A novel model to estimate lymph node metastasis in endometrial cancer patients
Identifieur interne : 003D57 ( Pmc/Curation ); précédent : 003D56; suivant : 003D58A novel model to estimate lymph node metastasis in endometrial cancer patients
Auteurs : Cristina Anton [Brésil] ; Alexandre Silva E Silva [Brésil] ; Edmund Chada Baracat [Brésil] ; Nasuh Utku Dogan [Turquie] ; Christhardt Köhler ; Jesus Paula Carvalho [Brésil] ; Giovanni Mastrantonio Di FaveroSource :
- Clinics [ 1807-5932 ] ; 2017.
Abstract
To evaluate the postoperative pathological characteristics of hysterectomy specimens, preoperative cancer antigen (CA)-125 levels and imaging modalities in patients with endometrial cancer and to build a risk matrix model to identify and recruit patients for retroperitoneal lymphadenectomy.
A total of 405 patients undergoing surgical treatment for endometrial cancer were retrospectively reviewed and analyzed. Clinical (age and body mass index), laboratory (CA-125), radiological (lymph node evaluation), and pathological (tumour size, grade, lymphovascular space invasion, lymph node metastasis, and myometrial invasion) parameters were used to test the ability to predict lymph node metastasis. Four parameters were selected by logistic regression to create a risk matrix for nodal metastasis.
Of the 405 patients, 236 (58.3%) underwent complete pelvic and para-aortic lymphadenectomy, 96 (23.7%) underwent nodal sampling, and 73 (18%) had no surgical lymph node assessment. The parameters predicting nodal involvement obtained through logistic regression were myometrial infiltration >50%, lymphovascular space involvement, pelvic lymph node involvement by imaging, and a CA-125 value >21.5 U/mL. According to our risk matrix, the absence of these four parameters implied a risk of lymph node metastasis of 2.7%, whereas in the presence of all four parameters the risk was 82.3%.
Patients without deep myometrial invasion and lymphovascular space involvement on the final pathological examination and with normal CA-125 values and lymph node radiological examinations have a relatively low risk of lymph node involvement. This risk assessment matrix may be able to refer patients with high-risk parameters necessitating lymphadenectomy and to decide the risks and benefits of lymphadenectomy.
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DOI: 10.6061/clinics/2017(01)06
PubMed: 28226030
PubMed Central: 5251192
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Nasuh Utku Dogan<affiliation><nlm:aff id="af2-cln_72p30">Asklepios Hospital Hamburg, Department of Advanced Operative and Oncologic Gynecology, GermanyGermany</nlm:aff><wicri:noCountry code="subfield">GermanyGermany</wicri:noCountry></affiliation><affiliation wicri:level="1"><nlm:aff id="af3-cln_72p30">Akdeniz University, Department of Obstetrics and Gynecology, Antalya, Turkey</nlm:aff><country xml:lang="fr">Turquie</country><wicri:regionArea>Akdeniz University, Department of Obstetrics and Gynecology, Antalya</wicri:regionArea></affiliation><affiliation><nlm:aff id="af2-cln_72p30">Asklepios Hospital Hamburg, Department of Advanced Operative and Oncologic Gynecology, GermanyGermany</nlm:aff><wicri:noCountry code="subfield">GermanyGermany</wicri:noCountry></affiliation><affiliation><nlm:aff id="af2-cln_72p30">Asklepios Hospital Hamburg, Department of Advanced Operative and Oncologic Gynecology, GermanyGermany</nlm:aff><wicri:noCountry code="subfield">GermanyGermany</wicri:noCountry></affiliation>Le document en format XML
