important intellectual content</role>
          <xref ref-type="aff" rid="aff6">
            <sup>2</sup>
          </xref>
        </contrib>
        <contrib contrib-type="author">
          <contrib-id contrib-id-type="orcid">0000-0003-3416-5965</contrib-id>
          <name>
            <surname>Sahin</surname>
            <given-names>Anil</given-names>
          </name>
          <role>Conception and design of the research</role>
          <role>Acquisition of data</role>
          <role>Analysis and interpretation of the data</role>
          <role>Statistical analysis</role>
          <role>Writing of the manuscript and Critical revision of the manuscript for important intellectual content</role>
          <xref ref-type="aff" rid="aff5">
            <sup>1</sup>
          </xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Cerik</surname>
            <given-names>Idris Bugra</given-names>
          </name>
          <role>Conception and design of the research</role>
          <role>Acquisition of data</role>
          <role>Analysis and interpretation of the data</role>
          <role>Statistical analysis</role>
          <role>Writing of the manuscript and Critical revision of the manuscript for important intellectual content</role>
          <xref ref-type="aff" rid="aff7">
            <sup>3</sup>
          </xref>
        </contrib>
        <contrib contrib-type="author">
          <contrib-id contrib-id-type="orcid">0000-0002-3895-1923</contrib-id>
          <name>
            <surname>Dogdus</surname>
            <given-names>Mustafa</given-names>
          </name>
          <role>Conception and design of the research</role>
          <role>Acquisition of data</role>
          <role>Analysis and interpretation of the data</role>
          <role>Statistical analysis</role>
          <role>Writing of the manuscript and Critical revision of the manuscript for important intellectual content</role>
          <xref ref-type="aff" rid="aff8">
            <sup>4</sup>
          </xref>
        </contrib>
        <aff id="aff5">
          <label>1</label>
          <addr-line>
            <named-content content-type="city">Sivas</named-content>
          </addr-line>
          <country country="TR">Turkey</country>
          <institution content-type="original">Sivas Cumhuriyet University &#8211; Department of Cardiology, Sivas &#8211; Turkey</institution>
        </aff>
        <aff id="aff6">
          <label>2</label>
          <addr-line>
            <named-content content-type="city">Usak</named-content>
          </addr-line>
          <country country="TR">Turkey</country>
          <institution content-type="original">Usak University &#8211; Department of Cardiology, Usak &#8211; Turkey</institution>
        </aff>
        <aff id="aff7">
          <label>3</label>
          <addr-line>
            <named-content content-type="city">Ordu</named-content>
          </addr-line>
          <country country="TR">Turkey</country>
          <institution content-type="original">Ordu University &#8211; Department of Cardiology, Ordu &#8211; Turkey</institution>
        </aff>
        <aff id="aff8">
          <label>4</label>
          <addr-line>
            <named-content content-type="city">Izmir</named-content>
          </addr-line>
          <country country="TR">Turkey</country>
          <institution content-type="original">Izmir University of Economics &#8211; Department of Cardiology, Izmir &#8211; Turkey</institution>
        </aff>
      </contrib-group>
      <author-notes>
        <corresp id="c2"><bold>Mailing Address: Emin Koyun &#8226;</bold> Sivas Cumhuriyet University - Department of Cardiology - Cumhuriyet &#220;niversitesi T&#305;p Fak&#252;ltesi Hastanesi Kalp Hastal&#305;klar&#305; Merkezi Sivas <postal-code>58000</postal-code> &#8211; Turkey. E-mail: <email>eminkoyun.93@gmail.com</email></corresp>
        <fn fn-type="conflict">
          <p>
            <bold>Potential conflict of interest</bold>
          </p>
          <p>No potential conflict of interest relevant to this article was reported.</p>
        </fn>
        <fn fn-type="edited-by">
          <p>Editor responsible for the review: Gl&#225;ucia Maria Moraes de Oliveira</p>
        </fn>
      </author-notes>
      <abstract>
        <title>Abstract</title>
        <sec>
          <title>Background:</title>
          <p>Cancer screening is absolutely necessary in patients with pericardial effusion, given that cancer is one of the most serious diseases in the etiology of pericardial effusion. In previous studies, it was stated that the systemic immune-inflammation index (SII); the prognostic nutrition index (PNI); and the hemoglobin, albumin, lymphocyte, platelet (HALP) score can produce scores related to cancer.</p>
        </sec>
        <sec>
          <title>Objectives:</title>
          <p>This study began considering that these scoring systems could predict cancer in the etiology of patients with pericardial effusion.</p>
        </sec>
        <sec>
          <title>Methods:</title>
          <p>This study produced a retrospective analysis of patients who underwent pericardiocentesis between 2006 and 2022. Pericardiocentesis was performed in a total of 283 patients with moderate-to-large pericardial effusion or pericardial tamponade within the specified period. HALP, PNI, and SII scores were calculated according to the peripheral venous blood taken before the pericardiocentesis procedure. The statistical significance level was set at p&lt;0.05.</p>
        </sec>
        <sec>
          <title>Results:</title>
          <p>The HALP score proved to be 0.173 (0.125-0.175) in cancer patients and 0.32 (0.20-0.49) in non-cancer patients (p&lt;0.001). The PNI score proved to be 33.1&#177;5.6 in cancer patients and 39.8&#177;4.8 in non-cancer patients (p&lt;0.001).</p>
        </sec>
        <sec>
          <title>Conclusion:</title>
          <p>The HALP score and PNI proved to be easy and fast cancer screening tests that can predict cancer metastasis in the etiology of patients with pericardial effusion.</p>
        </sec>
      </abstract>
      <kwd-group xml:lang="en">
        <title>Keywords:</title>
        <kwd>Cancer</kwd>
