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BMC Cancer
Published in: BMC Cancer 1/2016

Open Access 01-12-2016 | Research article

A nomogram for predicting pathological complete response in patients with human epidermal growth factor receptor 2 negative breast cancer

Authors: Xi Jin, Yi-Zhou Jiang, Sheng Chen, Ke-Da Yu, Ding Ma, Wei Sun, Zhi-Min Shao, Gen-Hong Di

Published in: BMC Cancer | Issue 1/2016

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Abstract

Background

The response to neoadjuvant chemotherapy has been proven to predict long-term clinical benefits for patients. Our research is to construct a nomogram to predict pathological complete response of human epidermal growth factor receptor 2 negative breast cancer patients.

Methods

We enrolled 815 patients who received neoadjuvant chemotherapy from 2003 to 2015 and divided them into a training set and a validation set. Univariate logistic regression was performed to screen for predictors and construct the nomogram; multivariate logistic regression was performed to identify independent predictors.

Results

After performing the univariate logistic regression analysis in the training set, tumor size, hormone receptor status, regimens of neoadjuvant chemotherapy and cycles of neoadjuvant chemotherapy were the final predictors for the construction of the nomogram. The multivariate logistic regression analysis demonstrated that T4 status, hormone receptor status and receiving regimen of paclitaxel and carboplatin were independent predictors of pathological complete response. The area under the receiver operating characteristic curve of the training set and the validation set was 0.779 and 0.701, respectively.

Conclusions

We constructed and validated a nomogram to predict pathological complete response in human epidermal growth factor receptor 2 negative breast cancer patients. We also identified tumor size, hormone receptor status and paclitaxel and carboplatin regimen as independent predictors of pathological complete response.
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Metadata
Title
A nomogram for predicting pathological complete response in patients with human epidermal growth factor receptor 2 negative breast cancer
Authors
Xi Jin
Yi-Zhou Jiang
Sheng Chen
Ke-Da Yu
Ding Ma
Wei Sun
Zhi-Min Shao
Gen-Hong Di
Publication date
01-12-2016
Publisher
BioMed Central
Published in
BMC Cancer / Issue 1/2016
Electronic ISSN: 1471-2407
DOI
https://doi.org/10.1186/s12885-016-2652-z

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