<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">A novel model to estimate lymph node metastasis in endometrial cancer patients</title><author><name sortKey="Anton, Cristina" sort="Anton, Cristina" uniqKey="Anton C" first="Cristina" last="Anton">Cristina Anton</name><affiliation wicri:level="1"><nlm:aff id="af1-cln_72p30">Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo, Instituto do Câncer do Estado de São Paulo – ICESP, Departamento de Ginecologia e Obstetrícia, São Paulo/SP, Brazil</nlm:aff><country xml:lang="fr">Brésil</country><wicri:regionArea>Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo, Instituto do Câncer do Estado de São Paulo – ICESP, Departamento de Ginecologia e Obstetrícia, São Paulo/SP</wicri:regionArea></affiliation></author><author><name sortKey="E Silva, Alexandre Silva" sort="E Silva, Alexandre Silva" uniqKey="E Silva A" first="Alexandre Silva" last="E Silva">Alexandre Silva E 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xml:lang="fr">Brésil</country><wicri:regionArea>Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo, Instituto do Câncer do Estado de São Paulo – ICESP, Departamento de Ginecologia e Obstetrícia, São Paulo/SP</wicri:regionArea></affiliation></author><author><name sortKey="Dogan, Nasuh Utku" sort="Dogan, Nasuh Utku" uniqKey="Dogan N" first="Nasuh Utku" last="Dogan">Nasuh Utku Dogan</name><affiliation><nlm:aff id="af2-cln_72p30">Asklepios Hospital Hamburg, Department of Advanced Operative and Oncologic Gynecology, GermanyGermany</nlm:aff><wicri:noCountry code="subfield">GermanyGermany</wicri:noCountry></affiliation><affiliation wicri:level="1"><nlm:aff id="af3-cln_72p30">Akdeniz University, Department of Obstetrics and Gynecology, Antalya, Turkey</nlm:aff><country xml:lang="fr">Turquie</country><wicri:regionArea>Akdeniz University, Department of Obstetrics and Gynecology, Antalya</wicri:regionArea></affiliation></author><author><name sortKey="Kohler, Christhardt" sort="Kohler, Christhardt" uniqKey="Kohler C" first="Christhardt" last="Köhler">Christhardt Köhler</name><affiliation><nlm:aff id="af2-cln_72p30">Asklepios Hospital Hamburg, Department of Advanced Operative and Oncologic Gynecology, GermanyGermany</nlm:aff><wicri:noCountry code="subfield">GermanyGermany</wicri:noCountry></affiliation></author><author><name sortKey="Carvalho, Jesus Paula" sort="Carvalho, Jesus Paula" uniqKey="Carvalho J" first="Jesus Paula" last="Carvalho">Jesus Paula Carvalho</name><affiliation wicri:level="1"><nlm:aff id="af1-cln_72p30">Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo, Instituto do Câncer do Estado de São Paulo – ICESP, Departamento de Ginecologia e Obstetrícia, São Paulo/SP, Brazil</nlm:aff><country xml:lang="fr">Brésil</country><wicri:regionArea>Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo, Instituto do Câncer do Estado de São Paulo – ICESP, Departamento de Ginecologia e Obstetrícia, São Paulo/SP</wicri:regionArea></affiliation></author><author><name sortKey="Di Favero, Giovanni Mastrantonio" sort="Di Favero, Giovanni Mastrantonio" uniqKey="Di Favero G" first="Giovanni Mastrantonio" last="Di Favero">Giovanni Mastrantonio Di Favero</name><affiliation><nlm:aff id="af2-cln_72p30">Asklepios Hospital Hamburg, Department of Advanced Operative and Oncologic Gynecology, GermanyGermany</nlm:aff><wicri:noCountry code="subfield">GermanyGermany</wicri:noCountry></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">PMC</idno><idno type="pmid">28226030</idno><idno type="pmc">5251192</idno><idno type="url">http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5251192</idno><idno type="RBID">PMC:5251192</idno><idno type="doi">10.6061/clinics/2017(01)06</idno><date when="2017">2017</date><idno type="wicri:Area/Pmc/Corpus">003D58</idno><idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Corpus" wicri:corpus="PMC">003D58</idno><idno 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sortKey="E Silva, Alexandre Silva" sort="E Silva, Alexandre Silva" uniqKey="E Silva A" first="Alexandre Silva" last="E Silva">Alexandre Silva E Silva</name><affiliation wicri:level="1"><nlm:aff id="af1-cln_72p30">Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo, Instituto do Câncer do Estado de São Paulo – ICESP, Departamento de Ginecologia e Obstetrícia, São Paulo/SP, Brazil</nlm:aff><country xml:lang="fr">Brésil</country><wicri:regionArea>Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo, Instituto do Câncer do Estado de São Paulo – ICESP, Departamento de Ginecologia e Obstetrícia, São