Back to Search Start Over

A study of neutrophil to lymphocyte ratio for the prediction of axillary pathological complete response after neoadjuvant therapy in breast cancer

Authors :
BI Zhao , SONG Xianrang , CHEN Peng , XIE Li , JIANG Wei , SONG Xingguo , CONG Binbin , WANG Yongsheng
Source :
Zhongguo aizheng zazhi, Vol 31, Iss 1, Pp 63-68 (2021)
Publication Year :
2021
Publisher :
Editorial Office of China Oncology, 2021.

Abstract

Background and purpose: Neutrophil to lymphocyte ratio (NLR) is a simple, objective and inexpensive laboratory indicator, and its predictive value has been verified in different types of cancer. The purpose of this study was to integrate pretreatment indicators including clinical factors with NLR to predict axillary pathological complete response (apCR) after neoadjuvant therapy (NAT). Methods: From April 2016 to April 2020, 416 breast cancer patients with clinical nodal positive disease undergoing operation after NAT were included. The pretreatment clinicopathological factors and laboratory indexes were collected. The optimal cut-off values of age and laboratory indexes were determined by Youden index using receiver operating characteristic (ROC) curve analyses. The logistic regression analysis was applied to examine predictive factors of apCR. Then, a logistic model was developed according to multivariate analysis results, and it was analyzed using ROC curve and area under curve (AUC) value. Results: Among 416 patients, 37.3% (155) of them achieved apCR. The multivariate analysis showed that age (OR=0.528, 95% CI: 0.343-0.814), pathological grade (OR=1.846, 95% CI: 1.187-2.872), molecular subtype (OR=2.791, 95% CI: 1.780-4.377) and NLR (OR=0.302, 95% CI: 0.105-0.867) were indicated as independent predictors of apCR. Based on these factors, we built the logistic model to predict apCR: logit(P)=0.613×pathological grading+1.027×molecular subtype-0.638×age-1.196×NLR-0.244 (model checking χ 2 =54.478, P< 0.001). The AUC value of the logistic model was 0.702. Conclusion: Except for traditional clinical factors, the NLR level could also be identified as predictive factor of apCR after NAT. Integrating traditional clinical factors with NLR level could help to predict apCR and guide individualized treatment options.

Details

Language :
English, Chinese
ISSN :
10073639
Volume :
31
Issue :
1
Database :
Directory of Open Access Journals
Journal :
Zhongguo aizheng zazhi
Publication Type :
Academic Journal
Accession number :
edsdoj.7b238a62c1704a34aacb29be142a50ff
Document Type :
article
Full Text :
https://doi.org/10.19401/j.cnki.1007-3639.2021.01.008