Literature DB >> 31359285

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

Fanrong Zhang1,2, Minran Huang3, Huanhuan Zhou1,4, Kaiyan Chen1,4, Jiaoyue Jin1,5, Yingxue Wu1,5, Lisha Ying1,5, Xiaowen Ding1,2, Dan Su6,7, Dehong Zou8,9.   

Abstract

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.

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Year:  2019        PMID: 31359285     DOI: 10.1245/s10434-019-07655-7

Source DB:  PubMed          Journal:  Ann Surg Oncol        ISSN: 1068-9265            Impact factor:   5.344


  11 in total

1.  Construction of Nomograms for Predicting Pathological Complete Response and Tumor Shrinkage Size in Breast Cancer.

Authors:  Shuai Yan; Wenjie Wang; Bifa Zhu; Xixi Pan; Xiaoyan Wu; Weiyang Tao
Journal:  Cancer Manag Res       Date:  2020-09-10       Impact factor: 3.989

2.  Development and Validation of a Nomogram to Predict the Probability of Breast Cancer Pathologic Complete Response after Neoadjuvant Chemotherapy: A Retrospective Cohort Study.

Authors:  Yijun Li; Jian Zhang; Bin Wang; Huimin Zhang; Jianjun He; Ke Wang
Journal:  Front Surg       Date:  2022-06-09

3.  A nomogram based on clinicopathological features and serological indicators predicting breast pathologic complete response of neoadjuvant chemotherapy in breast cancer.

Authors:  Yijun Li; Jian Zhang; Bin Wang; Huimin Zhang; Jianjun He; Ke Wang
Journal:  Sci Rep       Date:  2021-05-31       Impact factor: 4.379

4.  Novel biomarkers and prediction model for the pathological complete response to neoadjuvant treatment of triple-negative breast cancer.

Authors:  Yiqun Han; Jiayu Wang; Binghe Xu
Journal:  J Cancer       Date:  2021-01-01       Impact factor: 4.207

5.  Development and validation of a prognostic nomogram for patients with triple-negative breast cancer with histology of infiltrating duct carcinoma.

Authors:  Na Jing; Ming-Wei Ma; Xian-Shu Gao; Jian-Ting Liu; Xiao-Bin Gu; Min Zhang; Bo Zhao; Yu Wang; Xian-Ling Wang; Hai-Xia Jia
Journal:  Ann Transl Med       Date:  2020-11

6.  Construction and Validation of a Serum Albumin-to-Alkaline Phosphatase Ratio-Based Nomogram for Predicting Pathological Complete Response in Breast Cancer.

Authors:  Fanli Qu; Zongyan Li; Shengqing Lai; XiaoFang Zhong; Xiaoyan Fu; Xiaojia Huang; Qian Li; Shengchun Liu; Haiyan Li
Journal:  Front Oncol       Date:  2021-10-08       Impact factor: 6.244

7.  A Practical Predictive Model Based on Ultrasound Imaging and Clinical Indices for Estimation of Response to Neoadjuvant Chemotherapy in Patients with Breast Cancer.

Authors:  Pingping Ye; Hongbo Duan; Zhenya Zhao; Shibo Fang
Journal:  Cancer Manag Res       Date:  2021-10-09       Impact factor: 3.989

8.  Prognostic Value of Salivary Biochemical Indicators in Primary Resectable Breast Cancer.

Authors:  Lyudmila V Bel'skaya; Elena A Sarf
Journal:  Metabolites       Date:  2022-06-16

9.  Can We Reliably Identify the Pathological Outcomes of Neoadjuvant Chemotherapy in Patients with Breast Cancer? Development and Validation of a Logistic Regression Nomogram Based on Preoperative Factors.

Authors:  Jian Zhang; Linhai Xiao; Shengyu Pu; Yang Liu; Jianjun He; Ke Wang
Journal:  Ann Surg Oncol       Date:  2020-10-23       Impact factor: 5.344

10.  Neoadjuvant Chemotherapy of Triple-Negative Breast Cancer: Evaluation of Early Clinical Response, Pathological Complete Response Rates, and Addition of Platinum Salts Benefit Based on Real-World Evidence.

Authors:  Milos Holanek; Iveta Selingerova; Ondrej Bilek; Tomas Kazda; Pavel Fabian; Lenka Foretova; Maria Zvarikova; Radka Obermannova; Ivana Kolouskova; Oldrich Coufal; Katarina Petrakova; Marek Svoboda; Alexandr Poprach
Journal:  Cancers (Basel)       Date:  2021-03-30       Impact factor: 6.639

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