Paulo/SP</wicri:regionArea></affiliation></author><author><name sortKey="Baracat, Edmund Chada" sort="Baracat, Edmund Chada" uniqKey="Baracat E" first="Edmund Chada" last="Baracat">Edmund Chada Baracat</name><affiliation wicri:level="1"><nlm:aff id="af1-cln_72p30">Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo, Instituto do Câncer do Estado de São Paulo – ICESP, Departamento de Ginecologia e Obstetrícia, São Paulo/SP, Brazil</nlm:aff><country xml:lang="fr">Brésil</country><wicri:regionArea>Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo, Instituto do Câncer do Estado de São Paulo – ICESP, Departamento de Ginecologia e Obstetrícia, São Paulo/SP</wicri:regionArea></affiliation></author><author><name sortKey="Dogan, Nasuh Utku" sort="Dogan, Nasuh Utku" uniqKey="Dogan N" first="Nasuh Utku" last="Dogan">Nasuh Utku Dogan</name><affiliation><nlm:aff id="af2-cln_72p30">Asklepios Hospital Hamburg, Department of Advanced Operative and Oncologic Gynecology, GermanyGermany</nlm:aff><wicri:noCountry code="subfield">GermanyGermany</wicri:noCountry></affiliation><affiliation wicri:level="1"><nlm:aff id="af3-cln_72p30">Akdeniz University, Department of Obstetrics and Gynecology, Antalya, Turkey</nlm:aff><country xml:lang="fr">Turquie</country><wicri:regionArea>Akdeniz University, Department of Obstetrics and Gynecology, Antalya</wicri:regionArea></affiliation></author><author><name sortKey="Kohler, Christhardt" sort="Kohler, Christhardt" uniqKey="Kohler C" first="Christhardt" last="Köhler">Christhardt Köhler</name><affiliation><nlm:aff id="af2-cln_72p30">Asklepios Hospital Hamburg, Department of Advanced Operative and Oncologic Gynecology, GermanyGermany</nlm:aff><wicri:noCountry code="subfield">GermanyGermany</wicri:noCountry></affiliation></author><author><name sortKey="Carvalho, Jesus Paula" sort="Carvalho, Jesus Paula" uniqKey="Carvalho J" first="Jesus Paula" last="Carvalho">Jesus Paula Carvalho</name><affiliation wicri:level="1"><nlm:aff id="af1-cln_72p30">Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo, Instituto do Câncer do Estado de São Paulo – ICESP, Departamento de Ginecologia e Obstetrícia, São Paulo/SP, Brazil</nlm:aff><country xml:lang="fr">Brésil</country><wicri:regionArea>Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo, Instituto do Câncer do Estado de São Paulo – ICESP, Departamento de Ginecologia e Obstetrícia, São Paulo/SP</wicri:regionArea></affiliation></author><author><name sortKey="Di Favero, Giovanni Mastrantonio" sort="Di Favero, Giovanni Mastrantonio" uniqKey="Di Favero G" first="Giovanni Mastrantonio" last="Di Favero">Giovanni Mastrantonio Di Favero</name><affiliation><nlm:aff id="af2-cln_72p30">Asklepios Hospital Hamburg, Department of Advanced Operative and Oncologic Gynecology, GermanyGermany</nlm:aff><wicri:noCountry code="subfield">GermanyGermany</wicri:noCountry></affiliation></author></analytic><series><title level="j">Clinics</title><idno type="ISSN">1807-5932</idno><idno type="eISSN">1980-5322</idno><imprint><date when="2017">2017</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><sec><title>OBJECTIVES:</title><p>To evaluate the postoperative pathological characteristics of hysterectomy specimens, preoperative cancer antigen (CA)-125 levels and imaging modalities in patients with endometrial cancer and to build a risk matrix model to identify and recruit patients for retroperitoneal lymphadenectomy.</p></sec><sec><title>METHODS:</title><p>A total of 405 patients undergoing surgical treatment for endometrial cancer were retrospectively reviewed and analyzed. Clinical (age and body mass index), laboratory (CA-125), radiological (lymph node evaluation), and pathological (tumour size, grade, lymphovascular space invasion, lymph node metastasis, and myometrial invasion) parameters were used to test the ability to predict lymph node metastasis. Four parameters were selected by logistic regression to create a risk matrix for nodal metastasis.