首页> 中文期刊> 《中华放射肿瘤学杂志》 >早期乳腺癌腋窝前哨淋巴结阳性患者腋窝非前哨淋巴结转移风险预测

早期乳腺癌腋窝前哨淋巴结阳性患者腋窝非前哨淋巴结转移风险预测

摘要

Objective To evaluate the risk factors of non-sentinel lymph node (NSLN) metastasis in breast cancer patients with 1-2 positive sentinel lymph nodes and to establish a new Nomogram prediction model.Methods Clinicopathological data of breast cancer patients who were diagnosed with 1-2 positive lymph nodes and underwent axillary lymph node dissection (ALND) without neoadjuvant chemotherapy from January 2008 to December 2014 were retrospectively analyzed.Measurement data between two groups were analyzed by chi-square test.Multivariate analysis was performed by logistic regression model.The prediction accuracy of the Nomogram model was evaluated using the area under the receiver operating characteristic curve (AUC) and calibration curves.Results A total of 270 patients were recruited in this study.Among them,87(32.2%) patients had NSLN metastases.The median age was 46 years old (21-80 years),the median number of SLNs was 4 (1-10) and the median number of axillary lymph nodes was 20(10-41).Univariate analysis demonstrated that the pathological grade,the size of SLN metastasis,the number of negative and positive SLNs were the risk factors of NSLN metastasis (P=0.001-0.045).Multivariate analysis showed that pathological grade,the number of negative and positive SLNs were independent risk factors of NSLN metastasis (P=0.000-0.041).The AUC value of Nomogram prediction model for NSLN metastasis was 0.70.The false negative rate of Nomogram was 10.5% when the cut-off point of predictive probability was ≤ 15%.Conclusions The Nomogram is a useful prediction model for evaluating NSLN metastasis.ALND or axillary radiotherapy can be avoided for patients with a low probability of NSLN metastasis.%目的 分析前哨淋巴结活检(SLNB)1~2个阳性乳腺癌患者中非前哨淋巴结(NSLN)转移的影响因素并构建预测模型.方法 回顾分析2008-2014年中国医学科学院北京协和医学院肿瘤医院未行新辅助化疗前哨淋巴结1~2个阳性并行腋窝淋巴结清扫的乳腺癌患者的临床病理因素.计数资料组间比较采用x2检验,多因素分析采用Logistic回归模型.以AUC值和校正曲线对Nomogram预测模型进行评估.结果 共270例患者纳入研究,87例(32.2%)存在NSLN转移.中位年龄46(21~80)岁,中位SLN送检个数4(1~10)个,中位腋窝淋巴结清扫个数20(10~41)个.单因素分析结果显示病理分级、SLN宏转移、阳性SLN个数和阴性SLN个数是腋窝NSLN转移的影响因素(P=0.001~0.045).多因素分析结果显示病理分级、阳性SLN个数和阴性SLN个数是NSLN转移的独立影响因素(P=0.000~0.041).乳腺癌NSLN转移Nomogram预测模型AUC=0.70,当预测患者的NSLN转移率≤15%时,假阴性率仅为10.5%.结论 Nomogram预测模型可作为临床医师进行腋窝处理时的决策参考,对于NSLN转移概率低的患者可以避免行腋窝淋巴结清扫或腋窝放疗.

著录项

  • 来源
    《中华放射肿瘤学杂志》 |2019年第2期|102-107|共6页
  • 作者单位

    Department of Radiation Oncology, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences(CAMS)and Peking Union Medical College(PUMC), Beijing 100021, China;

    Department of Radiation Oncology, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences(CAMS)and Peking Union Medical College(PUMC), Beijing 100021, China;

    Department of Radiation Oncology, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences(CAMS)and Peking Union Medical College(PUMC), Beijing 100021, China;

    Department of Radiation Oncology, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences(CAMS)and Peking Union Medical College(PUMC), Beijing 100021, China;

    Department of Radiation Oncology, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences(CAMS)and Peking Union Medical College(PUMC), Beijing 100021, China;

    Department of Radiation Oncology, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences(CAMS)and Peking Union Medical College(PUMC), Beijing 100021, China;

    Department of Radiation Oncology, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences(CAMS)and Peking Union Medical College(PUMC), Beijing 100021, China;

    Department of Radiation Oncology, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences(CAMS)and Peking Union Medical College(PUMC), Beijing 100021, China;

    Department of Radiation Oncology, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences(CAMS)and Peking Union Medical College(PUMC), Beijing 100021, China;

    Department of Radiation Oncology, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences(CAMS)and Peking Union Medical College(PUMC), Beijing 100021, China;

    Department of Radiation Oncology, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences(CAMS)and Peking Union Medical College(PUMC), Beijing 100021, China;

    Department of Radiation Oncology, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences(CAMS)and Peking Union Medical College(PUMC), Beijing 100021, China;

    Department of Radiation Oncology, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences(CAMS)and Peking Union Medical College(PUMC), Beijing 100021, China;

    Department of Radiation Oncology, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences(CAMS)and Peking Union Medical College(PUMC), Beijing 100021, China;

    Department of Radiation Oncology, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences(CAMS)and Peking Union Medical College(PUMC), Beijing 100021, China;

    Department of Radiation Oncology, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences(CAMS)and Peking Union Medical College(PUMC), Beijing 100021, China;

  • 原文格式 PDF
  • 正文语种 chi
  • 中图分类
  • 关键词

    乳腺肿瘤; 前哨淋巴结; 非前哨淋巴结; 预测模型;

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