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Predictive Value of Clinicopathological Characteristics for Sentinel Lymph Node Metastasis in Early Breast Cancer

Identifieur interne : 000134 ( Pmc/Checkpoint ); précédent : 000133; suivant : 000135

Predictive Value of Clinicopathological Characteristics for Sentinel Lymph Node Metastasis in Early Breast Cancer

Auteurs : Jinhua Ding [République populaire de Chine] ; Li Jiang [République populaire de Chine] ; Weizhu Wu [République populaire de Chine]

Source :

RBID : PMC:5584843

Abstract

Background

Sentinel lymph node biopsy (SLNB) is one of the preferred treatments for breast cancer including clinically negative lymph node breast cancer. However, for 60–70% of patients this invasive axilla surgery is unnecessary. Our study aimed to identify the predictors for sentinel lymph node (SLN) metastasis in early breast cancer patients and provide evidence for rational decision-making in specified clinical situations.

Material/Methods

Medical records of 417 breast cancer patients who were treated with a breast surgical procedure and SLNB in Ningbo Medical Center Lihuili Eastern Hospital were retrospectively reviewed. Univariate analysis and multivariate logistic regression analysis were used to analyze the correlation between SLN metastasis and clinicopathological characteristics, including patient age, menstrual status, body mass index (BMI), family history, tumor size, laterality of tumor, histological grade, estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor-2 (HER2), Ki67 index, and molecular subtypes of the tumor.

Results

In the cohort of 417 cases, the ratio of SLNM was 23.0%. Univariate analysis found that age, tumor size, histological grade, and Ki67 index were associated with SLN metastasis. However, age, tumor size, and histological grade were the only three independent predictors for SLN metastasis by multivariate logistic regression analysis. When these three factors were considered together, three different levels of SLN metastasis groups could be classified: low-risk group with the ratio of 14.3%, moderate-risk group with the ratio of 31.4%, and high-risk group with the ratio of 66.7%.

Conclusions

Our study demonstrated that age, tumor size, and histological grade were three independent predictive factors for SLN metastasis in early breast cancer patients. This finding may help surgeons in the decision-making process for early breast cancer patients before considering axilla surgical procedure.


Url:
DOI: 10.12659/MSM.902795
PubMed: 28839123
PubMed Central: 5584843


Affiliations:


