Simple Prediction Model of Axillary Lymph Node Positivity After Analyzing Molecular and Clinical Factors in Early Breast Cancer
Identifieur interne : 000B15 ( Main/Exploration ); précédent : 000B14; suivant : 000B16Simple Prediction Model of Axillary Lymph Node Positivity After Analyzing Molecular and Clinical Factors in Early Breast Cancer
Auteurs : Mi Joo Chung ; Jong Hoon Lee ; Sung Hwan Kim ; Young Jin Suh ; Hyun Joo ChoiSource :
- Medicine [ 0025-7974 ] ; 2016.
Abstract
The aim of this study was to evaluate the association between pretreatment molecular and clinical factors and axillary lymph node metastases in early breast cancer. A total of 367 consecutive breast cancer patients with cT1–2NxM0 who underwent breast conserving surgery and axillary lymph node dissection followed by whole breast irradiation were enrolled. We evaluated the pathologic tumor and node status, tumor differentiation, calcification, and lymphovascular invasion, the status of estrogen receptor (ER), progesterone receptor (PR), epidermal growth factor receptor 1 (EGFR1), and human epidermal growth factor receptor 2 (HER2), the expression of E-cadherin, P53, and Ki-67 index. Totally, 108 (29.4%) of the 367 patients had positive axillary lymph nodes. An increased tumor size (
Url:
DOI: 10.1097/MD.0000000000003689
PubMed: 27196477
PubMed Central: 4902419
Affiliations:
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<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">Simple Prediction Model of Axillary Lymph Node Positivity After Analyzing Molecular and Clinical Factors in Early Breast Cancer</title><author><name sortKey="Chung, Mi Joo" sort="Chung, Mi Joo" uniqKey="Chung M" first="Mi Joo" last="Chung">Mi Joo Chung</name></author><author><name sortKey="Lee, Jong Hoon" sort="Lee, Jong Hoon" uniqKey="Lee J" first="Jong Hoon" last="Lee">Jong Hoon Lee</name></author><author><name sortKey="Kim, Sung Hwan" sort="Kim, Sung Hwan" uniqKey="Kim S" first="Sung Hwan" last="Kim">Sung Hwan Kim</name></author><author><name sortKey="Suh, Young Jin" sort="Suh, Young Jin" uniqKey="Suh Y" first="Young Jin" last="Suh">Young Jin Suh</name></author><author><name sortKey="Choi, Hyun Joo" sort="Choi, Hyun Joo" uniqKey="Choi H" first="Hyun Joo" last="Choi">Hyun Joo Choi</name></author></titleStmt><publicationStmt><idno type="wicri:source">PMC</idno><idno type="pmid">27196477</idno><idno type="pmc">4902419</idno><idno type="url">http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4902419</idno><idno type="RBID">PMC:4902419</idno><idno type="doi">10.1097/MD.0000000000003689</idno><date when="2016">2016</date><idno type="wicri:Area/Pmc/Corpus">000789</idno><idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Corpus" wicri:corpus="PMC">000789</idno><idno type="wicri:Area/Pmc/Curation">000789</idno><idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Curation">000789</idno><idno type="wicri:Area/Pmc/Checkpoint">000598</idno><idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Checkpoint">000598</idno><idno type="wicri:Area/Ncbi/Merge">008310</idno><idno type="wicri:Area/Ncbi/Curation">008310</idno><idno type="wicri:Area/Ncbi/Checkpoint">008310</idno><idno type="wicri:doubleKey">0025-7974:2016:Chung M:simple:prediction:model</idno><idno type="wicri:Area/Main/Merge">000B16</idno><idno type="wicri:Area/Main/Curation">000B15</idno><idno type="wicri:Area/Main/Exploration">000B15</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en" level="a" type="main">Simple Prediction Model of Axillary Lymph Node Positivity After Analyzing Molecular and Clinical Factors in Early Breast Cancer</title><author><name sortKey="Chung, Mi Joo" sort="Chung, Mi Joo" uniqKey="Chung M" first="Mi Joo" last="Chung">Mi Joo Chung</name></author><author><name sortKey="Lee, Jong Hoon" sort="Lee, Jong Hoon" uniqKey="Lee J" first="Jong Hoon" last="Lee">Jong Hoon Lee</name></author><author><name sortKey="Kim, Sung Hwan" sort="Kim, Sung Hwan" uniqKey="Kim S" first="Sung Hwan" last="Kim">Sung Hwan Kim</name></author><author><name sortKey="Suh, Young Jin" sort="Suh, Young Jin" uniqKey="Suh Y" first="Young Jin" last="Suh">Young Jin Suh</name></author><author><name sortKey="Choi, Hyun Joo" sort="Choi, Hyun Joo" uniqKey="Choi H" first="Hyun Joo" last="Choi">Hyun Joo Choi</name></author></analytic><series><title level="j">Medicine</title><idno type="ISSN">0025-7974</idno><idno type="eISSN">1536-5964</idno><imprint><date when="2016">2016</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><title>Abstract</title><p>The aim of this study was to evaluate the association between pretreatment molecular and clinical factors and axillary lymph node metastases in early breast cancer. A total of 367 consecutive breast cancer patients with cT1–2NxM0 who underwent breast conserving surgery and axillary lymph node dissection followed by whole breast irradiation were enrolled. We evaluated the pathologic tumor and node status, tumor differentiation, calcification, and lymphovascular invasion, the status of estrogen receptor (ER), progesterone receptor (PR), epidermal growth factor receptor 1 (EGFR1), and human epidermal growth factor receptor 2 (HER2), the expression of E-cadherin, P53, and Ki-67 index. Totally, 108 (29.4%) of the 367 patients had positive axillary lymph nodes. An increased tumor size (<italic>P</italic> = 0.024), the presence of lymphovascular invasion (<italic>P</italic> < 0.001), and Ki-67 index of >20% (<italic>P</italic> = 0.038) were significantly associated with axillary lymph node metastases on the multivariate analysis. In our study, 86.2% of the patients with all the unfavorable factors had an involvement of axillary nodal metastases, and only 12.2% of the patients with all the favorable predictors had positive axillary nodes. The predictive power was significant on the receiver operating curve (<italic>P</italic> < 0.001). We found that several factors, such as tumor size, lymphovascular invasion, and the Ki-67 index, are independent factors that predict positive ALNM on multivariate analysis for the patients with cT1–2 breast cancer. Clinicians simply could predict the probability of ALNM after verifying the molecular and clinical factors in early breast cancer.</p></div></front><back><div1 type="bibliography"><listBibl><biblStruct><analytic><author><name sortKey="Donegan, Wl" uniqKey="Donegan W">WL Donegan</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Schaapveld, M" uniqKey="Schaapveld M">M Schaapveld</name></author><author><name sortKey="Otter, R" uniqKey="Otter R">R Otter</name></author><author><name sortKey="De Vries, Eg" uniqKey="De Vries E">EG de Vries</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Ernst, Mf" uniqKey="Ernst M">MF Ernst</name></author><author><name sortKey="Voogd, Ac" uniqKey="Voogd A">AC Voogd</name></author><author><name sortKey="Balder, W" uniqKey="Balder W">W Balder</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Lee, Jh" uniqKey="Lee J">JH Lee</name></author><author><name 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