Abstract
The purpose was to integrate clinicopathological and laboratory indicators to predict axillary nodal pathologic complete response (apCR) after neoadjuvant therapy (NAT). The pretreatment clinicopathological and laboratory indicators of 416 clinical nodal-positive breast cancer patients who underwent surgery after NAT were analyzed from April 2015 to 2020. Predictive factors of apCR were examined by logistic analysis. A nomogram was built according to logistic analysis. Among the 416 patients, 37.3% achieved apCR. Multivariate analysis showed that age, pathological grading, molecular subtype and neutrophil-to-lymphocyte ratio were independent predictors of apCR. A nomogram was established based on these four factors. The area under the curve (AUC) was 0.758 in the training set. The validation set showed good discrimination, with AUC of 0.732. In subtype analysis, apCR was 23.8, 47.1 and 50.8% in hormone receptor-positive/HER2-, HER2+ and triple-negative subgroups, respectively. According to the results of the multivariate analysis, pathological grade and fibrinogen level were independent predictors of apCR after NAT in HER2+ patients. Except for traditional clinicopathological factors, laboratory indicators could also be identified as predictive factors of apCR after NAT. The nomogram integrating pretreatment indicators demonstrated its distinguishing capability, with a high AUC, and could help to guide individualized treatment options.
Lay abstract
The purpose of this study was to integrate more pretreatment indicators, including clinicopathological factors and simple laboratory indicators, to predict axillary nodal pathologic complete response (apCR) after neoadjuvant therapy for breast cancer. The authors collected the pretreatment clinicopathological factors and laboratory indexes of 416 nodal-positive patients with breast cancer. The authors then built a nomogram to predict the therapeutic effect in axillary lymph nodes. Among 416 patients, 37.3% (155 of 416) achieved apCR. The results showed that age, pathological grading, molecular subtype and neutrophil-to-lymphocyte ratio were independent predictors of apCR. Based on these four factors, a nomogram was then built. This nomogram helped to predict apCR. In addition to traditional clinicopathological factors, laboratory indicators were also identified as predictive factors of apCR after neoadjuvant therapy. Integrating pretreatment indicators might help to predict apCR and guide individualized treatment options.
Author contributions
P Chen, T Zhao and Z Bi were responsible for study conception and design. X Song, C Wang and Y Wang were responsible for acquisition of data and analysis. Z Bi, Z Zhang, L Xie, Y Liu and X Song were responsible for drafting the manuscript. All authors were responsible for integration of data/results and revision of the manuscript.
Financial & competing interests disclosure
This work was funded by the National Natural Science Foundation of China (no. 81672638 and 81672104), Shandong Provincial Key Research and Development Program (no. 2016GSF201146, 2017CXGC1207, 2019GSF108179 and 2019GSF108104) and Shandong Cancer Hospital and Institute Clinical Training Program (no. 20206108). The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed.
No writing assistance was utilized in the production of this manuscript.
Ethical conduct of research
The study was approved by the Shandong Cancer Hospital Ethics Committee (no. SDTHEC20110324). All patients signed informed consent, and all procedures were conducted in accordance with the ethical standards of the responsible institutional committee on human experimentation and with the Declaration of Helsinki.