Improved Model for Predicting Axillary Response to Neoadjuvant Chemotherapy in Patients with Clinically Node-Positive Breast Cancer

被引:22
|
作者
Kim, Hyung Suk [1 ]
Shin, Man Sik [1 ]
Kim, Chang Jong [1 ]
Yoo, Sun Hyung [1 ]
Yoo, Tae Kyung [1 ]
Eom, Yong Hwa [1 ]
Chae, Byung Joo [1 ]
Song, Byung Joo [2 ]
机构
[1] Catholic Univ Korea, Coll Med, Seoul St Marys Hosp, Dept Surg,Div Breast Surg, Seoul, South Korea
[2] Catholic Univ Korea, Coll Med, Bucheon St Marys Hosp, Dept Surg,Div Breast Surg, 327 Sosa Ro, Bucheon 14647, South Korea
关键词
Axilla; Breast neoplasms; Lymph nodes; Neoadjuvant therapy; PATHOLOGICAL COMPLETE RESPONSE; SOLID TUMORS; LYMPH-NODES; BIOPSY; TRIAL; DISSECTION; THERAPY; METASTASES; MANAGEMENT; MORBIDITY;
D O I
10.4048/jbc.2017.20.4.378
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
Purpose: Pathological complete response (pCR) of axillary lymph node (LN) is frequently achieved in patients with clinically node-positive breast cancer after neoadjuvant chemotherapy (NAC). Treatment of the axilla after NAC is not well established and the value of sentinel LN biopsy following NAC remains unclear. This study investigated the predictive value of axillary response following NAC and evaluated the predictive value of a model based on axillary response. Methods: Data prospectively collected on 201 patients with clinically node-positive breast cancer who were treated with NAC and underwent axillary LN dissection (ALND) were retrieved. A model predictive of axillary pCR was developed based on clinicopathologic variables. The overall predictive ability between models was compared by receiver operating characteristic (ROC) curve analysis. Results: Of 201 patients who underwent ALND after NAC, 68 (33.8%) achieved axillary pCR. Multivariate analysis using axillary LN pCR after NAC as the dependent variable showed that higher histologic grade (p=0.031; odds ratio [OR], 2.537; 95% confidence interval [CI], 1.087-5.925) and tumor response rate >= 47.1% (p=0.001; OR, 3.212; 95% CI, 1.584-6.515) were significantly associated with an increased probability of achieving axillary pCR. The area under the ROC curve for estimating axillary pCR was significantly higher in the model that included tumor response rate than in the model that excluded this rate (0.732 vs. 0.649, p=0.022). Conclusion: Tumor response rate was the most significant independent predictor of axillary pCR in response to NAC. The model that included tumor response rate was a significantly better predictor of axillary pCR than the model that excluded tumor response rate.
引用
收藏
页码:378 / 385
页数:8
相关论文
共 50 条
  • [1] Nomograms for Predicting Axillary Response to Neoadjuvant Chemotherapy in Clinically Node-Positive Patients with Breast Cancer
    Vila, Jose
    Mittendorf, Elizabeth A.
    Farante, Gabriel
    Bassett, Roland L.
    Veronesi, Paolo
    Galimberti, Viviana
    Peradze, Nicolas
    Stauder, Michael C.
    Chavez-MacGregor, Mariana
    Litton, Jennifer F.
    Huo, Lei
    Kuerer, Henry M.
    Hunt, Kelly K.
    Caudle, Abigail S.
    [J]. ANNALS OF SURGICAL ONCOLOGY, 2016, 23 (11) : 3501 - 3509
  • [2] Nomograms for Predicting Axillary Response to Neoadjuvant Chemotherapy in Clinically Node-Positive Patients with Breast Cancer
    Jose Vila
    Elizabeth A. Mittendorf
    Gabriel Farante
    Roland L. Bassett
    Paolo Veronesi
    Viviana Galimberti
    Nicolas Peradze
    Michael C. Stauder
    Mariana Chavez-MacGregor
    Jennifer F. Litton
    Lei Huo
    Henry M. Kuerer
    Kelly K. Hunt
    Abigail S. Caudle
    [J]. Annals of Surgical Oncology, 2016, 23 : 3501 - 3509
  • [3] Predictors of axillary node response in clinically node-positive patients undergoing neoadjuvant chemotherapy for breast cancer
    Ladak, Farah
    Lesniak, David
    Chua, Natalie
    Peiris, Lashan
    [J]. ANNALS OF SURGICAL ONCOLOGY, 2019, 26 : 264 - 265
  • [4] Predicting Axillary Response to Neoadjuvant Chemotherapy: Breast MRI and US in Patients with Node-Positive Breast Cancer
    Kim, Rihyeon
    Chang, Jung Min
    Lee, Han-Byoel
    Lee, Su Hyun
    Kim, Soo-Yeon
    Kim, Eun Sil
    Cho, Nariya
    Moon, Woo Kyung
    [J]. RADIOLOGY, 2019, 293 (01) : 49 - 57
  • [5] A Predictive Model for Axillary Pathologic Response after Neoadjuvant Chemotherapy for Clinically Node-Positive Breast Cancer
    Matsumoto, Akiko
    Naruse, Saki
    Isono, Yuka
    Maeda, Yuka
    Sato, Ayana
    Yamada, Miki
    Ikeda, Tatsuhiko
    Jinno, Hiromitsu
    [J]. CANCER RESEARCH, 2023, 83 (05)
  • [6] Axillary Management Following Neoadjuvant Chemotherapy in Clinically Node-Positive Breast Cancer
    Mitri, Samir
    Roldan-Vasquez, Estefania
    Flores, Rene
    Pardo, Jaime
    Borgonovo, Giulia
    Davis, Roger B.
    James, Ted A.
    [J]. CLINICAL BREAST CANCER, 2024, 24 (06) : 527 - 532
  • [7] Predictive value of tumor response rate for axillary response of neoadjuvant chemotherapy in patients with clinically node-positive breast cancer
    Kim, H. S.
    Eom, Y. H.
    Yoo, T. K.
    Song, B. J.
    Chae, B. J.
    [J]. ANNALS OF ONCOLOGY, 2016, 27
  • [8] Predictors of axillary node response in node-positive patients undergoing neoadjuvant chemotherapy for breast cancer
    Ladak, Farah
    Chua, Natalie
    Lesniak, David
    Ghosh, Sunita
    Wiebe, Ericka
    Yakimetz, Walter
    Rajaee, Nikoo
    Olson, David
    Peiris, Lashan
    [J]. CANADIAN JOURNAL OF SURGERY, 2022, 65 (01) : E89 - E96
  • [9] Nomogram for predicting axillary lymph node pathological response in node-positive breast cancer patients after neoadjuvant chemotherapy
    Wang Wenyan
    Wang Xin
    Liu Jiaqi
    Zhu Qiang
    Wang Xiang
    Wang Pilin
    [J]. 中华医学杂志(英文版), 2022, 135 (03) : 333 - 340
  • [10] Nomogram for predicting axillary lymph node pathological response in node-positive breast cancer patients after neoadjuvant chemotherapy
    Wang, Xin
    Wang, Wenyan
    Liu, Jiaxiang
    Meng, Xiangzhi
    Liu, Jiaqi
    Guo, Changyuan
    Song, Ying
    Cui, Ningyi
    Li, Qiao
    Xing, Zeyu
    Wang, Jie
    Zhang, Menglu
    Feng, Kexin
    Wang, Pilin
    Wang, Xiang
    [J]. CANCER RESEARCH, 2021, 81 (04)