Advances in breast cancer related nomograms

姚儒; 潘博; 孙强; 徐颖; 王常珺; 周易冬; 茅枫; 林燕

doi:10.3969/j.issn.1007-3969.2013.09.012

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Advances in breast cancer related nomograms

更新时间：2025-12-31

- Advances in breast cancer related nomograms
- China Oncology Vol. 23, Issue 9, Pages: 765-771(2013)
- 作者机构：
  
  中国医学科学院北京协和医院乳腺外科,北京,100730
- 作者简介：
- 基金信息：
- DOI：10.3969/j.issn.1007-3969.2013.09.012
  CLC：
- Published Online：20 February 2014，
  
  Published：2013
- 稿件说明：
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姚儒,潘博,孙强,徐颖,王常珺,周易冬,茅枫,林燕. 乳腺癌列线图模型的研究进展[J]. 中国癌症杂志, 2013, 23(9): 765-771.

姚儒, 潘博, 孙强, et al. Advances in breast cancer related nomograms[J]. China Oncology, 2013, 23(9): 765-771.
姚儒,潘博,孙强,徐颖,王常珺,周易冬,茅枫,林燕. 乳腺癌列线图模型的研究进展[J]. 中国癌症杂志, 2013, 23(9): 765-771. DOI： 10.3969/j.issn.1007-3969.2013.09.012.

姚儒, 潘博, 孙强, et al. Advances in breast cancer related nomograms[J]. China Oncology, 2013, 23(9): 765-771. DOI： 10.3969/j.issn.1007-3969.2013.09.012.

摘要

乳腺癌是危害全世界女性健康最常见的恶性肿瘤，对乳腺癌患者淋巴结转移情况及个体化预后进行评估预测，可为个体化综合治疗方案的制定以及临床决策提供参考依据。列线图模型(nomogram)可通过各种预测因素量化临床事件风险。从nomogram在前哨淋巴结阳性患者非前哨淋巴结转移预测、早期乳腺癌前哨淋巴结转移预测以及乳腺癌个体化预后预测等3个方面，分别评价其预测因素、应用特点以及预测的准确性等指标，以期在未来的工作中，通过选择更合理的预测因素、调整不同预测因素所占权重，以建立、改良能更好地应用于临床预测的nomogram模型，为制定临床决策提供参考依据。现就乳腺癌相关列线图模型的最新研究进展作一综述。

Abstract

Breast cancer is the leading cause of malignancy-related mortality in women worldwide. The more accurate prediction of lymph node metastasis and evaluation of personalized prognosis of breast cancer patients could provide evidence and reference for individualized comprehensive treatment and clinical decision-making. Nomogram is statistical calculation model developed to generate individualized prediction of a certain clinical event through the factors associated with it. Currently breast cancer related nomogram models is most commonly used in the prediction of non-sentinel lymph node status in patients with sentinel lymph node-positive breast cancer

sentinel lymph node metastasis in clinical node-negative breast cancer and prognosis evaluation of breast cancer. This article reviewed the recent advances in breast cancer related nomograms according to the above mentioned three aspects

and evaluated respectively the predictive factors

accuracy

characteristics and clinical application potential.

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