</p></sec><sec><title>RESULTS:</title><p>Of the 405 patients, 236 (58.3%) underwent complete pelvic and para-aortic lymphadenectomy, 96 (23.7%) underwent nodal sampling, and 73 (18%) had no surgical lymph node assessment. The parameters predicting nodal involvement obtained through logistic regression were myometrial infiltration >50%, lymphovascular space involvement, pelvic lymph node involvement by imaging, and a CA-125 value >21.5 U/mL. According to our risk matrix, the absence of these four parameters implied a risk of lymph node metastasis of 2.7%, whereas in the presence of all four parameters the risk was 82.3%.</p></sec><sec><title>CONCLUSION:</title><p>Patients without deep myometrial invasion and lymphovascular space involvement on the final pathological examination and with normal CA-125 values and lymph node radiological examinations have a relatively low risk of lymph node involvement. This risk assessment matrix may be able to refer patients with high-risk parameters necessitating lymphadenectomy and to decide the risks and benefits of lymphadenectomy.</p></sec></div></front><back><div1 type="bibliography"><listBibl><biblStruct><analytic><author><name sortKey="Lurain, Jr" uniqKey="Lurain J">JR Lurain</name></author><author><name sortKey="Rice, Bl" uniqKey="Rice B">BL Rice</name></author><author><name sortKey="Rademaker, Aw" uniqKey="Rademaker A">AW Rademaker</name></author><author><name sortKey="Poggensee, Le" uniqKey="Poggensee L">LE Poggensee</name></author><author><name sortKey="Schink, Jc" uniqKey="Schink J">JC Schink</name></author><author><name sortKey="Miller, Ds" uniqKey="Miller D">DS Miller</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Creasman, Wt" uniqKey="Creasman W">WT Creasman</name></author><author><name sortKey="Morrow, Cp" uniqKey="Morrow C">CP Morrow</name></author><author><name sortKey="Bundy, Bn" 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Fleming</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Cade, Tj" uniqKey="Cade T">TJ Cade</name></author><author><name sortKey="Quinn, Ma" uniqKey="Quinn M">MA Quinn</name></author><author><name sortKey="Mcnally, Om" uniqKey="Mcnally O">OM McNally</name></author><author><name sortKey="Neesham, D" uniqKey="Neesham D">D Neesham</name></author><author><name sortKey="Pyman, J" uniqKey="Pyman J">J Pyman</name></author><author><name sortKey="Dobrotwir, A" uniqKey="Dobrotwir A">A Dobrotwir</name></author></analytic></biblStruct></listBibl></div1></back></TEI><pmc article-type="research-article"><pmc-dir>properties open_access</pmc-dir>
<front><journal-meta><journal-id journal-id-type="nlm-ta">Clinics (Sao Paulo)</journal-id><journal-id journal-id-type="iso-abbrev">Clinics (Sao Paulo)</journal-id><journal-title-group><journal-title>Clinics</journal-title></journal-title-group><issn pub-type="ppub">1807-5932</issn><issn pub-type="epub">1980-5322</issn><publisher><publisher-name>Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="pmid">28226030</article-id><article-id pub-id-type="pmc">5251192</article-id><article-id pub-id-type="doi">10.6061/clinics/2017(01)06</article-id><article-id pub-id-type="publisher-id">cln_72p30</article-id><article-categories><subj-group subj-group-type="heading"><subject>Clinical Science</subject></subj-group></article-categories><title-group><article-title>A novel model to estimate lymph node metastasis in endometrial cancer patients</article-title></title-group><contrib-group><contrib contrib-type="author"><name><surname>Anton</surname><given-names>Cristina</given-names></name><xref ref-type="aff" rid="af1-cln_72p30">I</xref><xref ref-type="corresp" rid="c1-cln_72p30">*</xref></contrib><contrib contrib-type="author"><name><surname>e Silva</surname><given-names>Alexandre Silva</given-names></name><xref ref-type="aff" rid="af1-cln_72p30">I</xref></contrib><contrib contrib-type="author"><name><surname>Baracat</surname><given-names>Edmund Chada</given-names></name><xref ref-type="aff" rid="af1-cln_72p30">I</xref></contrib><contrib contrib-type="author"><name><surname>Dogan</surname><given-names>Nasuh