        <kwd>Hemoglobin, Albumin, Lymphocyte, Platelet (HALP)</kwd>
        <kwd>Prognostic Nutrition &#304;ndex</kwd>
        <kwd>Pericardial Effusion</kwd>
      </kwd-group>
    </front-stub>
    <body>
      <fig id="f4">
        <graphic xlink:href="1678-4170-abc-121-01-e20230376-30376-gf01-en.tif"/></fig>
      <sec sec-type="intro">
        <title>Introduction</title>
        <p>Abnormal fluid accumulation in the pericardial space is defined as pericardial effusion.<sup><xref ref-type="bibr" rid="B1">1</xref></sup> There are many causes of pericardial effusion, such as infections and autoimmune, neoplastic, iatrogenic, traumatic, metabolic diseases, and heart diseases.<sup><xref ref-type="bibr" rid="B2">2</xref></sup></p>
        <p>Cancer is a disease with a high morbidity and mortality. It is also well-known that nutrition and inflammatory status are among the factors determining the prognosis in cancer patients.<sup><xref ref-type="bibr" rid="B3">3</xref></sup> In the literature, scoring systems, such as the hemoglobin, albumin, lymphocyte, platelet (HALP), the systemic immune-inflammation index (SII), and the prognostic nutrition index (PNI) scores are associated with nutritional and inflammatory conditions and can thus be predictive of cancer. The HALP score, which consists of four laboratory markers (hemoglobin, albumin, lymphocyte, platelet), is associated with both nutrition and inflammatory status, and is commonly used as a prognostic factor in patients with various malignant tumors, including gastrointestinal cancer<sup><xref ref-type="bibr" rid="B4">4</xref></sup> and genitourinary cancer.<sup><xref ref-type="bibr" rid="B5">5</xref></sup></p>
        <p>The interaction between systemic inflammation, which is one of the features of cancer, and local immune response plays a role in the formation of various types of malignancy and in the course of cancer.<sup><xref ref-type="bibr" rid="B6">6</xref>,<xref ref-type="bibr" rid="B7">7</xref></sup> Systemic inflammation parameters have also been accepted as prognostic factors in malignant solid tumors.<sup><xref ref-type="bibr" rid="B8">8</xref></sup> SII, which consists of lymphocyte, neutrophil, and platelet counts, has been reported to be a prognostic factor for patients with some malignant tumors.<sup><xref ref-type="bibr" rid="B9">9</xref></sup> In colorectal<sup><xref ref-type="bibr" rid="B10">10</xref></sup> and esophageal cancer,<sup><xref ref-type="bibr" rid="B11">11</xref></sup> nutrition of patients and inflammatory parameters in the blood have proven to be effective in predicting prognoses in these patients.</p>
        <p>PNI, by contrast, was first used to assess patient risk in surgery for gastrointestinal diseases.<sup><xref ref-type="bibr" rid="B12">12</xref></sup> PNI, which is a scoring system consisting of the combination of the albumin level in blood serum and lymphocyte counts in the blood, is used to evaluate nutritional and immune statuses in cancer patients,<sup><xref ref-type="bibr" rid="B13">13</xref></sup> and serves as a prognostic score in esophageal carcinoma and osteosarcoma.<sup><xref ref-type="bibr" rid="B14">14</xref>,<xref ref-type="bibr" rid="B15">15</xref></sup></p>
        <p>Our most important aim in this study is to quickly detect cancer metastasis in etiology in patients with pericardial effusion. Because the most serious disease in the etiology of patients with pericardial effusion is cancer. While investigating the etiology in patients presenting pericardial effusion, we first establihsed the hypothesis that these scoring systems, which can be calculated with simple laboratory tests, can predict the development of cancer-related pericardial effusion. These scoring systems are simple and easy to apply. If a scoring system for pericardial effusion is found to be effective in identifying patients with cancer, these scoring systems can accelerate the diagnosis and treatment of cancer and reduce cancer-related morbidity and mortality.</p>
      </sec>
      <sec sec-type="methods">
        <title>Methods</title>
        <p>This study produced a retrospective analysis of patients who underwent pericardiocentesis between 2006 and 2022. Approval from the ethics committee of the local university was obtained, logged under ethics committee decision number: 2022-10/11. Consent was obtained from the patients and their relatives to participate in the study. During the stated period, a total of 295 patients with medium to large pericardial effusion or pericardial tamponade underwent pericardiocentesis under fluoroscopy guidance (<xref ref-type="fig" rid="f4">Central Illustration</xref>). Pericardial effusion size of the patients from the present study was classified according to the echocardiography as mild (&lt;10 mm), moderate (10&#8211;20 mm), or large (&gt;20 mm) according to the classification system.<sup><xref ref-type="bibr" rid="B16">16</xref></sup> All of the patients included in our study were patients with moderate-to-large effusion or cardiac tamponade, classified according to size. Percutaneous pericardiocentesis procedures were performed mostly from the subxiphoid space and rarely from the intercostal space. Each patient's medical records were reviewed to obtain patient demographics, clinical data, and disease diagnoses. Pericardial fluid data, laboratory parameters, pathology results and microbiology results at the time of admission were recorded. The effusion was classified as either malignant or benign. If the pericardial fluid cytology showed malignant and suspicious cells, the effusion was classified as malignant. Those without abnormal findings in pericardial effusion cytology were classified as benign. The patients were then divided into two groups: those diagnosed with cancer and those not diagnosed with cancer. The following were determined as exclusion criteria: being younger than 18 years of age, having a pericardial effusion less than 10 mm, and having a glomerular filtration rate (GFR) &lt;30 ml/min/m<sup>2</sup>. The diagnosis of pericardiocentesis was conducted using the transthorasic echocardiogram (TTE). All patients underwent follow-up via TTE before and after pericardiocentesis. Peripheral venous blood tests were taken from all patients diagnosed with pericardial effusion. Biochemistry parameters (high density lipoprotein (HDL), low density lipoprotein (LDL), C-reactive protein (CRP), creatinine, serum electrolytes) were analyzed according to the blood samples. The SII score was calculated using the Neutrophil 10<sup>3</sup>/uL x Platelet 10<sup>3</sup>/uL / Lymphocyte 10<sup>3</sup>/uL formula, while the PNI score was calculated using the (serum alb&#252;min g/dL level &#215; 10) + (lymphocyte 10<sup>3</sup>/uL &#215; 0.005) formula. The HALP score, by contrast, was calculated using the Hemoglobin g/dL x Albumin g/dL x Lymphocyte 10<sup>3</sup>/uL / Platelet 10<sup>3</sup>/uL formula.</p>