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PMC:5584843

Le document en format XML

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<p>Sentinel lymph node biopsy (SLNB) is one of the preferred treatments for breast cancer including clinically negative lymph node breast cancer. However, for 60–70% of patients this invasive axilla surgery is unnecessary. Our study aimed to identify the predictors for sentinel lymph node (SLN) metastasis in early breast cancer patients and provide evidence for rational decision-making in specified clinical situations.</p>
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<title>Material/Methods</title>
<p>Medical records of 417 breast cancer patients who were treated with a breast surgical procedure and SLNB in Ningbo Medical Center Lihuili Eastern Hospital were retrospectively reviewed. Univariate analysis and multivariate logistic regression analysis were used to analyze the correlation between SLN metastasis and clinicopathological characteristics, including patient age, menstrual status, body mass index (BMI), family history, tumor size, laterality of tumor, histological grade, estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor-2 (HER2), Ki67 index, and molecular subtypes of the tumor.</p>
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<title>Results</title>
<p>In the cohort of 417 cases, the ratio of SLNM was 23.0%. Univariate analysis found that age, tumor size, histological grade, and Ki67 index were associated with SLN metastasis. However, age, tumor size, and histological grade were the only three independent predictors for SLN metastasis by multivariate logistic regression analysis. When these three factors were considered together, three different levels of SLN metastasis groups could be classified: low-risk group with the ratio of 14.3%, moderate-risk group with the ratio of 31.4%, and high-risk group with the ratio of 66.7%.</p>
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<p>Our study demonstrated that age, tumor size, and histological grade were three independent predictive factors for SLN metastasis in early breast cancer patients. This finding may help surgeons in the decision-making process for early breast cancer patients before considering axilla surgical procedure.</p>
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<pmc-dir>properties open_access</pmc-dir>
<front>
<journal-meta>
<journal-id journal-id-type="nlm-ta">Med Sci Monit</journal-id>
<journal-id journal-id-type="iso-abbrev">Med. Sci. Monit</journal-id>
<journal-id journal-id-type="publisher-id">Medical Science Monitor</journal-id>
<journal-title-group>
<journal-title>Medical Science Monitor : International Medical Journal of Experimental and Clinical Research</journal-title>
</journal-title-group>
<issn pub-type="ppub">1234-1010</issn>
<issn pub-type="epub">1643-3750</issn>
<publisher>
<publisher-name>International Scientific Literature, Inc.</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="pmid">28839123</article-id>
<article-id pub-id-type="pmc">5584843</article-id>
<article-id pub-id-type="doi">10.12659/MSM.902795</article-id>
<article-id pub-id-type="publisher-id">902795</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Clinical Research</subject>
</subj-group>
</article-categories>
<title-group>
<article-title>Predictive Value of Clinicopathological Characteristics for Sentinel Lymph Node Metastasis in Early Breast Cancer</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname>Ding</surname>
<given-names>Jinhua</given-names>
</name>
<xref ref-type="aff" rid="af1-medscimonit-23-4102">1</xref>
<xref ref-type="author-notes" rid="fn2-medscimonit-23-4102">B</xref>
<xref ref-type="author-notes" rid="fn3-medscimonit-23-4102">C</xref>
<xref ref-type="author-notes" rid="fn4-medscimonit-23-4102">D</xref>
<xref ref-type="author-notes" rid="fn5-medscimonit-23-4102">E</xref>
<xref ref-type="author-notes" rid="fn6-medscimonit-23-4102">F</xref>
<xref ref-type="author-notes" rid="fn8-medscimonit-23-4102">*</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Jiang</surname>
<given-names>Li</given-names>
</name>
<xref ref-type="aff" rid="af2-medscimonit-23-4102">2</xref>
<xref ref-type="author-notes" rid="fn2-medscimonit-23-4102">B</xref>
<xref ref-type="author-notes" rid="fn3-medscimonit-23-4102">C</xref>
<xref ref-type="author-notes" rid="fn8-medscimonit-23-4102">*</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Wu</surname>
<given-names>Weizhu</given-names>
</name>
<xref ref-type="aff" rid="af1-medscimonit-23-4102">1</xref>
<xref ref-type="author-notes" rid="fn1-medscimonit-23-4102">A</xref>
<xref ref-type="author-notes" rid="fn7-medscimonit-23-4102">G</xref>
<xref ref-type="author-notes" rid="fn8-medscimonit-23-4102">*</xref>
<xref ref-type="corresp" rid="c1-medscimonit-23-4102"></xref>
</contrib>
</contrib-group>
<aff id="af1-medscimonit-23-4102">
<label>1</label>
Department of Breast and Thyroid Surgery, Ningbo Medical Center Lihuili Eastern Hospital, Ningbo, Zhejiang, P.R. China</aff>
<aff id="af2-medscimonit-23-4102">
<label>2</label>
Department of Emergency, Ningbo Medical Center Lihuili Eastern Hospital, Ningbo, Zhejiang, P.R. China</aff>