Utku</given-names></name><xref ref-type="aff" rid="af2-cln_72p30">II</xref><xref ref-type="aff" rid="af3-cln_72p30">III</xref></contrib><contrib contrib-type="author"><name><surname>Köhler</surname><given-names>Christhardt</given-names></name><xref ref-type="aff" rid="af2-cln_72p30">II</xref></contrib><contrib contrib-type="author"><name><surname>Carvalho</surname><given-names>Jesus Paula</given-names></name><xref ref-type="aff" rid="af1-cln_72p30">I</xref></contrib><contrib contrib-type="author"><name><surname>di Favero</surname><given-names>Giovanni Mastrantonio</given-names></name><xref ref-type="aff" rid="af2-cln_72p30">II</xref></contrib><aff id="af1-cln_72p30"><label>I</label>Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo, Instituto do Câncer do Estado de São Paulo – ICESP, Departamento de Ginecologia e Obstetrícia, São Paulo/SP, Brazil</aff><aff id="af2-cln_72p30"><label>II</label>Asklepios Hospital Hamburg, Department of Advanced Operative and Oncologic Gynecology, GermanyGermany</aff><aff id="af3-cln_72p30"><label>III</label>Akdeniz University, Department of Obstetrics and Gynecology, Antalya, Turkey</aff></contrib-group><author-notes><corresp id="c1-cln_72p30">*Corresponding author. E-mail: <email>cristinaanton@terra.com.br</email></corresp></author-notes><pub-date pub-type="epub"><month>1</month><year>2017</year></pub-date><pub-date pub-type="ppub"><month>1</month><year>2017</year></pub-date><volume>72</volume><issue>1</issue><fpage>30</fpage><lpage>35</lpage><history><date date-type="received"><day>19</day><month>8</month><year>2016</year></date><date date-type="rev-recd"><day>7</day><month>10</month><year>2016</year></date><date date-type="accepted"><day>21</day><month>10</month><year>2016</year></date></history><permissions><copyright-statement>Copyright © 2017 CLINICS</copyright-statement><copyright-year>2017</copyright-year><license license-type="open-access" xlink:href="http://creativecommons.org/licenses/by/4.0/"><license-p>This is an Open Access article distributed under the terms of the Creative Commons License (<ext-link ext-link-type="uri" xlink:href="http://creativecommons.org/licenses/by/4.0/">http://creativecommons.org/licenses/by/4.0/</ext-link>) which permits unrestricted use, distribution, and reproduction in any medium or format, provided the original work is properly cited.</license-p></license></permissions><abstract><sec><title>OBJECTIVES:</title><p>To evaluate the postoperative pathological characteristics of hysterectomy specimens, preoperative cancer antigen (CA)-125 levels and imaging modalities in patients with endometrial cancer and to build a risk matrix model to identify and recruit patients for retroperitoneal lymphadenectomy.</p></sec><sec><title>METHODS:</title><p>A total of 405 patients undergoing surgical treatment for endometrial cancer were retrospectively reviewed and analyzed. Clinical (age and body mass index), laboratory (CA-125), radiological (lymph node evaluation), and pathological (tumour size, grade, lymphovascular space invasion, lymph node metastasis, and myometrial invasion) parameters were used to test the ability to predict lymph node metastasis. Four parameters were selected by logistic regression to create a risk matrix for nodal metastasis.</p></sec><sec><title>RESULTS:</title><p>Of the 405 patients, 236 (58.3%) underwent complete pelvic and para-aortic lymphadenectomy, 96 (23.7%) underwent nodal sampling, and 73 (18%) had no surgical lymph node assessment. The parameters predicting nodal involvement obtained through logistic regression were myometrial infiltration >50%, lymphovascular space involvement, pelvic lymph node involvement by imaging, and a CA-125 value >21.5 U/mL. According to our risk matrix, the absence of these four parameters implied a risk of lymph node metastasis of 2.7%, whereas in the presence of all four parameters the risk was 82.3%.