Development of nomograms to predict axillary lymph node status in breast cancer patients.
Development of nomograms to predict axillary lymph node status in breast cancer patients.
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开发列线图来预测乳腺癌患者的腋窝淋巴结状态
DOI：
10.1186/s12885-017-3535-7
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发表时间：
2017-08-23
期刊：
影响因子：
3.8
通讯作者：
Jacobs L
中科院分区：
文献类型：
--
作者：
Chen K;Liu J;Li S;Jacobs L
研究背景乳腺癌患者术前预测腋窝淋巴结（ALN）状态是乳腺癌治疗的关键。本研究的目的是开发一套新的列线图，以准确地预测ALN status.MethodsWe搜索了国家癌症数据库，以确定符合条件的女性乳腺癌患者的配置文件包含关键信息。2010-2011年和2012-2013年诊断的患者分别被指定为训练（n= 99，618）和验证（n= 101，834）队列。我们使用二元逻辑回归来研究ALN状态的风险因素，并开发一组新的列线图来确定任何阳性ALN和N2-3疾病的概率。我们使用ROC分析和校准图来评估的判别能力和准确性的列线图，resultsIn训练队列，我们确定了年龄，象限的肿瘤，肿瘤大小，组织学，ER，PR，HER 2，肿瘤分级和淋巴血管浸润作为ALNs状态的显着预测。开发列线图-A以预测在训练和验证队列中C指数分别为0.788和0.786的全人群中具有任何阳性ALN（P_any）的概率。在阳性ALN患者中，开发Nomogram-B来预测N2-3疾病的条件概率（P_con），训练和验证队列中的C指数分别为0.680和0.677。有N2-3疾病的绝对概率可以估计由P_any*P_con. Both的诺模图well-calibrated.ConclusionsWe开发了一套诺模图来预测ALN状态在乳腺癌患者。
BackgroundPrediction of axillary lymph node (ALN) status preoperatively is critical in the management of breast cancer patients. This study aims to develop a new set of nomograms to accurately predict ALN status.MethodsWe searched the National Cancer Database to identify eligible female breast cancer patients with profiles containing critical information. Patients diagnosed in 2010–2011 and 2012–2013 were designated the training (n= 99,618) and validation (n= 101,834) cohorts, respectively. We used binary logistic regression to investigate risk factors for ALN status and to develop a new set of nomograms to determine the probability of having any positive ALNs and N2–3 disease. We used ROC analysis and calibration plots to assess the discriminative ability and accuracy of the nomograms, respectively.ResultsIn the training cohort, we identified age, quadrant of the tumor, tumor size, histology, ER, PR, HER2, tumor grade and lymphovascular invasion as significant predictors of ALNs status. Nomogram-A was developed to predict the probability of having any positive ALNs (P_any) in the full population with a C-index of 0.788 and 0.786 in the training and validation cohorts, respectively. In patients with positive ALNs, Nomogram-B was developed to predict the conditional probability of having N2–3 disease (P_con) with a C-index of 0.680 and 0.677 in the training and validation cohorts, respectively. The absolute probability of having N2–3 disease can be estimated by P_any*P_con. Both of the nomograms were well-calibrated.ConclusionsWe developed a set of nomograms to predict the ALN status in breast cancer patients.
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影响因子：
0.9
作者：
Leddy, Rebecca;Irshad, Abid;Lewis, Madelene
通讯作者：
Lewis, Madelene
影响因子：
168.9
作者：
Overgaard, M;Jensen, MB;Mouridsen, HT
通讯作者：
Mouridsen, HT
影响因子：
3
作者：
Wright, Gerald Paul;Mater, Megan E.;Chung, Mathew H.
通讯作者：
Chung, Mathew H.
DOI：
10.3390/s120709936
发表时间：
2012
期刊：
Sensors (Basel, Switzerland)
影响因子：
--
作者：
Xie F;Yang H;Wang S;Zhou B;Tong F;Yang D;Zhang J
通讯作者：
Zhang J
影响因子：
3.8
作者：
Chen, Jia-ying;Chen, Jia-jian;Wu, Jiong
通讯作者：
Wu, Jiong