        <sec>
          <title>Statistical analysis</title>
          <p>Histogram, q-q graph and Shapiro-Wilk test were used to evaluate whether or not the data violated normality assumptions. The T-test and Mann Whitney U test were performed on two-samples in order to compare quantative variables between groups. The chi-square analysis was used to evaluate the relationship between categorical variables. The continuous data were presented as mean &#177; standard deviation (SD) or median (1<sup>st</sup> quartile &#8211; 3d quartile) based on the data distribution. The categorical variables were expressed as the number (n) with a percentage (%). Logistic regression analysis was used to determine the risk factors affecting the cancer status. Variables that were found to be statistically significant as a result of logistic regression analysis were evaluated using multiple logistic regression analysis. Receiver operating characteristic (ROC) analysis was performed to evaluate the HALP and PNI scores used to predict cancer. The area under the curve (AUC) and the cut-off value were calculated for each score value. Sensitivity and specificity were calculated to evaluate the diagnostic test performance of each score. The statistical significance level was set at p&lt;0.05. Data analysis was performed using SPSS 22 statistical software.</p>
        </sec>
      </sec>
      <sec sec-type="results">
        <title>Results</title>
        <p>Pericardiocentesis was performed on 295 patients between 2006 and 2022. Twelve patients were excluded from the study due to a lack of blood parameters. The remaining 283 patients were included in the study. While 29 of 84 patients who underwent pericardiocentesis had a previous diagnosis of cancer, 55 patients were diagnosed with cancer within 6 months after pericardiocentesis. The most common disease was lung cancer, with breast cancer ranking second (<xref ref-type="table" rid="t4">Table 1</xref>).</p>
        <table-wrap id="t4">
          <label>Table 1</label>
          <caption>
            <title>Distribution of patients diagnosed with cancer</title>
          </caption>
          <table frame="hsides" rules="none">
            <colgroup width="50%">
              <col/>
              <col/>
            </colgroup>
            <thead style="border-top: thin solid; border-bottom: thin solid; border-color: #000000">
              <tr style="background-color:#76B4CF">
                <th valign="middle" align="left">Cancer Type</th>
                <th valign="middle" align="center">Number of patients (n: 84)(%)</th>
              </tr>
            </thead>
            <tbody style="border-bottom: thin solid; border-color: #000000">
              <tr>
                <td valign="middle" align="left">Lung cancer</td>
                <td valign="middle" align="center">45 (%53.57)</td>
              </tr>
              <tr style="background-color:#C7DFEC">
                <td valign="middle" align="left">Breast cancer</td>
                <td valign="middle" align="center">11 (%13)</td>
              </tr>
              <tr>
                <td valign="middle" align="left">Gastric cancer</td>
                <td valign="middle" align="center">8 (%9.52)</td>
              </tr>
              <tr style="background-color:#C7DFEC">
                <td valign="middle" align="left">Leukemia</td>
                <td valign="middle" align="center">4 (%4.76)</td>
              </tr>
              <tr>
                <td valign="middle" align="left">Prostate cancer</td>
                <td valign="middle" align="center">4 (%4.76)</td>
              </tr>
              <tr style="background-color:#C7DFEC">
                <td valign="middle" align="left">Lymphoma</td>
                <td valign="middle" align="center">3 (%3.57)</td>
              </tr>
              <tr>
                <td valign="middle" align="left">Renal cancer</td>
                <td valign="middle" align="center">2 (%2.38)</td>
              </tr>
              <tr style="background-color:#C7DFEC">
                <td valign="middle" align="left">Colon cancer</td>
                <td valign="middle" align="center">2 (%2.38)</td>
              </tr>
              <tr>
                <td valign="middle" align="left">Testis cancer</td>
                <td valign="middle" align="center">2 (%2.38)</td>
              </tr>
              <tr style="background-color:#C7DFEC">
                <td valign="middle" align="left">Bladder cancer</td>
                <td valign="middle" align="center">1 (%1.19)</td>
              </tr>
              <tr>
                <td valign="middle" align="left">Soft tissue cancer</td>
                <td valign="middle" align="center">1 (%1.19)</td>
              </tr>
              <tr style="background-color:#C7DFEC">
                <td valign="middle" align="left">Thyroid cancer</td>
                <td valign="middle" align="center">1 (%1.19)</td>
              </tr>
            </tbody>
          </table>
        </table-wrap>
        <p>The incidence of cancer was higher in the male gender. Among the compared laboratory parameters, hemoglobin, albumin, and lymphocyte values were found at lower levels in cancer patients, while the CRP value was found at higher levels. In the comparison between scoring systems, the HALP and PNI scores proved to be lower in cancer patients, while the SII value was higher. No significant difference was found between the two groups except for sex, hemoglobin, albumin, lymphocyte, CRP, HALP, SII, and PNI parameters (<xref ref-type="table" rid="t5">Table 2</xref>).</p>