<author-notes>
<corresp id="c1-medscimonit-23-4102">Corresponding Author: Weizhu Wu, e-mail:
<email>1144184462@qq.com</email>
</corresp>
<fn id="fn1-medscimonit-23-4102">
<label>A</label>
<p>Study Design</p>
</fn>
<fn id="fn2-medscimonit-23-4102">
<label>B</label>
<p>Data Collection</p>
</fn>
<fn id="fn3-medscimonit-23-4102">
<label>C</label>
<p>Statistical Analysis</p>
</fn>
<fn id="fn4-medscimonit-23-4102">
<label>D</label>
<p>Data Interpretation</p>
</fn>
<fn id="fn5-medscimonit-23-4102">
<label>E</label>
<p>Manuscript Preparation</p>
</fn>
<fn id="fn6-medscimonit-23-4102">
<label>F</label>
<p>Literature Search</p>
</fn>
<fn id="fn7-medscimonit-23-4102">
<label>G</label>
<p>Funds Collection</p>
</fn>
<fn id="fn8-medscimonit-23-4102">
<label>*</label>
<p>These authors contributed equally to this work.</p>
</fn>
</author-notes>
<pub-date pub-type="collection">
<year>2017</year>
</pub-date>
<pub-date pub-type="epub">
<day>25</day>
<month>8</month>
<year>2017</year>
</pub-date>
<volume>23</volume>
<fpage>4102</fpage>
<lpage>4108</lpage>
<history>
<date date-type="received">
<day>12</day>
<month>12</month>
<year>2016</year>
</date>
<date date-type="accepted">
<day>01</day>
<month>2</month>
<year>2017</year>
</date>
</history>
<permissions>
<copyright-statement>© Med Sci Monit, 2017</copyright-statement>
<copyright-year>2017</copyright-year>
<license license-type="open-access">
<license-p>This work is licensed under Creative Common Attribution-NonCommercial-NoDerivatives 4.0 International (
<ext-link ext-link-type="uri" xlink:href="https://creativecommons.org/licenses/by-nc-nd/4.0/">CC BY-NC-ND 4.0</ext-link>
)</license-p>
</license>
</permissions>
<abstract>
<sec>
<title>Background</title>
<p>Sentinel lymph node biopsy (SLNB) is one of the preferred treatments for breast cancer including clinically negative lymph node breast cancer. However, for 60–70% of patients this invasive axilla surgery is unnecessary. Our study aimed to identify the predictors for sentinel lymph node (SLN) metastasis in early breast cancer patients and provide evidence for rational decision-making in specified clinical situations.</p>
</sec>
<sec>
<title>Material/Methods</title>
<p>Medical records of 417 breast cancer patients who were treated with a breast surgical procedure and SLNB in Ningbo Medical Center Lihuili Eastern Hospital were retrospectively reviewed. Univariate analysis and multivariate logistic regression analysis were used to analyze the correlation between SLN metastasis and clinicopathological characteristics, including patient age, menstrual status, body mass index (BMI), family history, tumor size, laterality of tumor, histological grade, estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor-2 (HER2), Ki67 index, and molecular subtypes of the tumor.</p>
</sec>
<sec>
<title>Results</title>
<p>In the cohort of 417 cases, the ratio of SLNM was 23.0%. Univariate analysis found that age, tumor size, histological grade, and Ki67 index were associated with SLN metastasis. However, age, tumor size, and histological grade were the only three independent predictors for SLN metastasis by multivariate logistic regression analysis. When these three factors were considered together, three different levels of SLN metastasis groups could be classified: low-risk group with the ratio of 14.3%, moderate-risk group with the ratio of 31.4%, and high-risk group with the ratio of 66.7%.</p>
</sec>
<sec>
<title>Conclusions</title>
<p>Our study demonstrated that age, tumor size, and histological grade were three independent predictive factors for SLN metastasis in early breast cancer patients. This finding may help surgeons in the decision-making process for early breast cancer patients before considering axilla surgical procedure.</p>
</sec>
</abstract>
<kwd-group>
<title>MeSH Keywords</title>
<kwd>Breast Neoplasms</kwd>
<kwd>Multivariate Analysis</kwd>
<kwd>Sentinel Lymph Node Biopsy</kwd>
</kwd-group>
</article-meta>
</front>
<floats-group>
<fig id="f1-medscimonit-23-4102" position="float">
<label>Figure 1</label>
<caption>
<p>The distribution details of identified SLN number.</p>
</caption>
<graphic xlink:href="medscimonit-23-4102-g001"></graphic>
</fig>
<fig id="f2-medscimonit-23-4102" position="float">
<label>Figure 2</label>
<caption>
<p>The percentage of different SLN positive numbers.</p>
</caption>
<graphic xlink:href="medscimonit-23-4102-g002"></graphic>
</fig>
<table-wrap id="t1-medscimonit-23-4102" position="float">
<label>Table 1</label>
<caption>
<p>Clinicopathologic characteristics of early breast cancer patients.</p>
</caption>
<table frame="hsides" rules="rows">
<thead>
<tr>
<th valign="middle" align="left" rowspan="1" colspan="1"></th>
<th valign="middle" align="center" rowspan="1" colspan="1">Numbers (n)</th>
<th valign="middle" align="center" rowspan="1" colspan="1">Percentage (%)</th>
</tr>
</thead>
<tbody>
<tr>
<td colspan="3" valign="top" align="left" rowspan="1">Age (years)</td>
</tr>
<tr>
<td valign="top" align="left" rowspan="1" colspan="1"> <40</td>
<td valign="top" align="center" rowspan="1" colspan="1">68</td>
