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To achieve this, we used a decision tree-based prediction method\u2014the alternating decision tree (ADTree).<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Methods<\/jats:title>\n            <jats:p>Clinical datasets for primary breast cancer patients who underwent sentinel lymph node biopsy or AxLN dissection without prior treatment were collected from three institutes (institute A, <jats:italic>n<\/jats:italic>\u2009=\u2009148; institute B, <jats:italic>n<\/jats:italic>\u2009=\u2009143; institute C, <jats:italic>n<\/jats:italic>\u2009=\u2009174) and were used for variable selection, model training and external validation, respectively. The models were evaluated using area under the receiver operating characteristics (ROC) curve analysis to discriminate node-positive patients from node-negative patients.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Results<\/jats:title>\n            <jats:p>The ADTree model selected 15 of 24 clinicopathological variables in the variable selection dataset. The resulting area under the ROC curve values were 0.770 [95% confidence interval (CI), 0.689\u20130.850] for the model training dataset and 0.772 (95% CI: 0.689\u20130.856) for the validation dataset, demonstrating high accuracy and generalization ability of the model. The bootstrap value of the validation dataset was 0.768 (95% CI: 0.763\u20130.774).<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Conclusions<\/jats:title>\n            <jats:p>Our prediction model showed high accuracy for predicting nodal metastasis in patients with breast cancer using commonly recorded clinical variables. Therefore, our model might help oncologists in the decision-making process for primary breast cancer patients before starting treatment.<\/jats:p>\n          <\/jats:sec>","DOI":"10.1186\/1472-6947-12-54","type":"journal-article","created":{"date-parts":[[2012,6,21]],"date-time":"2012-06-21T19:22:36Z","timestamp":1340306556000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":35,"title":["Prediction of axillary lymph node metastasis in primary breast cancer patients using a decision tree-based model"],"prefix":"10.1186","volume":"12","author":[{"given":"Masahiro","family":"Takada","sequence":"first","affiliation":[]},{"given":"Masahiro","family":"Sugimoto","sequence":"additional","affiliation":[]},{"given":"Yasuhiro","family":"Naito","sequence":"additional","affiliation":[]},{"given":"Hyeong-Gon","family":"Moon","sequence":"additional","affiliation":[]},{"given":"Wonshik","family":"Han","sequence":"additional","affiliation":[]},{"given":"Dong-Young","family":"Noh","sequence":"additional","affiliation":[]},{"given":"Masahide","family":"Kondo","sequence":"additional","affiliation":[]},{"given":"Katsumasa","family":"Kuroi","sequence":"additional","affiliation":[]},{"given":"Hironobu","family":"Sasano","sequence":"additional","affiliation":[]},{"given":"Takashi","family":"Inamoto","sequence":"additional","affiliation":[]},{"given":"Masaru","family":"Tomita","sequence":"additional","affiliation":[]},{"given":"Masakazu","family":"Toi","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2012,6,13]]},"reference":[{"key":"499_CR1","doi-asserted-by":"publisher","first-page":"1551","DOI":"10.1002\/1097-0142(19831101)52:9<1551::AID-CNCR2820520902>3.0.CO;2-3","volume":"52","author":"B Fisher","year":"1983","unstructured":"Fisher B, Bauer M, Wickerham DL, Redmond CK, Fisher ER, Cruz AB, Foster R, Gardner B, Lerner H, Margolese R: Relation of number of positive axillary nodes to the prognosis of patients with primary breast cancer. 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