</p></sec><sec><title>CONCLUSION:</title><p>Patients without deep myometrial invasion and lymphovascular space involvement on the final pathological examination and with normal CA-125 values and lymph node radiological examinations have a relatively low risk of lymph node involvement. This risk assessment matrix may be able to refer patients with high-risk parameters necessitating lymphadenectomy and to decide the risks and benefits of lymphadenectomy.</p></sec></abstract><kwd-group><kwd>Endometrial Cancer</kwd><kwd>Lymph Node Metastasis</kwd><kwd>Lymphadenectomy</kwd><kwd>Risk Matrix</kwd></kwd-group></article-meta></front><floats-group><fig id="f1-cln_72p30" position="float"><label>Figure 1</label><caption><p>ROC curve for CA-125 in lymph node metastasis prediction. Se: sensitivity, Sp: specificity, AUC: area under the curve.</p></caption><graphic xlink:href="cln-72-01-030-g001"></graphic></fig><table-wrap id="t1-cln_72p30" position="float"><label>Table 1</label><caption><p>Characteristics of the study population.</p></caption><table frame="hsides" rules="groups"><thead><tr><th align="left" rowspan="1" colspan="1">Variable</th><th align="center" rowspan="1" colspan="1">N=405 (100%)</th></tr></thead><tbody><tr><td align="left" rowspan="1" colspan="1"><bold>Age</bold></td><td align="left" rowspan="1" colspan="1"></td></tr><tr><td align="left" rowspan="1" colspan="1">Median (mean)</td><td align="center" rowspan="1" colspan="1">63 (63.6)</td></tr><tr><td align="left" rowspan="1" colspan="1"><bold>Range</bold></td><td align="center" rowspan="1" colspan="1">31–91</td></tr><tr><td align="left" rowspan="1" colspan="1"><bold>Race</bold></td><td align="left" rowspan="1" colspan="1"></td></tr><tr><td align="left" rowspan="1" colspan="1">Caucasian</td><td align="center" rowspan="1" colspan="1">313 (77.3%)</td></tr><tr><td align="left" rowspan="1" colspan="1">Black</td><td align="center" rowspan="1" colspan="1">42 (10.4%)</td></tr><tr><td align="left" rowspan="1" colspan="1">Other</td><td align="center" rowspan="1" colspan="1">50 (12.3%)</td></tr><tr><td align="left" rowspan="1" colspan="1"><bold>BMI (kg/m<sup>2</sup>)</bold></td><td align="left" rowspan="1" colspan="1"></td></tr><tr><td align="left" rowspan="1" colspan="1">Median (mean)</td><td align="center" rowspan="1" colspan="1">27.8 (32.2)</td></tr><tr><td align="left" rowspan="1" colspan="1">Range</td><td align="center" rowspan="1" colspan="1">19.2–58</td></tr><tr><td align="left" rowspan="1" colspan="1"><bold>Histologic type</bold></td><td align="left" rowspan="1" colspan="1"></td></tr><tr><td align="left" rowspan="1" colspan="1">Endometrioid</td><td align="center" rowspan="1" colspan="1">326 (80.5%)</td></tr><tr><td align="left" rowspan="1" colspan="1">Serous</td><td align="center" rowspan="1" colspan="1">60 (14.8%)</td></tr><tr><td align="left" rowspan="1" colspan="1">Clear cell</td><td align="center" rowspan="1" colspan="1">19 (4.7%)</td></tr><tr><td align="left" rowspan="1" colspan="1"><bold>Grade</bold></td><td align="left" rowspan="1" colspan="1"></td></tr><tr><td align="left" rowspan="1" colspan="1">Low</td><td align="center" rowspan="1" colspan="1">283 (69.8%)</td></tr><tr><td align="left" rowspan="1" colspan="1">High</td><td align="center" rowspan="1" colspan="1">122 (30.1%)</td></tr><tr><td align="left" rowspan="1" colspan="1"><bold>FIGO stage</bold></td><td align="left" rowspan="1" colspan="1"></td></tr><tr><td align="left" rowspan="1" colspan="1">IA</td><td align="center" rowspan="1" colspan="1">178 (44.0%)</td></tr><tr><td align="left" rowspan="1" colspan="1">IB</td><td align="center" rowspan="1" colspan="1">81 (20%)</td></tr><tr><td align="left" rowspan="1" colspan="1">II</td><td align="center" rowspan="1" colspan="1">29 (7.2%)</td></tr><tr><td align="left" rowspan="1" colspan="1">IIIA</td><td align="center" rowspan="1" colspan="1">22 (5.4%)</td></tr><tr><td align="left" rowspan="1" colspan="1">IIIB</td><td align="center" rowspan="1" colspan="1">8 (2.0%)</td></tr><tr><td align="left" rowspan="1" colspan="1">IIIC1</td><td align="center" rowspan="1" colspan="1">37 (9.1%)</td></tr><tr><td align="left" rowspan="1" colspan="1">IIIC2</td><td