<td valign="top" align="center" rowspan="1" colspan="1">16.3</td>
</tr>
<tr>
<td valign="top" align="left" rowspan="1" colspan="1"> 40–60</td>
<td valign="top" align="center" rowspan="1" colspan="1">282</td>
<td valign="top" align="center" rowspan="1" colspan="1">67.6</td>
</tr>
<tr>
<td valign="top" align="left" rowspan="1" colspan="1"> >60</td>
<td valign="top" align="center" rowspan="1" colspan="1">67</td>
<td valign="top" align="center" rowspan="1" colspan="1">16.1</td>
</tr>
<tr>
<td colspan="3" valign="top" align="left" rowspan="1">Menstrual status</td>
</tr>
<tr>
<td valign="top" align="left" rowspan="1" colspan="1"> Premenopausal</td>
<td valign="top" align="center" rowspan="1" colspan="1">253</td>
<td valign="top" align="center" rowspan="1" colspan="1">60.7</td>
</tr>
<tr>
<td valign="top" align="left" rowspan="1" colspan="1"> Postmenopausal</td>
<td valign="top" align="center" rowspan="1" colspan="1">164</td>
<td valign="top" align="center" rowspan="1" colspan="1">39.3</td>
</tr>
<tr>
<td colspan="3" valign="top" align="left" rowspan="1">BMI</td>
</tr>
<tr>
<td valign="top" align="left" rowspan="1" colspan="1"> ≤25</td>
<td valign="top" align="center" rowspan="1" colspan="1">273</td>
<td valign="top" align="center" rowspan="1" colspan="1">65.5</td>
</tr>
<tr>
<td valign="top" align="left" rowspan="1" colspan="1"> >25</td>
<td valign="top" align="center" rowspan="1" colspan="1">144</td>
<td valign="top" align="center" rowspan="1" colspan="1">34.5</td>
</tr>
<tr>
<td colspan="3" valign="top" align="left" rowspan="1">Family history</td>
</tr>
<tr>
<td valign="top" align="left" rowspan="1" colspan="1"> Yes</td>
<td valign="top" align="center" rowspan="1" colspan="1">27</td>
<td valign="top" align="center" rowspan="1" colspan="1">6.5</td>
</tr>
<tr>
<td valign="top" align="left" rowspan="1" colspan="1"> No</td>
<td valign="top" align="center" rowspan="1" colspan="1">390</td>
<td valign="top" align="center" rowspan="1" colspan="1">93.5</td>
</tr>
<tr>
<td colspan="3" valign="top" align="left" rowspan="1">Laterality of tumor</td>
</tr>
<tr>
<td valign="top" align="left" rowspan="1" colspan="1"> Left</td>
<td valign="top" align="center" rowspan="1" colspan="1">210</td>
<td valign="top" align="center" rowspan="1" colspan="1">50.4</td>
</tr>
<tr>
<td valign="top" align="left" rowspan="1" colspan="1"> Right</td>
<td valign="top" align="center" rowspan="1" colspan="1">207</td>
<td valign="top" align="center" rowspan="1" colspan="1">49.6</td>
</tr>
<tr>
<td colspan="3" valign="top" align="left" rowspan="1">Tumor size (cm)</td>
</tr>
<tr>
<td valign="top" align="left" rowspan="1" colspan="1"> <1 cm</td>
<td valign="top" align="center" rowspan="1" colspan="1">78</td>
<td valign="top" align="center" rowspan="1" colspan="1">18.7</td>
</tr>
<tr>
<td valign="top" align="left" rowspan="1" colspan="1"> 1–2 cm</td>
<td valign="top" align="center" rowspan="1" colspan="1">230</td>
<td valign="top" align="center" rowspan="1" colspan="1">55.2</td>
</tr>
<tr>
<td valign="top" align="left" rowspan="1" colspan="1"> >2 cm</td>
<td valign="top" align="center" rowspan="1" colspan="1">109</td>
<td valign="top" align="center" rowspan="1" colspan="1">26.1</td>
</tr>
<tr>
<td colspan="3" valign="top" align="left" rowspan="1">Histological grade</td>
</tr>
<tr>
<td valign="top" align="left" rowspan="1" colspan="1"> I</td>
<td valign="top" align="center" rowspan="1" colspan="1">62</td>
<td valign="top" align="center" rowspan="1" colspan="1">14.9</td>
</tr>
<tr>
<td valign="top" align="left" rowspan="1" colspan="1"> II</td>
<td valign="top" align="center" rowspan="1" colspan="1">270</td>
<td valign="top" align="center" rowspan="1" colspan="1">64.7</td>
</tr>
<tr>
<td valign="top" align="left" rowspan="1" colspan="1"> III</td>
<td valign="top" align="center" rowspan="1" colspan="1">85</td>
<td valign="top" align="center" rowspan="1" colspan="1">20.4</td>
</tr>
<tr>
<td colspan="3" valign="top" align="left" rowspan="1">Histological type</td>
</tr>
<tr>
<td valign="top" align="left" rowspan="1" colspan="1"> IDC</td>
<td valign="top" align="center" rowspan="1" colspan="1">388</td>
<td valign="top" align="center" rowspan="1" colspan="1">93.0</td>
</tr>
<tr>
<td valign="top" align="left" rowspan="1" colspan="1"> ILC</td>
<td valign="top" align="center" rowspan="1" colspan="1">4</td>
<td valign="top" align="center" rowspan="1" colspan="1">1.0</td>
</tr>
<tr>
<td valign="top" align="left" rowspan="1" colspan="1"> Mucinous</td>
<td valign="top" align="center" rowspan="1" colspan="1">20</td>
<td valign="top" align="center" rowspan="1" colspan="1">4.8</td>
</tr>
<tr>
<td valign="top" align="left" rowspan="1" colspan="1"> Medullary</td>
<td valign="top" align="center" rowspan="1" colspan="1">5</td>
<td valign="top" align="center" rowspan="1" colspan="1">1.2</td>
</tr>
<tr>
<td colspan="3" valign="top" align="left" rowspan="1">ER</td>
</tr>
<tr>
<td valign="top" align="left" rowspan="1" colspan="1"> Negative</td>
<td valign="top" align="center" rowspan="1" colspan="1">109</td>
<td valign="top" align="center" rowspan="1" colspan="1">26.1</td>
</tr>
<tr>
<td valign="top" align="left" rowspan="1" colspan="1"> Positive</td>