        <table-wrap id="t5">
          <label>Table 2</label>
          <caption>
            <title>Comparison of cancer status and various variables</title>
          </caption>
          <table frame="hsides" rules="none">
            <colgroup width="24%">
              <col width="1%"/>
              <col/>
              <col/>
              <col/>
              <col/>
            </colgroup>
            <thead style="border-top: thin solid; border-bottom: thin solid; border-color: #000000">
              <tr style="background-color:#76B4CF">
                <th valign="middle" align="left" rowspan="2" colspan="2">Variables</th>
                <th valign="middle" align="center" colspan="2" style="border-bottom: thin solid; border-top: thin solid; border-color: #000000">Cancer</th>
                <th valign="middle" align="center" rowspan="2">p-value</th>
              </tr>
              <tr style="background-color:#76B4CF">
                <th valign="middle" align="center">No<break/> (n=199)</th>
                <th valign="middle" align="center">Yes<break/> (n=84)</th>
              </tr>
            </thead>
            <tbody style="border-bottom: thin solid; border-color: #000000">
              <tr>
                <td valign="middle" align="left" colspan="2">Age (years)</td>
                <td valign="middle" align="center">63&#177;15.9</td>
                <td valign="middle" align="center">60.6&#177;16</td>
                <td valign="middle" align="center">0.26</td>
              </tr>
              <tr style="background-color:#C7DFEC">
                <td valign="middle" align="left" colspan="2">Sex n(%)</td>
                <td valign="middle" align="center"/>
                <td valign="middle" align="center"/>
                <td valign="middle" align="center"/>
              </tr>
              <tr style="background-color:#C7DFEC">
                <td valign="middle" align="left"/>
                <td valign="middle" align="left">Female</td>
                <td valign="middle" align="center">114(57.2)</td>
                <td valign="middle" align="center">36(42.8)</td>
                <td valign="middle" align="center">0.028</td>
              </tr>
              <tr style="background-color:#C7DFEC">
                <td valign="middle" align="left"/>
                <td valign="middle" align="left">Male</td>
                <td valign="middle" align="center">85(42.8)</td>
                <td valign="middle" align="center">48(57.2)</td>
                <td valign="middle" align="left"/>
              </tr>
              <tr>
                <td valign="middle" align="left" colspan="2">LVEF (%)</td>
                <td valign="middle" align="center">50.7&#177;12.8</td>
                <td valign="middle" align="center">51&#177;13.4</td>
                <td valign="middle" align="center">0.64</td>
              </tr>
              <tr style="background-color:#C7DFEC">
                <td valign="middle" align="left" colspan="2">HT n(%)</td>
                <td valign="middle" align="center">47(23.6)</td>
                <td valign="middle" align="center">16(19)</td>
                <td valign="middle" align="center">0.44</td>
              </tr>
              <tr>
                <td valign="middle" align="left" colspan="2">CAD n(%)</td>
                <td valign="middle" align="center">14(7)</td>
                <td valign="middle" align="center">3(3.6)</td>
                <td valign="middle" align="center">0.411</td>
              </tr>
              <tr style="background-color:#C7DFEC">
                <td valign="middle" align="left" colspan="2">Hemoglobin (g/dL)</td>
                <td valign="middle" align="center">13.1&#177;1.9</td>
                <td valign="middle" align="center">11&#177;1.7</td>
                <td valign="middle" align="center">&lt;0.001</td>
              </tr>
              <tr>
                <td valign="middle" align="left" colspan="2">RBC (10<sup>6</sup>/uL)</td>
                <td valign="middle" align="center">4.45&#177;0.79</td>
                <td valign="middle" align="center">4.29&#177;0.82</td>
                <td valign="middle" align="center">0.14</td>
              </tr>
              <tr style="background-color:#C7DFEC">
                <td valign="middle" align="left" colspan="2">WBC (10<sup>3</sup>/uL)</td>
                <td valign="middle" align="center">9.3&#177;4.3</td>
                <td valign="middle" align="center">8.6&#177;4.7</td>
                <td valign="middle" align="center">0.2</td>
              </tr>
              <tr>
                <td valign="middle" align="left" colspan="2">LDL (mg/dL)</td>
                <td valign="middle" align="center">97.2&#177;40</td>
                <td valign="middle" align="center">90.7&#177;38.2</td>
                <td valign="middle" align="center">0.25</td>
              </tr>
              <tr style="background-color:#C7DFEC">
                <td valign="middle" align="left" colspan="2">HDL (mg/dL)</td>
                <td valign="middle" align="center">35.9&#177;14.8</td>
                <td valign="middle" align="center">34&#177;14.3</td>
                <td valign="middle" align="center">0.35</td>
              </tr>
              <tr>
                <td valign="middle" align="left" colspan="2">DM n(%)</td>
                <td valign="middle" align="center">33(18.0)</td>
                <td valign="middle" align="center">8(11.3)</td>
                <td valign="middle" align="center">0.138</td>
              </tr>
              <tr style="background-color:#C7DFEC">
                <td valign="middle" align="left" colspan="2">Uric asid (mg/dL)</td>
                <td valign="middle" align="center">6.27&#177;2.4</td>
                <td valign="middle" align="center">6.15&#177;2.3</td>
                <td valign="middle" align="center">0.76</td>
              </tr>
              <tr>
                <td valign="middle" align="left" colspan="2">BUN (mg/dL)</td>
                <td valign="middle" align="center">20.4&#177;14.6</td>
                <td valign="middle" align="center">19.7&#177;11.7</td>
                <td valign="middle" align="center">0.672</td>
              </tr>