align="center" rowspan="1" colspan="1">32 (7.9%)</td></tr><tr><td align="left" rowspan="1" colspan="1">IVA</td><td align="center" rowspan="1" colspan="1">2 (0.5%)</td></tr><tr><td align="left" rowspan="1" colspan="1">IVB</td><td align="center" rowspan="1" colspan="1">16 (4.0%)</td></tr><tr><td align="left" rowspan="1" colspan="1"><bold>Myometrial infiltration</bold></td><td align="left" rowspan="1" colspan="1"></td></tr><tr><td align="left" rowspan="1" colspan="1">< 50%</td><td align="center" rowspan="1" colspan="1">198 (48.9%)</td></tr><tr><td align="left" rowspan="1" colspan="1">> 50%</td><td align="center" rowspan="1" colspan="1">196 (48.4%)</td></tr><tr><td align="left" rowspan="1" colspan="1">Unknown</td><td align="center" rowspan="1" colspan="1">11 (2.7%)</td></tr><tr><td align="left" rowspan="1" colspan="1"><bold>Lymphovascular space invasion</bold></td><td align="left" rowspan="1" colspan="1"></td></tr><tr><td align="left" rowspan="1" colspan="1">Yes</td><td align="center" rowspan="1" colspan="1">128 (31.6%)</td></tr><tr><td align="left" rowspan="1" colspan="1">No</td><td align="center" rowspan="1" colspan="1">267 (65.9%)</td></tr><tr><td align="left" rowspan="1" colspan="1">Unknown</td><td align="center" rowspan="1" colspan="1">10 (2.5%)</td></tr><tr><td align="left" rowspan="1" colspan="1"><bold>Tumour size (cm)</bold></td><td align="left" rowspan="1" colspan="1"></td></tr><tr><td align="left" rowspan="1" colspan="1">Median</td><td align="center" rowspan="1" colspan="1">4</td></tr><tr><td align="left" rowspan="1" colspan="1">Range</td><td align="center" rowspan="1" colspan="1">(0–13)</td></tr></tbody></table><table-wrap-foot><fn id="tfn1-cln_72p30"><label>*</label><p>BMI: Body mass index.</p></fn></table-wrap-foot></table-wrap><table-wrap id="t2-cln_72p30" position="float"><label>Table 2</label><caption><p>Logistic regression.</p></caption><table frame="hsides" rules="groups"><thead><tr><th align="left" rowspan="1" colspan="1"></th><th align="center" rowspan="1" colspan="1">Lymph node metastasis risk <italic>OR</italic></th><th align="center" rowspan="1" colspan="1">CI 95%</th></tr></thead><tbody><tr><td align="left" rowspan="1" colspan="1"><bold>Myometrial infiltration</bold></td><td align="center" rowspan="1" colspan="1">2.12</td><td align="center" rowspan="1" colspan="1">0.86-5.79</td></tr><tr><td align="left" rowspan="1" colspan="1"><bold>Lymphovascular space invasion</bold></td><td align="center" rowspan="1" colspan="1">2.98</td><td align="center" rowspan="1" colspan="1">1.29-7.41</td></tr><tr><td align="left" rowspan="1" colspan="1"><bold>Pelvic lymph node involvement by imaging (MRI/CT)</bold></td><td align="center" rowspan="1" colspan="1">6.49</td><td align="center" rowspan="1" colspan="1">2.86-16.9</td></tr><tr><td align="left" rowspan="1" colspan="1"><bold>CA125 ≥ 21.5 U/mL</bold></td><td align="center" rowspan="1" colspan="1">4.01</td><td align="center" rowspan="1" colspan="1">1.67-11.69</td></tr></tbody></table><table-wrap-foot><fn id="tfn2-cln_72p30"><label>*</label><p>CI: Confidence interval.</p></fn></table-wrap-foot></table-wrap><table-wrap id="t3-cln_72p30" position="float"><label>Table 3</label><caption><p>Risk matrix: probability of lymph node involvement based on the presence or absence of predictive variables.</p></caption><table frame="hsides" rules="groups"><thead><tr><th align="center" rowspan="1" colspan="1">Myometrial infiltration ≥ 50%</th><th align="center" rowspan="1" colspan="1">Lymphovascular space invasion</th><th align="center" rowspan="1" colspan="1">Pelvic lymph node involvement by imaging</th><th align="center" rowspan="1" colspan="1">CA125 ≥ 21.5U/mL</th><th align="center" rowspan="1" colspan="1">Probability of lymph node involvement</th></tr></thead><tbody><tr><td align="center" rowspan="1" colspan="1">0</td><td align="center" rowspan="1" colspan="1">0</td><td align="center" rowspan="1" colspan="1">0</td><td align="center" rowspan="1" colspan="1">0</td><td align="center" rowspan="1" colspan="1">2.7%</td></tr><tr><td