<td valign="top" align="center" rowspan="1" colspan="1">308</td>
<td valign="top" align="center" rowspan="1" colspan="1">73.9</td>
</tr>
<tr>
<td colspan="3" valign="top" align="left" rowspan="1">PR</td>
</tr>
<tr>
<td valign="top" align="left" rowspan="1" colspan="1"> Negative</td>
<td valign="top" align="center" rowspan="1" colspan="1">127</td>
<td valign="top" align="center" rowspan="1" colspan="1">30.5</td>
</tr>
<tr>
<td valign="top" align="left" rowspan="1" colspan="1"> Positive</td>
<td valign="top" align="center" rowspan="1" colspan="1">290</td>
<td valign="top" align="center" rowspan="1" colspan="1">69.5</td>
</tr>
<tr>
<td colspan="3" valign="top" align="left" rowspan="1">HER2</td>
</tr>
<tr>
<td valign="top" align="left" rowspan="1" colspan="1"> Negative</td>
<td valign="top" align="center" rowspan="1" colspan="1">341</td>
<td valign="top" align="center" rowspan="1" colspan="1">81.8</td>
</tr>
<tr>
<td valign="top" align="left" rowspan="1" colspan="1"> Positive</td>
<td valign="top" align="center" rowspan="1" colspan="1">76</td>
<td valign="top" align="center" rowspan="1" colspan="1">18.2</td>
</tr>
<tr>
<td colspan="3" valign="top" align="left" rowspan="1">Ki67</td>
</tr>
<tr>
<td valign="top" align="left" rowspan="1" colspan="1"> Low expression index</td>
<td valign="top" align="center" rowspan="1" colspan="1">281</td>
<td valign="top" align="center" rowspan="1" colspan="1">67.4</td>
</tr>
<tr>
<td valign="top" align="left" rowspan="1" colspan="1"> High expression index</td>
<td valign="top" align="center" rowspan="1" colspan="1">136</td>
<td valign="top" align="center" rowspan="1" colspan="1">32.6</td>
</tr>
<tr>
<td colspan="3" valign="top" align="left" rowspan="1">Molucular subtype</td>
</tr>
<tr>
<td valign="top" align="left" rowspan="1" colspan="1"> Luminal A-like</td>
<td valign="top" align="center" rowspan="1" colspan="1">118</td>
<td valign="top" align="center" rowspan="1" colspan="1">28.3</td>
</tr>
<tr>
<td valign="top" align="left" rowspan="1" colspan="1"> Luminal B-like</td>
<td valign="top" align="center" rowspan="1" colspan="1">200</td>
<td valign="top" align="center" rowspan="1" colspan="1">48.0</td>
</tr>
<tr>
<td valign="top" align="left" rowspan="1" colspan="1"> HER2 overexpression</td>
<td valign="top" align="center" rowspan="1" colspan="1">61</td>
<td valign="top" align="center" rowspan="1" colspan="1">14.6</td>
</tr>
<tr>
<td valign="top" align="left" rowspan="1" colspan="1"> Triple negative</td>
<td valign="top" align="center" rowspan="1" colspan="1">38</td>
<td valign="top" align="center" rowspan="1" colspan="1">9.1</td>
</tr>
<tr>
<td colspan="3" valign="top" align="left" rowspan="1">Surgery</td>
</tr>
<tr>
<td valign="top" align="left" rowspan="1" colspan="1"> BCS + SLNB</td>
<td valign="top" align="center" rowspan="1" colspan="1">254</td>
<td valign="top" align="center" rowspan="1" colspan="1">60.9</td>
</tr>
<tr>
<td valign="top" align="left" rowspan="1" colspan="1"> BCS + ALND</td>
<td valign="top" align="center" rowspan="1" colspan="1">70</td>
<td valign="top" align="center" rowspan="1" colspan="1">16.8</td>
</tr>
<tr>
<td valign="top" align="left" rowspan="1" colspan="1"> Mastectomy + SLNB</td>
<td valign="top" align="center" rowspan="1" colspan="1">48</td>
<td valign="top" align="center" rowspan="1" colspan="1">11.5</td>
</tr>
<tr>
<td valign="top" align="left" rowspan="1" colspan="1"> MRM</td>
<td valign="top" align="center" rowspan="1" colspan="1">45</td>
<td valign="top" align="center" rowspan="1" colspan="1">10.8</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn id="tfn1-medscimonit-23-4102">
<p>IDC – invasive ductal carcinoma; ILC – invasive lobular carcinoma; ER – estrogen receptor; PR – progesterone receptor; HER2 – human epidermal growth factor receptor 2; BCS – breast conserving surgery; SLNB – sentinel lymph node biopsy; ALND – axillary lymph node dissection; MRM – modified radical mastectomy.</p>
</fn>
</table-wrap-foot>
</table-wrap>
<table-wrap id="t2-medscimonit-23-4102" position="float">
<label>Table 2</label>
<caption>
<p>Relationship of clinicopathologic factors for SLN metastasis.</p>
</caption>
<table frame="hsides" rules="rows">
<thead>
<tr>
<th valign="middle" align="center" rowspan="1" colspan="1">Variable</th>
<th valign="middle" align="center" rowspan="1" colspan="1">SLNM (n)</th>
<th valign="middle" align="center" rowspan="1" colspan="1">SLN-NM (n)</th>
<th valign="middle" align="center" rowspan="1" colspan="1">p Value</th>
<th valign="middle" align="center" rowspan="1" colspan="1">Hazard ratio</th>
<th valign="middle" align="center" rowspan="1" colspan="1">95%CI</th>
</tr>
</thead>
<tbody>
<tr>
<td colspan="6" valign="top" align="left" rowspan="1">Age</td>
</tr>
<tr>
<td valign="top" align="left" rowspan="1" colspan="1"> <40 years</td>
<td valign="top" align="right" rowspan="1" colspan="1">24</td>
<td valign="top" align="right" rowspan="1" colspan="1">44</td>
<td valign="top" align="center" rowspan="1" colspan="1"></td>
<td valign="top" align="center" rowspan="1" colspan="1"></td>
<td valign="top" align="center" rowspan="1" colspan="1"></td>
</tr>
<tr>
<td valign="top" align="left" rowspan="1" colspan="1"> ≥40 years</td>