              <tr style="background-color:#C7DFEC">
                <td valign="middle" align="left" colspan="2">Creatinine (mg/dL)</td>
                <td valign="middle" align="center">0.8(0.7-1.0)</td>
                <td valign="middle" align="center">0.9(0.7-1.0)</td>
                <td valign="middle" align="center">0.128</td>
              </tr>
              <tr>
                <td valign="middle" align="left" colspan="2">GFR (ml/min/m2)</td>
                <td valign="middle" align="center">79.7&#177;21.9</td>
                <td valign="middle" align="center">83.2&#177;17.4</td>
                <td valign="middle" align="center">0.15</td>
              </tr>
              <tr style="background-color:#C7DFEC">
                <td valign="middle" align="left" colspan="2">BASO (10<sup>3</sup>/uL)</td>
                <td valign="middle" align="center">0.02(0.01-0.04)</td>
                <td valign="middle" align="center">0.02(0.01-0.05)</td>
                <td valign="middle" align="center">0.16</td>
              </tr>
              <tr>
                <td valign="middle" align="left" colspan="2">EO (10<sup>3</sup>/uL)</td>
                <td valign="middle" align="center">0.08(0.01-0.18)</td>
                <td valign="middle" align="center">0.07(0.02-0.16)</td>
                <td valign="middle" align="center">0.78</td>
              </tr>
              <tr style="background-color:#C7DFEC">
                <td valign="middle" align="left" colspan="2">HCT (%)</td>
                <td valign="middle" align="center">38.3&#177;5.9</td>
                <td valign="middle" align="center">37.4&#177;7</td>
                <td valign="middle" align="center">0.271</td>
              </tr>
              <tr>
                <td valign="middle" align="left" colspan="2">MCH</td>
                <td valign="middle" align="center">28.3&#177;4.7</td>
                <td valign="middle" align="center">28.3&#177;2.6</td>
                <td valign="middle" align="center">0.91</td>
              </tr>
              <tr style="background-color:#C7DFEC">
                <td valign="middle" align="left" colspan="2">MCV (fL)</td>
                <td valign="middle" align="center">85.8&#177;8.10</td>
                <td valign="middle" align="center">86.8&#177;8.1</td>
                <td valign="middle" align="center">0.61</td>
              </tr>
              <tr>
                <td valign="middle" align="left" colspan="2">MONO (10<sup>3</sup>/uL)</td>
                <td valign="middle" align="center">0.55(0.40-0.80)</td>
                <td valign="middle" align="center">0.55(0.38-0.80)</td>
                <td valign="middle" align="center">0.37</td>
              </tr>
              <tr style="background-color:#C7DFEC">
                <td valign="middle" align="left" colspan="2">MPV (fL)</td>
                <td valign="middle" align="center">9.3&#177;1.26</td>
                <td valign="middle" align="center">9.3&#177;1.46</td>
                <td valign="middle" align="center">0.34</td>
              </tr>
              <tr>
                <td valign="middle" align="left" colspan="2">NEUT (10<sup>3</sup>/uL)</td>
                <td valign="middle" align="center">7.4&#177;4.6</td>
                <td valign="middle" align="center">7.2&#177;4.4</td>
                <td valign="middle" align="center">0.69</td>
              </tr>
              <tr style="background-color:#C7DFEC">
                <td valign="middle" align="left" colspan="2">PCT (%)</td>
                <td valign="middle" align="center">0.24&#177;0.11</td>
                <td valign="middle" align="center">0.23&#177;0.15</td>
                <td valign="middle" align="center">0.36</td>
              </tr>
              <tr>
                <td valign="middle" align="left" colspan="2">PDW (%)</td>
                <td valign="middle" align="center">19.55&#177;11.6</td>
                <td valign="middle" align="center">18.2&#177;10.3</td>
                <td valign="middle" align="center">0.37</td>
              </tr>
              <tr style="background-color:#C7DFEC">
                <td valign="middle" align="left" colspan="2">RDW (%)</td>
                <td valign="middle" align="center">15.5&#177;2.6</td>
                <td valign="middle" align="center">15.5&#177;2.6</td>
                <td valign="middle" align="center">0.37</td>
              </tr>
              <tr>
                <td valign="middle" align="left" colspan="2">Albumin (g/dL)</td>
                <td valign="middle" align="center">3.92&#177;0.45</td>
                <td valign="middle" align="center">3.3&#177;0.56</td>
                <td valign="middle" align="center">&lt;0.001</td>
              </tr>
              <tr style="background-color:#C7DFEC">
                <td valign="middle" align="left" colspan="2">Lymphocyte (10<sup>3</sup>/uL)</td>
                <td valign="middle" align="center">1.84&#177;0.66</td>
                <td valign="middle" align="center">1.29&#177;0.81</td>
                <td valign="middle" align="center">&lt;0.001</td>
              </tr>
              <tr>
                <td valign="middle" align="left" colspan="2">Platelet (10<sup>3</sup>/uL)</td>
                <td valign="middle" align="center">234&#177;88.7</td>
                <td valign="middle" align="center">259.7&#177;122.00</td>
                <td valign="middle" align="center">0.095</td>
              </tr>
              <tr style="background-color:#C7DFEC">
                <td valign="middle" align="left" colspan="2">Total cholesterol</td>
                <td valign="middle" align="center">162.4&#177;52.00</td>
                <td valign="middle" align="center">152.6&#177;47.8</td>
                <td valign="middle" align="center">0.18</td>
              </tr>
              <tr>
                <td valign="middle" align="left" colspan="2">CRP (mg/L)</td>
                <td valign="middle" align="center">24.7(8.4-81.2)</td>
                <td valign="middle" align="center">56.0(15.0-119.0)</td>
                <td valign="middle" align="center">0.006</td>
              </tr>
              <tr style="background-color:#C7DFEC">
                <td valign="middle" align="left" colspan="2">HALP</td>
