Validation and modification study of axillary node pathologic complete response predictive model after neoadjuvant chemotherapy for breast cancer

郑卫真; 孙菊杰; 刘雁冰; 邱鹏飞; 毕　钊; 赵　桐; 王永胜

doi:10.19401/j.cnki.1007-3639.2019.06.008

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Validation and modification study of axillary node pathologic complete response predictive model after neoadjuvant chemotherapy for breast cancer

更新时间：2026-01-27

- Validation and modification study of axillary node pathologic complete response predictive model after neoadjuvant chemotherapy for breast cancer
- China Oncology Vol. 29, Issue 6, Pages: 445-451(2019)
- 作者机构：
  
  1. 济南大学山东省医学科学院医学与生命科学学院,山东,济南,250062
  2. 山东大学附属山东省肿瘤医院乳腺病中心外科三病区,山东,济南,250117
  3. 山东大学附属山东省肿瘤医院病理科,山东,济南,250117
- 作者简介：
- 基金信息：
- DOI：10.19401/j.cnki.1007-3639.2019.06.008
  CLC： R737.9;R730.53
- Published Online：12 July 2019，
  
  Published：12 July 2019
- 稿件说明：
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郑卫真，孙菊杰，刘雁冰，邱鹏飞，毕　钊，赵　桐，王永胜. 乳腺癌新辅助化疗后腋窝淋巴结病理学完全缓解预测模型的验证与改良研究[J]. 中国癌症杂志, 2019, 29(6): 445-451.

郑卫真, 孙菊杰, 刘雁冰, et al. Validation and modification study of axillary node pathologic complete response predictive model after neoadjuvant chemotherapy for breast cancer[J]. China Oncology, 2019, 29(6): 445-451.
郑卫真，孙菊杰，刘雁冰，邱鹏飞，毕　钊，赵　桐，王永胜. 乳腺癌新辅助化疗后腋窝淋巴结病理学完全缓解预测模型的验证与改良研究[J]. 中国癌症杂志, 2019, 29(6): 445-451. DOI： 10.19401/j.cnki.1007-3639.2019.06.008.

郑卫真, 孙菊杰, 刘雁冰, et al. Validation and modification study of axillary node pathologic complete response predictive model after neoadjuvant chemotherapy for breast cancer[J]. China Oncology, 2019, 29(6): 445-451. DOI： 10.19401/j.cnki.1007-3639.2019.06.008.

摘要

背景与目的：新辅助化疗（neoadjuvant chemotherapy，NAC）是局部晚期乳腺癌患者的标准治疗模式，2018年有研究报道了一个多变量预测模型，用于预测临床腋窝淋巴结阳性（clinical lymph node-positive，cN

）患者NAC后腋淋巴结病理完全缓解（ypN

）的概率。分析乳腺癌NAC后ypN

的相关因素，验证Olga Kantor预测模型的临床应用价值。方法：纳入山东大学附属山东省肿瘤医院2014年4月—2018年5月收治的350例临床腋淋巴结阳性NAC后行腋窝淋巴结清扫术（axillary lymph node dissection，ALND）的患者，并进行Olga Kantor预测模型的验证；由于该模型采用术后病理学评估乳腺原发肿瘤反应无助于术前预测ypN

，因此采用术前影像评价替代术后病理学评估进行改良，分别分析验证模型和改良模型的独立预测因素，计算受试者工作特征（receiver operating characteristic，ROC）曲线的曲线下面积（area under curve，AUC）评估两模型的预测效能。结果：验证模型中年龄、分型分组及病理乳房原发肿瘤反应为ypN0的独立预测指标，改良模型中年龄、分型分组及临床乳房原发肿瘤反应为ypN

的独立预测指标（P均＜0.05）。验证模型及改良模型的AUC分别为0.788和0.782（P0.05）。改良模型分数≤3分、4~7分及≥8分患者NAC后ypN

概率分别为2.5%（1/40）、22.4%（51/228）和68.3%（56/82）。结论：Olga Kantor预测模型可以较为准确地评估cN+患者ypN

概率，改良模型具有同等的预测效能且更贴合临床实际，有助于NAC后腋窝处理模式的合理选择：得分≤3分推荐直接行ALND，4~7分可选择前哨淋巴结活检（sentinel lymph node biopsy，SLNB），≥8分推荐行SLNB。

Abstract

Background and p

urpose: Neoadjuvant chemotherapy (NAC) has become the standard treatment method for locally advanced breast cancer. In 2018

researchers established a multivariate predictive model for predicting the probability of axillary complete response (ypN

) after NAC in patients with clinical axillary lymph node positive (cN

) disease. This study aimed to evaluate the related factors of ypN

after NAC

and to verify and modify the Olga Kantor predictive model for breast cancer patients. Methods: A total of 350 consecutive node-positive breast cancer patients who received axillary lymph node dissection (ALND) after NAC in Shandong Cancer Hospital Affiliated to Shandong University were retrospectively analyzed. As the pathological evaluation of the primary breast tumor response in the Olga Kantor model could not be used for preoperative prediction of ypN

preoperative image after NAC was incorporated in our study as a surrogate to modify this model. Independent predictive factors were analyzed both in the validation model and the modification model

and the predictive accuracy was assessed by the area under receiver operating characteristic (ROC) curve (AUC) in the two models. Results: Age

molecular subtype

Ki-67 and pathological extent of breast tumor response were independent predictors of ypN

in the validation model

while age

molecular subtype and clinical extent of breast tumor response were independent predictors in the modification model (P0.05

respectively). The validation and modification models achieved the AUC of 0.788 and 0.782

respectively (P0.05). In the modification model

patients with predictive score ≤3

4-7 and ≥8 reached ypN0 rates of 2.5% (1/40)

22.4% (51/228) and 68.3% (56/82)

respectively. Conclusion: Olga Kantor model could accurately predict ypN

after NAC

and our modification model could reach the same predictive power but was more in line with clinical practice

which could provide a reasonable support for patient selectio

n for sentinel lymph node biopsy (SLNB) after NAC. ALND is suggested in patients with score ≤3

SLNB is suitable for patients with score 4-7

and SLNB is recommended to patients with score ≥8.

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