<td valign="top" align="right" rowspan="1" colspan="1">72</td>
<td valign="top" align="right" rowspan="1" colspan="1">277</td>
<td valign="top" align="center" rowspan="1" colspan="1">0.009</td>
<td valign="top" align="center" rowspan="1" colspan="1">2.098</td>
<td valign="top" align="center" rowspan="1" colspan="1">1.198–3.677</td>
</tr>
<tr>
<td colspan="6" valign="top" align="left" rowspan="1">Menstrual status</td>
</tr>
<tr>
<td valign="top" align="left" rowspan="1" colspan="1"> Premenopausal</td>
<td valign="top" align="right" rowspan="1" colspan="1">32</td>
<td valign="top" align="right" rowspan="1" colspan="1">132</td>
<td valign="top" align="center" rowspan="1" colspan="1"></td>
<td valign="top" align="center" rowspan="1" colspan="1"></td>
<td valign="top" align="center" rowspan="1" colspan="1"></td>
</tr>
<tr>
<td valign="top" align="left" rowspan="1" colspan="1"> Postmenopausal</td>
<td valign="top" align="right" rowspan="1" colspan="1">64</td>
<td valign="top" align="right" rowspan="1" colspan="1">189</td>
<td valign="top" align="center" rowspan="1" colspan="1">0.171</td>
<td valign="top" align="center" rowspan="1" colspan="1">0.716</td>
<td valign="top" align="center" rowspan="1" colspan="1">0.443–1.156</td>
</tr>
<tr>
<td colspan="6" valign="top" align="left" rowspan="1">BMI</td>
</tr>
<tr>
<td valign="top" align="left" rowspan="1" colspan="1"> ≤25</td>
<td valign="top" align="right" rowspan="1" colspan="1">58</td>
<td valign="top" align="right" rowspan="1" colspan="1">215</td>
<td valign="top" align="center" rowspan="1" colspan="1"></td>
<td valign="top" align="center" rowspan="1" colspan="1"></td>
<td valign="top" align="center" rowspan="1" colspan="1"></td>
</tr>
<tr>
<td valign="top" align="left" rowspan="1" colspan="1"> >25</td>
<td valign="top" align="right" rowspan="1" colspan="1">38</td>
<td valign="top" align="right" rowspan="1" colspan="1">106</td>
<td valign="top" align="center" rowspan="1" colspan="1">0.235</td>
<td valign="top" align="center" rowspan="1" colspan="1">0.753</td>
<td valign="top" align="center" rowspan="1" colspan="1">0.470–1.205</td>
</tr>
<tr>
<td colspan="6" valign="top" align="left" rowspan="1">Family history</td>
</tr>
<tr>
<td valign="top" align="left" rowspan="1" colspan="1"> Yes</td>
<td valign="top" align="right" rowspan="1" colspan="1">9</td>
<td valign="top" align="right" rowspan="1" colspan="1">18</td>
<td valign="top" align="center" rowspan="1" colspan="1"></td>
<td valign="top" align="center" rowspan="1" colspan="1"></td>
<td valign="top" align="center" rowspan="1" colspan="1"></td>
</tr>
<tr>
<td valign="top" align="left" rowspan="1" colspan="1"> No</td>
<td valign="top" align="right" rowspan="1" colspan="1">87</td>
<td valign="top" align="right" rowspan="1" colspan="1">203</td>
<td valign="top" align="center" rowspan="1" colspan="1">0.188</td>
<td valign="top" align="center" rowspan="1" colspan="1">1.741</td>
<td valign="top" align="center" rowspan="1" colspan="1">0.756–4.013</td>
</tr>
<tr>
<td colspan="6" valign="top" align="left" rowspan="1">Laterality of the tumor</td>
</tr>
<tr>
<td valign="top" align="left" rowspan="1" colspan="1"> Left</td>
<td valign="top" align="right" rowspan="1" colspan="1">52</td>
<td valign="top" align="right" rowspan="1" colspan="1">158</td>
<td valign="top" align="center" rowspan="1" colspan="1"></td>
<td valign="top" align="center" rowspan="1" colspan="1"></td>
<td valign="top" align="center" rowspan="1" colspan="1"></td>
</tr>
<tr>
<td valign="top" align="left" rowspan="1" colspan="1"> Right</td>
<td valign="top" align="right" rowspan="1" colspan="1">44</td>
<td valign="top" align="right" rowspan="1" colspan="1">163</td>
<td valign="top" align="center" rowspan="1" colspan="1">0.392</td>
<td valign="top" align="center" rowspan="1" colspan="1">1.219</td>
<td valign="top" align="center" rowspan="1" colspan="1">0.772–1.926</td>
</tr>
<tr>
<td colspan="6" valign="top" align="left" rowspan="1">Tumor size</td>
</tr>
<tr>
<td valign="top" align="left" rowspan="1" colspan="1"> ≤2 cm</td>
<td valign="top" align="right" rowspan="1" colspan="1">58</td>
<td valign="top" align="right" rowspan="1" colspan="1">250</td>
<td valign="top" align="center" rowspan="1" colspan="1"></td>
<td valign="top" align="center" rowspan="1" colspan="1"></td>
<td valign="top" align="center" rowspan="1" colspan="1"></td>
</tr>
<tr>
<td valign="top" align="left" rowspan="1" colspan="1"> >2 cm</td>
<td valign="top" align="right" rowspan="1" colspan="1">38</td>
<td valign="top" align="right" rowspan="1" colspan="1">71</td>
<td valign="top" align="center" rowspan="1" colspan="1">0.001</td>
<td valign="top" align="center" rowspan="1" colspan="1">0.433</td>
<td valign="top" align="center" rowspan="1" colspan="1">0.266–0.705</td>
</tr>
<tr>
<td colspan="6" valign="top" align="left" rowspan="1">Histological grade</td>
</tr>
<tr>
<td valign="top" align="left" rowspan="1" colspan="1"> I–II</td>
<td valign="top" align="right" rowspan="1" colspan="1">62</td>
<td valign="top" align="right" rowspan="1" colspan="1">270</td>
<td valign="top" align="center" rowspan="1" colspan="1"></td>
<td valign="top" align="center" rowspan="1" colspan="1"></td>