align="center" rowspan="1" colspan="1">1</td><td align="center" rowspan="1" colspan="1">0</td><td align="center" rowspan="1" colspan="1">0</td><td align="center" rowspan="1" colspan="1">0</td><td align="center" rowspan="1" colspan="1">5.8%</td></tr><tr><td align="center" rowspan="1" colspan="1">0</td><td align="center" rowspan="1" colspan="1">1</td><td align="center" rowspan="1" colspan="1">0</td><td align="center" rowspan="1" colspan="1">0</td><td align="center" rowspan="1" colspan="1">7.8%</td></tr><tr><td align="center" rowspan="1" colspan="1">0</td><td align="center" rowspan="1" colspan="1">0</td><td align="center" rowspan="1" colspan="1">0</td><td align="center" rowspan="1" colspan="1">1</td><td align="center" rowspan="1" colspan="1">10.1%</td></tr><tr><td align="center" rowspan="1" colspan="1">1</td><td align="center" rowspan="1" colspan="1">1</td><td align="center" rowspan="1" colspan="1">0</td><td align="center" rowspan="1" colspan="1">0</td><td align="center" rowspan="1" colspan="1">15.1%</td></tr><tr><td align="center" rowspan="1" colspan="1">0</td><td align="center" rowspan="1" colspan="1">0</td><td align="center" rowspan="1" colspan="1">1</td><td align="center" rowspan="1" colspan="1">0</td><td align="center" rowspan="1" colspan="1">15.5%</td></tr><tr><td align="center" rowspan="1" colspan="1">1</td><td align="center" rowspan="1" colspan="1">0</td><td align="center" rowspan="1" colspan="1">0</td><td align="center" rowspan="1" colspan="1">1</td><td align="center" rowspan="1" colspan="1">19.3%</td></tr><tr><td align="center" rowspan="1" colspan="1">0</td><td align="center" rowspan="1" colspan="1">1</td><td align="center" rowspan="1" colspan="1">0</td><td align="center" rowspan="1" colspan="1">1</td><td align="center" rowspan="1" colspan="1">25.2%</td></tr><tr><td align="center" rowspan="1" colspan="1">1</td><td align="center" rowspan="1" colspan="1">0</td><td align="center" rowspan="1" colspan="1">1</td><td align="center" rowspan="1" colspan="1">0</td><td align="center" rowspan="1" colspan="1">27.9%</td></tr><tr><td align="center" rowspan="1" colspan="1">0</td><td align="center" rowspan="1" colspan="1">1</td><td align="center" rowspan="1" colspan="1">1</td><td align="center" rowspan="1" colspan="1">0</td><td align="center" rowspan="1" colspan="1">35.3%</td></tr><tr><td align="center" rowspan="1" colspan="1">1</td><td align="center" rowspan="1" colspan="1">1</td><td align="center" rowspan="1" colspan="1">0</td><td align="center" rowspan="1" colspan="1">1</td><td align="center" rowspan="1" colspan="1">41.6%</td></tr><tr><td align="center" rowspan="1" colspan="1">0</td><td align="center" rowspan="1" colspan="1">0</td><td align="center" rowspan="1" colspan="1">1</td><td align="center" rowspan="1" colspan="1">1</td><td align="center" rowspan="1" colspan="1">42.3%</td></tr><tr><td align="center" rowspan="1" colspan="1">1</td><td align="center" rowspan="1" colspan="1">1</td><td align="center" rowspan="1" colspan="1">1</td><td align="center" rowspan="1" colspan="1">0</td><td align="center" rowspan="1" colspan="1">53.6%</td></tr><tr><td align="center" rowspan="1" colspan="1">1</td><td align="center" rowspan="1" colspan="1">0</td><td align="center" rowspan="1" colspan="1">1</td><td align="center" rowspan="1" colspan="1">1</td><td align="center" rowspan="1" colspan="1">60.8%</td></tr><tr><td align="center" rowspan="1" colspan="1">0</td><td align="center" rowspan="1" colspan="1">1</td><td align="center" rowspan="1" colspan="1">1</td><td align="center" rowspan="1" colspan="1">1</td><td align="center" rowspan="1" colspan="1">68.6%</td></tr><tr><td align="center" rowspan="1" colspan="1">1</td><td align="center" rowspan="1" colspan="1">1</td><td align="center" rowspan="1" colspan="1">1</td><td align="center" rowspan="1" colspan="1">1</td><td align="center" rowspan="1" colspan="1">82.3%</td></tr></tbody></table></table-wrap></floats-group></pmc></record>Pour manipuler ce document sous Unix (Dilib)
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