                <td valign="middle" align="center">0.32(0.20-0.49)</td>
                <td valign="middle" align="center">0.173(0.125-0.175)</td>
                <td valign="middle" align="center">&lt;0.001</td>
              </tr>
              <tr>
                <td valign="middle" align="left" colspan="2">SII</td>
                <td valign="middle" align="center">857.8(528-1664)</td>
                <td valign="middle" align="center">1329.8(697-2272.2)</td>
                <td valign="middle" align="center">&lt;0.001</td>
              </tr>
              <tr style="background-color:#C7DFEC">
                <td valign="middle" align="left" colspan="2">PNI</td>
                <td valign="middle" align="center">39.8&#177;4.8</td>
                <td valign="middle" align="center">33.1&#177;5.6</td>
                <td valign="middle" align="center">&lt;0.001</td>
              </tr>
            </tbody>
          </table>
          <table-wrap-foot>
            <fn id="TFN3">
              <p>Data are expressed as n(%), mean &#177; standard deviation, median(1st quartile - 3rd quartile). LVEF: left ventricular ejection fraction; HT: hypertension; CAD: coronary artery disease; RBC: red blood cells; WBC: white blood cells; LDL: low density lipoprotein; HDL: high density lipoprotein; DM: diabetes mellitus; BUN: blood urea nitrogen; GFR: glomerular filtration rate; BASO: basophil; EO: eosinophil; HCT: hematocrit; MCH: mean corpuscular hemoglobin; MCV: mean corpuscular volume; Mono: monocyte; MPV: mean platelet volume; NEUT: neutrophyl; PCT: procalcitonin; PDW: platelet distribution width; RDW: redcell distribution width; CRP: C-reactive protein; SII: systemic immune-inflammation index; PNI: prognostic nutritional index.</p>
            </fn>
          </table-wrap-foot>
        </table-wrap>
        <p>In multiple logistic regression analysis, HALP and PNI proved to be independent predictors of cancer metastasis in patients with pericardial effusion (<xref ref-type="table" rid="t6">Table 3</xref>).</p>
        <table-wrap id="t6">
          <label>Table 3</label>
          <caption>
            <title>Evaluation of risk factors that may affect definitive cancer status</title>
          </caption>
          <table frame="hsides" rules="none">
            <colgroup width="19%">
              <col width="1%"/>
              <col/>
              <col/>
              <col/>
              <col/>
              <col/>
            </colgroup>
            <thead style="border-top: thin solid; border-bottom: thin solid; border-color: #000000">
              <tr style="background-color:#76B4CF">
                <th valign="middle" align="left" colspan="2" rowspan="3">Variables</th>
                <th valign="middle" align="center" colspan="4" style="border-bottom: thin solid; border-top: thin solid; border-color: #000000">Cancer</th>
              </tr>
              <tr style="background-color:#76B4CF">
                <th valign="middle" align="center" colspan="2">Univariate analyses</th>
                <th valign="middle" align="center" colspan="2">Multivariate analyses</th>
              </tr>
              <tr style="background-color:#76B4CF">
                <th valign="middle" align="center">Odds Ratio (95% CI)</th>
                <th valign="middle" align="center">p-value</th>
                <th valign="middle" align="center">Odds Ratio (95% CI)</th>
                <th valign="middle" align="center">p-value</th>
              </tr>
            </thead>
            <tbody style="border-bottom: thin solid; border-color: #000000">
              <tr>
                <td valign="middle" align="left" colspan="2">Sex n(%)</td>
                <td valign="middle" align="center"/>
                <td valign="middle" align="center"/>
                <td valign="middle" align="center"/>
                <td valign="middle" align="center" rowspan="3"/>
              </tr>
              <tr>
                <td valign="middle" align="left"/>
                <td valign="middle" align="left">Female</td>
                <td valign="middle" align="center">1</td>
                <td valign="middle" align="center">0.027</td>
                <td valign="middle" align="center"/>
              </tr>
              <tr>
                <td valign="middle" align="left"/>
                <td valign="middle" align="left">Male</td>
                <td valign="middle" align="center">1.788(1.068-2.994)</td>
                <td valign="middle" align="center"/>
                <td valign="middle" align="center"/>
              </tr>
              <tr style="background-color:#C7DFEC">
                <td valign="middle" align="left" colspan="2">Hemoglobin (g/dL)</td>
                <td valign="middle" align="center">0.514(0.427-0.619)</td>
                <td valign="middle" align="center">&lt;0.001</td>
                <td valign="middle" align="center"/>
                <td valign="middle" align="center"/>
              </tr>
              <tr>
                <td valign="middle" align="left" colspan="2">Albumin (g/dL)</td>
                <td valign="middle" align="center">0.066(0.027-0.158)</td>
                <td valign="middle" align="center">&lt;0.001</td>
                <td valign="middle" align="center"/>
                <td valign="middle" align="center"/>
              </tr>
              <tr style="background-color:#C7DFEC">
                <td valign="middle" align="left" colspan="2">Lymphocyte (10<sup>3</sup>/uL)</td>
                <td valign="middle" align="center">0.318(0.174-0.583)</td>
                <td valign="middle" align="center">&lt;0.001</td>
                <td valign="middle" align="center"/>
                <td valign="middle" align="center"/>
              </tr>
              <tr>
                <td valign="middle" align="left" colspan="2">HALP</td>
                <td valign="middle" align="center">0.003(0.001-0.041)</td>
                <td valign="middle" align="center">&lt;0.001</td>
                <td valign="middle" align="center">0.006(0.001-0.090)</td>
                <td valign="middle" align="center">&lt;0.001</td>
              </tr>
              <tr style="background-color:#C7DFEC">
                <td valign="middle" align="left" colspan="2">PNI</td>