<td valign="top" align="center" rowspan="1" colspan="1"></td>
</tr>
<tr>
<td valign="top" align="left" rowspan="1" colspan="1"> III</td>
<td valign="top" align="right" rowspan="1" colspan="1">34</td>
<td valign="top" align="right" rowspan="1" colspan="1">51</td>
<td valign="top" align="center" rowspan="1" colspan="1">0.000</td>
<td valign="top" align="center" rowspan="1" colspan="1">0.344</td>
<td valign="top" align="center" rowspan="1" colspan="1">0.206–0.576</td>
</tr>
<tr>
<td colspan="6" valign="top" align="left" rowspan="1">ER</td>
</tr>
<tr>
<td valign="top" align="left" rowspan="1" colspan="1"> Positive</td>
<td valign="top" align="right" rowspan="1" colspan="1">76</td>
<td valign="top" align="right" rowspan="1" colspan="1">232</td>
<td valign="top" align="center" rowspan="1" colspan="1"></td>
<td valign="top" align="center" rowspan="1" colspan="1"></td>
<td valign="top" align="center" rowspan="1" colspan="1"></td>
</tr>
<tr>
<td valign="top" align="left" rowspan="1" colspan="1"> Negative</td>
<td valign="top" align="right" rowspan="1" colspan="1">20</td>
<td valign="top" align="right" rowspan="1" colspan="1">89</td>
<td valign="top" align="center" rowspan="1" colspan="1">0.178</td>
<td valign="top" align="center" rowspan="1" colspan="1">1.458</td>
<td valign="top" align="center" rowspan="1" colspan="1">0.841–2.526</td>
</tr>
<tr>
<td colspan="6" valign="top" align="left" rowspan="1">PR</td>
</tr>
<tr>
<td valign="top" align="left" rowspan="1" colspan="1"> Positive</td>
<td valign="top" align="right" rowspan="1" colspan="1">68</td>
<td valign="top" align="right" rowspan="1" colspan="1">222</td>
<td valign="top" align="center" rowspan="1" colspan="1"></td>
<td valign="top" align="center" rowspan="1" colspan="1"></td>
<td valign="top" align="center" rowspan="1" colspan="1"></td>
</tr>
<tr>
<td valign="top" align="left" rowspan="1" colspan="1"> Negative</td>
<td valign="top" align="right" rowspan="1" colspan="1">28</td>
<td valign="top" align="right" rowspan="1" colspan="1">99</td>
<td valign="top" align="center" rowspan="1" colspan="1">0.754</td>
<td valign="top" align="center" rowspan="1" colspan="1">1.083</td>
<td valign="top" align="center" rowspan="1" colspan="1">0.657–1.785</td>
</tr>
<tr>
<td colspan="6" valign="top" align="left" rowspan="1">HER2</td>
</tr>
<tr>
<td valign="top" align="left" rowspan="1" colspan="1"> Positive</td>
<td valign="top" align="right" rowspan="1" colspan="1">16</td>
<td valign="top" align="right" rowspan="1" colspan="1">60</td>
<td valign="top" align="center" rowspan="1" colspan="1"></td>
<td valign="top" align="center" rowspan="1" colspan="1"></td>
<td valign="top" align="center" rowspan="1" colspan="1"></td>
</tr>
<tr>
<td valign="top" align="left" rowspan="1" colspan="1"> Negative</td>
<td valign="top" align="right" rowspan="1" colspan="1">80</td>
<td valign="top" align="right" rowspan="1" colspan="1">261</td>
<td valign="top" align="center" rowspan="1" colspan="1">0.652</td>
<td valign="top" align="center" rowspan="1" colspan="1">0.870</td>
<td valign="top" align="center" rowspan="1" colspan="1">0.475–1.594</td>
</tr>
<tr>
<td colspan="6" valign="top" align="left" rowspan="1">Ki67</td>
</tr>
<tr>
<td valign="top" align="left" rowspan="1" colspan="1"> Low index</td>
<td valign="top" align="right" rowspan="1" colspan="1">54</td>
<td valign="top" align="right" rowspan="1" colspan="1">224</td>
<td valign="top" align="center" rowspan="1" colspan="1"></td>
<td valign="top" align="center" rowspan="1" colspan="1"></td>
<td valign="top" align="center" rowspan="1" colspan="1"></td>
</tr>
<tr>
<td valign="top" align="left" rowspan="1" colspan="1"> High index</td>
<td valign="top" align="right" rowspan="1" colspan="1">42</td>
<td valign="top" align="right" rowspan="1" colspan="1">97</td>
<td valign="top" align="center" rowspan="1" colspan="1">0.014</td>
<td valign="top" align="center" rowspan="1" colspan="1">0.557</td>
<td valign="top" align="center" rowspan="1" colspan="1">0.349–0.889</td>
</tr>
<tr>
<td colspan="6" valign="top" align="left" rowspan="1">Molucular subtype</td>
</tr>
<tr>
<td valign="top" align="left" rowspan="1" colspan="1"> Triple negative</td>
<td valign="top" align="right" rowspan="1" colspan="1">6</td>
<td valign="top" align="right" rowspan="1" colspan="1">32</td>
<td valign="top" align="center" rowspan="1" colspan="1"></td>
<td valign="top" align="center" rowspan="1" colspan="1"></td>
<td valign="top" align="center" rowspan="1" colspan="1"></td>
</tr>
<tr>
<td valign="top" align="left" rowspan="1" colspan="1"> Non-triple negative</td>
<td valign="top" align="right" rowspan="1" colspan="1">90</td>
<td valign="top" align="right" rowspan="1" colspan="1">289</td>
<td valign="top" align="center" rowspan="1" colspan="1">0.267</td>
<td valign="top" align="center" rowspan="1" colspan="1">0.602</td>
<td valign="top" align="center" rowspan="1" colspan="1">0.244–1.486</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn id="tfn2-medscimonit-23-4102">
<p>SLNM – sentinel lymphnode metastasis; SLN-NM – sentinel lymph node not metastasis; CI – confidence interval; ER – estrogen receptor; PR – progesterone receptor; HER2 – human epidermal growth factor receptor-2.</p>
