A Nomogram to Predict the Pathologic Complete Response of Neoadjuvant Chemotherapy in Triple-Negative Breast Cancer Based on Simple Laboratory Indicators

被引:30
|
作者
Zhang, Fanrong [1 ,2 ]
Huang, Minran [3 ]
Zhou, Huanhuan [1 ,4 ]
Chen, Kaiyan [1 ,4 ]
Jin, Jiaoyue [1 ,5 ]
Wu, Yingxue [1 ,5 ]
Ying, Lisha [1 ,5 ]
Ding, Xiaowen [1 ,2 ]
Su, Dan [1 ,5 ]
Zou, Dehong [1 ,2 ]
机构
[1] Chinese Acad Sci, Inst Canc Res & Basic Med Sci, Hangzhou, Zhejiang, Peoples R China
[2] Univ Chinese Acad Sci, Zhejiang Canc Hosp, Canc Hosp, Dept Breast Surg, Hangzhou, Zhejiang, Peoples R China
[3] Zhejiang Chinese Med Univ, Clin Med Coll 2, Dept Oncol, Hangzhou, Zhejiang, Peoples R China
[4] Univ Chinese Acad Sci, Zhejiang Canc Hosp, Canc Hosp, Dept Chemotherapy, Hangzhou, Zhejiang, Peoples R China
[5] Univ Chinese Acad Sci, Zhejiang Canc Hosp, Canc Hosp, Dept Pathol, Hangzhou, Zhejiang, Peoples R China
关键词
REACTIVE PROTEIN/ALBUMIN RATIO; TO-MONOCYTE RATIO; CELL LUNG-CANCER; FREE SURVIVAL; D-DIMER; FIBRINOGEN; INFLAMMATION; OUTCOMES; THERAPY; TAXANES;
D O I
10.1245/s10434-019-07655-7
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
Background. Triple-negative breast cancer (TNBC) patients who achieve a pathologic complete response (pCR) after neoadjuvant chemotherapy (NAC) have better prognoses. Objective. This study aimed to develop an intuitive nomogram based on simple laboratory indexes to predict the pCR of standard NAC in TNBC patients. Methods. A total of 80 TNBC patients who received eight cycles of thrice-weekly standard NAC (anthracycline and cyclophosphamide followed by taxane) and subsequently underwent surgery in Zhejiang Cancer Hospital were retrospectively enrolled, and data on their pretreatment clinical features and multiple simple laboratory indexes were collected. The optimal cut-off values of the laboratory indexes were determined by the Youden index using receiver operating characteristic (ROC) curve analyses. Forward stepwise logistic regression (likelihood ratio) analysis was applied to identify predictive factors for a pCR of NAC. A nomogram was then developed according to the logistic model, and internally validated using the bootstrap resampling method. Results. pCR was achieved in 39 (48.8%) patients after NAC. Multivariate analysis identified four independent indicators: clinical tumor stage, lymphocyte to monocyte ratio, fibrinogen level, and D-dimer level. The nomogram established based on these factors showed its discriminatory ability, with an area under the curve (AUC) of 0.803 (95% confidence interval 0.706-0.899) and a bias-corrected AUC of 0.771. The calibration curve and Hosmer-Lemeshow test showed that the predictive ability of the nomogram was a good fit to actual observation. Conclusions. The nomogram proposed in the present study exhibited a sufficient discriminatory ability for predicting pCR of NAC in TNBC patients.
引用
收藏
页码:3912 / 3919
页数:8
相关论文
共 50 条
  • [1] A Nomogram to Predict the Pathologic Complete Response of Neoadjuvant Chemotherapy in Triple-Negative Breast Cancer Based on Simple Laboratory Indicators
    Fanrong Zhang
    Minran Huang
    Huanhuan Zhou
    Kaiyan Chen
    Jiaoyue Jin
    Yingxue Wu
    Lisha Ying
    Xiaowen Ding
    Dan Su
    Dehong Zou
    Annals of Surgical Oncology, 2019, 26 : 3912 - 3919
  • [2] A nomogram to predict pathologic complete response of neoadjuvant chemotherapy in triple-negative breast cancer based on simple blood indicators
    Zhang, F.