                <td valign="middle" align="center">0.831(0.773-0.894)</td>
                <td valign="middle" align="center">&lt;0.001</td>
                <td valign="middle" align="center">0.825(0.763-0.893)</td>
                <td valign="middle" align="center">&lt;0.001</td>
              </tr>
              <tr>
                <td valign="middle" align="left" colspan="2">Age (years)</td>
                <td valign="middle" align="center">991(975-1007)</td>
                <td valign="middle" align="center">0.262</td>
                <td valign="middle" align="center"/>
                <td valign="middle" align="center"/>
              </tr>
              <tr style="background-color:#C7DFEC">
                <td valign="middle" align="left" colspan="2">DM n(%)</td>
                <td valign="middle" align="center">515(227-1172)</td>
                <td valign="middle" align="center">0.114</td>
                <td valign="middle" align="center"/>
                <td valign="middle" align="center"/>
              </tr>
              <tr>
                <td valign="middle" align="left" colspan="2">Creatinine (mg/dL)</td>
                <td valign="middle" align="center">848(646-1113)</td>
                <td valign="middle" align="center">0.236</td>
                <td valign="middle" align="center"/>
                <td valign="middle" align="center"/>
              </tr>
              <tr style="background-color:#C7DFEC">
                <td valign="middle" align="left" colspan="2">Platelet (10<sup>3</sup>/uL)</td>
                <td valign="middle" align="center">1002(1000-1005)</td>
                <td valign="middle" align="center">0.059</td>
                <td valign="middle" align="center"/>
                <td valign="middle" align="center"/>
              </tr>
              <tr>
                <td valign="middle" align="left" colspan="2">CRP (mg/L)</td>
                <td valign="middle" align="center">1005(1002-1009)</td>
                <td valign="middle" align="center">0.004</td>
                <td valign="middle" align="center"/>
                <td valign="middle" align="center"/>
              </tr>
              <tr style="background-color:#C7DFEC">
                <td valign="middle" align="left" colspan="2">SII</td>
                <td valign="middle" align="center">1000(1000-1001)</td>
                <td valign="middle" align="center">&lt;0.001</td>
                <td valign="middle" align="center"/>
                <td valign="middle" align="center"/>
              </tr>
            </tbody>
          </table>
          <table-wrap-foot>
            <fn id="TFN4">
              <p>CI: confidence &#305;nterval; HALP: hemoglobin-albumin-lymphocyte-platelet index; PNI: prognostic nutritional index; DM: diabetes mellitus; CRP: C-reactive protein; SII: systemic immune-inflamation index.</p>
            </fn>
          </table-wrap-foot>
        </table-wrap>
        <p>ROC analysis was performed to find the ideal cut-off values of HALP and PNI to predict cancer metastasis in patients with pericardial effusion. A HALP value of &lt;0.2524 has an 80% sensitivity and an 81.4% specificity to predict cancer metastasis in patients with pericardial effusion. A PNI value of &lt;36.18 has a sensitivity of 74% and a specificity of 74.9% in predicting cancer metastasis in patients with pericardial effusion. The AUC of HALP proved to be higher than the AUC of PNI in predicting cancer metastasis in patients with pericardial effusion (<xref ref-type="fig" rid="f3">Figure 1</xref>).</p>
        <fig id="f3">
          <label>Figure 1</label>
          <caption>
            <title>ROC graphs of HALP and PNI scores. HALP: hemoglobin-albumin-lymphocyte-platelet index; PNI: prognostic nutritional index.</title>
          </caption>
          <graphic xlink:href="1678-4170-abc-121-01-e20230376-30376-gf02-en.tif"/></fig>
      </sec>
      <sec sec-type="discussion">
        <title>Discussion</title>
        <p>To the best of our knowledge, this is the first study to compare HALP, SII, and PNI scores in cancer research among patients with pericardial effusion who underwent pericardiocentesis, and to look at the effect of these scoring systems on cancer development. In this study, HALP proved to have a greater predictive power for cancer metastasis than did PNI and SII. HALP can be used to predict cancer in patients undergoing cancer research, considering that it is an easy, quick, and effective biomarker. The HALP score in gastrointestinal cancers, including gastric cancer,<sup><xref ref-type="bibr" rid="B17">17</xref></sup> esophageal squamous cell cance,<sup><xref ref-type="bibr" rid="B18">18</xref></sup> advanced colorectal cancer,<sup><xref ref-type="bibr" rid="B4">4</xref></sup> as well as in genitourinary cancers, including bladder cancer<sup><xref ref-type="bibr" rid="B5">5</xref></sup> and renal cell carcinoma,<sup><xref ref-type="bibr" rid="B19">19</xref></sup> has proven to have a prognostic role. It is also a very comprehensive index that shows both the nutritional and immune status of patients. Previous studies have shown that a high HALP score in other tumors can predict good therapeutic outcomes and prognosis.<sup><xref ref-type="bibr" rid="B4">4</xref>,<xref ref-type="bibr" rid="B17">17</xref>,<xref ref-type="bibr" rid="B19">19</xref></sup></p>
        <p>The HALP and PNI scores have quite similar diagnostic performances in determining the status of cancer metastasis; however, the HALP score appears to be stronger than the PNI. Many studies have shown that PNI plays a role in cancer prognosis.<sup><xref ref-type="bibr" rid="B13">13</xref></sup> The most important reason why PNI can provide a reliable prediction of the prognosis in cancer patients is that lymphocytes help the immune system and hinder proliferation and metastasis in cancer cells.<sup><xref ref-type="bibr" rid="B13">13</xref></sup> Serum albumin, another PNI component, can predict the prognosis by reflecting the nutritional status of the body, which is a determining factor in the immune reactions of cancer cells.<sup><xref ref-type="bibr" rid="B13">13</xref></sup> In many studies, low-level PNI has been associated with outcomes, including cancer with negative tumor characteristics in lung cancer, poorly differentiated cancer, large-sized cancer, and metastasis.<sup><xref ref-type="bibr" rid="B20">20</xref></sup> It has been shown that a lower PNI level can predict a more aggressive cancer and a worse prognosis of lung cancer.<sup><xref ref-type="bibr" rid="B21">21</xref></sup> In our study, the PNI level proved to be quite low in patients with cancer metastasis.</p>