</fn>
</table-wrap-foot>
</table-wrap>
<table-wrap id="t3-medscimonit-23-4102" position="float">
<label>Table 3</label>
<caption>
<p>Multivariate analysis for SLN metastasis predictive parameters</p>
</caption>
<table frame="hsides" rules="rows">
<thead>
<tr>
<th valign="middle" align="center" rowspan="1" colspan="1">Variable</th>
<th valign="middle" align="center" rowspan="1" colspan="1">SLNM (n)</th>
<th valign="middle" align="center" rowspan="1" colspan="1">SLN-NM (n)</th>
<th valign="middle" align="center" rowspan="1" colspan="1">p Value</th>
<th valign="middle" align="center" rowspan="1" colspan="1">Hazard ratio</th>
<th valign="middle" align="center" rowspan="1" colspan="1">95%CI</th>
</tr>
</thead>
<tbody>
<tr>
<td colspan="6" valign="top" align="left" rowspan="1">Age</td>
</tr>
<tr>
<td valign="top" align="left" rowspan="1" colspan="1"> <40 years</td>
<td valign="top" align="center" rowspan="1" colspan="1">24</td>
<td valign="top" align="right" rowspan="1" colspan="1">44</td>
<td valign="top" align="center" rowspan="1" colspan="1"></td>
<td valign="top" align="center" rowspan="1" colspan="1"></td>
<td valign="top" align="center" rowspan="1" colspan="1"></td>
</tr>
<tr>
<td valign="top" align="left" rowspan="1" colspan="1"> ≥40 years</td>
<td valign="top" align="center" rowspan="1" colspan="1">72</td>
<td valign="top" align="right" rowspan="1" colspan="1">277</td>
<td valign="top" align="center" rowspan="1" colspan="1">0.011</td>
<td valign="top" align="center" rowspan="1" colspan="1">2.188</td>
<td valign="top" align="center" rowspan="1" colspan="1">1.198–4.001</td>
</tr>
<tr>
<td colspan="6" valign="top" align="left" rowspan="1">Tumor size</td>
</tr>
<tr>
<td valign="top" align="left" rowspan="1" colspan="1"> ≤2 cm</td>
<td valign="top" align="center" rowspan="1" colspan="1">58</td>
<td valign="top" align="right" rowspan="1" colspan="1">250</td>
<td valign="top" align="center" rowspan="1" colspan="1"></td>
<td valign="top" align="center" rowspan="1" colspan="1"></td>
<td valign="top" align="center" rowspan="1" colspan="1"></td>
</tr>
<tr>
<td valign="top" align="left" rowspan="1" colspan="1"> >2 cm</td>
<td valign="top" align="center" rowspan="1" colspan="1">38</td>
<td valign="top" align="right" rowspan="1" colspan="1">71</td>
<td valign="top" align="center" rowspan="1" colspan="1">0.028</td>
<td valign="top" align="center" rowspan="1" colspan="1">0.616</td>
<td valign="top" align="center" rowspan="1" colspan="1">0.401–0.949</td>
</tr>
<tr>
<td colspan="6" valign="top" align="left" rowspan="1">Histological grade</td>
</tr>
<tr>
<td valign="top" align="left" rowspan="1" colspan="1"> I–II</td>
<td valign="top" align="center" rowspan="1" colspan="1">62</td>
<td valign="top" align="right" rowspan="1" colspan="1">270</td>
<td valign="top" align="center" rowspan="1" colspan="1"></td>
<td valign="top" align="center" rowspan="1" colspan="1"></td>
<td valign="top" align="center" rowspan="1" colspan="1"></td>
</tr>
<tr>
<td valign="top" align="left" rowspan="1" colspan="1"> III</td>
<td valign="top" align="center" rowspan="1" colspan="1">34</td>
<td valign="top" align="right" rowspan="1" colspan="1">51</td>
<td valign="top" align="center" rowspan="1" colspan="1">0.003</td>
<td valign="top" align="center" rowspan="1" colspan="1">0.408</td>
<td valign="top" align="center" rowspan="1" colspan="1">0.224–0.743</td>
</tr>
<tr>
<td colspan="6" valign="top" align="left" rowspan="1">Ki67</td>
</tr>
<tr>
<td valign="top" align="left" rowspan="1" colspan="1"> Low index</td>
<td valign="top" align="center" rowspan="1" colspan="1">54</td>
<td valign="top" align="right" rowspan="1" colspan="1">224</td>
<td valign="top" align="center" rowspan="1" colspan="1"></td>
<td valign="top" align="center" rowspan="1" colspan="1"></td>
<td valign="top" align="center" rowspan="1" colspan="1"></td>
</tr>
<tr>
<td valign="top" align="left" rowspan="1" colspan="1"> High index</td>
<td valign="top" align="center" rowspan="1" colspan="1">42</td>
<td valign="top" align="right" rowspan="1" colspan="1">97</td>
<td valign="top" align="center" rowspan="1" colspan="1">0.574</td>
<td valign="top" align="center" rowspan="1" colspan="1">0.851</td>
<td valign="top" align="center" rowspan="1" colspan="1">0.485–1.494</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn id="tfn3-medscimonit-23-4102">
<p>SLNM – sentinel lymph node metastasis; SLN-NM – sentinel lymph node not metastasis; CI – confidence interval</p>
</fn>
</table-wrap-foot>
</table-wrap>
</floats-group>
</pmc>
<affiliations>
<list>
<country>
<li>République populaire de Chine</li>
</country>
</list>
<tree>
<country name="République populaire de Chine">
<noRegion>
<name sortKey="Ding, Jinhua" sort="Ding, Jinhua" uniqKey="Ding J" first="Jinhua" last="Ding">Jinhua Ding</name>
</noRegion>
<name sortKey="Jiang, Li" sort="Jiang, Li" uniqKey="Jiang L" first="Li" last="Jiang">Li Jiang</name>
<name sortKey="Wu, Weizhu" sort="Wu, Weizhu" uniqKey="Wu W" first="Weizhu" last="Wu">Weizhu Wu</name>
</country>
</tree>
</affiliations>
</record>

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