    Huang, M.
    Zhou, H.
    Chen, K.
    Jin, J.
    Ding, X.
    Su, D.
    Zou, D.
    ANNALS OF ONCOLOGY, 2019, 30
  • [3] Relationship between Complete Pathologic Response to Neoadjuvant Chemotherapy and Survival in Triple-Negative Breast Cancer
    Hatzis, Christos
    Symmans, W. Fraser
    Zhang, Ya
    Gould, Rebekah E.
    Moulder, Stacy L.
    Hunt, Kelly K.
    Abu-Khalaf, Maysa
    Hofstatter, Erin W.
    Lannin, Donald
    Chagpar, Anees B.
    Pusztai, Lajos
    CLINICAL CANCER RESEARCH, 2016, 22 (01) : 26 - 33
  • [4] Predictors of Distant Metastases in Triple-Negative Breast Cancer Without Pathologic Complete Response After Neoadjuvant Chemotherapy
    Kennedy, William R.
    Tricarico, Christopher
    Gabani, Prashant
    Weiner, Ashley A.
    Altman, Michael B.
    Ochoa, Laura L.
    Thomas, Maria A.
    Margenthaler, Julie A.
    Sanati, Souzan
    Peterson, Lindsay L.
    Ma, Cynthia X.
    Ademuyiwa, Foluso O.
    Zoberi, Imran
    JOURNAL OF THE NATIONAL COMPREHENSIVE CANCER NETWORK, 2020, 18 (03): : 288 - 296
  • [5] Predictors of Pathologic Complete Response After Standard Neoadjuvant Chemotherapy in Triple-negative Breast Carcinoma
    Kraus, James A.
    Beriwal, Sushil
    Dabbs, David J.
    Ahrendt, Gretchen M.
    McGuire, Kandace P.
    Johnson, Ronald R.
    Badve, Preeti
    Puhalla, Shannon L.
    Bhargava, Rohit
    APPLIED IMMUNOHISTOCHEMISTRY & MOLECULAR MORPHOLOGY, 2012, 20 (04): : 334 - 339
  • [6] A nomogram based on clinicopathological features and serological indicators predicting breast pathologic complete response of neoadjuvant chemotherapy in breast cancer
    Yijun Li
    Jian Zhang
    Bin Wang
    Huimin Zhang
    Jianjun He
    Ke Wang
    Scientific Reports, 11
  • [7] A nomogram based on clinicopathological features and serological indicators predicting breast pathologic complete response of neoadjuvant chemotherapy in breast cancer
    Li, Yijun
    Zhang, Jian
    Wang, Bin
    Zhang, Huimin
    He, Jianjun
    Wang, Ke
    SCIENTIFIC REPORTS, 2021, 11 (01)
  • [8] Predictive biomarker of pathologic complete response to neoadjuvant chemotherapy in triple negative breast cancer
    Kim, T.
    Han, W.
    Moon, H-G
    Noh, D-Y
    CANCER RESEARCH, 2012, 72
  • [9] Meta-analysis on the association between pathologic complete response and triple-negative breast cancer after neoadjuvant chemotherapy
    Wu, Kunpeng
    Yang, Qiaozhu
    Liu, Yi
    Wu, Aibing
    Yang, Zhixiong
    WORLD JOURNAL OF SURGICAL ONCOLOGY, 2014, 12
  • [10] Meta-analysis on the association between pathologic complete response and triple-negative breast cancer after neoadjuvant chemotherapy
    Kunpeng Wu
    Qiaozhu Yang
    Yi Liu
    Aibing Wu
    Zhixiong Yang
    World Journal of Surgical Oncology, 12