        <p>Among the most important factors in the cancer inflammation pathway are chemokines, cytokines, and small inflammatory proteins, all of which provide intracellular communication in the tumor microenvironment, as well as connection and communication between cells, which is very important when predicting invasion, angiogenesis, tumor growth, and metastasis. In addition, tumor necrosis and cytokine-mediated transcription factor activation also play important roles.<sup><xref ref-type="bibr" rid="B6">6</xref></sup> The inflammatory process in pericardial effusion occurs depending on the pathological process. Accordingly, fluid production in the pericardial area increases. SII shows us the balance between the inflammatory and immune processes.<sup><xref ref-type="bibr" rid="B22">22</xref></sup> SII proved to be a promising index for hepatocellular carcinoma, gastric cancer, small cell lung cancer, and prostate cancer.<sup><xref ref-type="bibr" rid="B23">23</xref></sup> A high SII level indicates changes that favor cancer initiation, progression, and metastasis in cancer patients.<sup><xref ref-type="bibr" rid="B8">8</xref></sup> This can be explained by the fact that the SII levels of the cancer patients group were higher than those of the patients in the non-cancer group.</p>
        <p>In our study, the most common cancer causing pericardial effusion was lung cancer, followed by breast and stomach cancer. Prostate and colorectal cancer in men and breast and colorectal cancers in women are also common cancers, similar to lung cancer. However, it was observed that these types of cancer did not cause pericardial effusion as much as lung cancer did. This may be related to the fact that lung cancer metastasizes more to the pericardium.<sup><xref ref-type="bibr" rid="B21">21</xref></sup> In addition, in this study, the male sex ratio proved to be higher among patients with cancer. According to the Global Cancer Statistics report, lung cancer incidence and death rates are reported to be approximately 2-fold higher in men than in women.<sup><xref ref-type="bibr" rid="B21">21</xref></sup> According to data obtained from the Turkey Lung Cancer Map Project, 90.4% of all lung cancer cases are male.<sup><xref ref-type="bibr" rid="B24">24</xref></sup> Since lung cancer is most common in men, the high rate of cancer in men in our study can be explained in a similar manner. In addition, the low number of people diagnosed with cancer may have to the results from our study. Therefore, larger studies with a larger numbers of patients are warranted.</p>
        <p>Anemia, which is among the cancer-related comorbidities, is frequently seen at the time of diagnosis<sup><xref ref-type="bibr" rid="B25">25</xref></sup> and is commonly caused by chronic inflammation associated with cancer.<sup><xref ref-type="bibr" rid="B26">26</xref></sup> In our study, the low hemoglobin level in patients diagnosed with cancer can be explained by chronic inflammation. However, since the etiology of anemia in cancer patients has not been investigated in detail, the causes of low hemoglobin have not been fully clarified.</p>
        <p>In cancer patients, hypoalbuminemia has been associated with a systemic inflammatory reaction and malnutrition in patients.<sup><xref ref-type="bibr" rid="B27">27</xref></sup> Increased CRP levels have been associated with decreased T lymphocyte response to cancer cells.<sup><xref ref-type="bibr" rid="B28">28</xref></sup> In our study, high CRP and low albumin values in cancer patients can be explained in a similar manner.</p>
        <p>Recent studies show us that a systemic inflammatory response may play an important role in the development and progression of cancer.<sup><xref ref-type="bibr" rid="B29">29</xref></sup> Cancer-related systemic inflammation causes lymphopenia in patients,<sup><xref ref-type="bibr" rid="B30">30</xref></sup> which provides a logical explanation for the low lymphocyte levels in cancer patients in the present study.</p>
        <sec>
          <title>Limitations</title>
          <p>This study has several limitations. It is a retrospective study. Therefore, the prognosis could not be commented on, as the patients did not receive follow-up. More large-scale, multicenter studies with follow-up are needed to define the role of HALP and PNI in the pathophysiology of cancer. Although this study identified an association between those scores and a malignant pericardial effusion, those scores are meant to determine prognosis in those who were already diagnosed with cancer. Those scores can be realtively high in any chronic disease, which can lead to misleading results.</p>
        </sec>
      </sec>
      <sec sec-type="conclusions">
        <title>Conclusion</title>
        <p>HALP and PNI are scoring systems with high predictive power for cancer metastasis. These scoring systems are easy, quick, and effective tests that can be used in cancer screening.</p>
      </sec>
    </body>
    <back>
      <fn-group>
        <fn fn-type="financial-disclosure" id="fn4">
          <p>
            <bold>Sources of funding</bold>
          </p>
          <p>There were no external funding sources for this study.</p>
        </fn>
        <fn fn-type="other" id="fn5">
          <p>
            <bold>Study association</bold>
          </p>
          <p>This study is not associated with any thesis or dissertation work.</p>
        </fn>
        <fn fn-type="other" id="fn6">
          <p>
            <bold>Ethics approval and consent to participate</bold>
          </p>
          <p>This study was approved by the Ethics Committee of the Sivas Cumhuriyet University Ethics Committee under the protocol number 2022-10/11. 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>
    </back>
  </sub-article>
</article>
