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, 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.
,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
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
0
) after NAC in patients with clinical axillary lymph node positive (cN
+
) disease. This study aimed to evaluate the related factors of ypN
0
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
0
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
0
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
0
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.