The residual cancer burden index as a valid prognostic indicator in breast cancer after neoadjuvant chemotherapy

• Published in: BMC cancer Vol. 24; no. 1; pp. 13 - 12
• Main Authors: Xu, Xin, Zhao, Wei, Liu, Cuicui, Gao, Yongsheng, Chen, Dawei, Wu, Meng, Li, Chao, Wang, Xinzhao, Song, Xiang, Yu, Jinming, Liu, Zhaoyun, Yu, Zhiyong
• Format: Journal Article
• Language: English
• Published: England BioMed Central Ltd 02.01.2024; BioMed Central; BMC
• Subjects: Adjuvant treatment; Antineoplastic Combined Chemotherapy Protocols - therapeutic use; Breast cancer; Breast Neoplasms - pathology; Cancer; Cancer patients; Cancer therapies; Care and treatment; Chemotherapy; Classification; Comorbidity; Comparative analysis; Development and progression; Diagnosis; ErbB-2 protein; Female; Gene amplification; Humans; Medical prognosis; Medical records; Metastasis; Miller-Payne grading; Neoadjuvant chemotherapy; Neoadjuvant Therapy; Neoplasm Recurrence, Local - drug therapy; Neoplasm, Residual - pathology; Oncology, Experimental; Pathologic complete response; Pathology; Patients; Prognosis; Recurrence; Regression analysis; Residual cancer burden; Retrospective Studies; Risk factors; Statistical analysis; Surgery; Triple Negative Breast Neoplasms - pathology; China; Taiwan; Neoadjuvant chemotherapy; Pathologic complete response; Breast cancer; Residual cancer burden; Miller-Payne grading
• DOI: 10.1186/s12885-023-11719-z
• ISSN: 1471-2407

The residual cancer burden index (RCB) was proposed as a response evaluation criterion in breast cancer patients treated with Neoadjuvant Chemotherapy (NAC). This study evaluated the relevance of RCB with replase-free survival (RFS). The clinical data of 254 breast cancer patients who received NAC between 2016 and 2020 were retrospectively collected. The relationship between clinicopathologic factors and RFS was evaluated using Cox proportional hazards regression models. RFS estimates were determined by Kaplan-Meier(K-M) analysis and compared using the log-rank test. Multivariate logistic regression analysis was used to evaluate the risk factors associated with RCB. Receiver operating characteristic (ROC) curves showed the potential of the RCB and MP grading systems as biomarkers for RFS. At a median follow-up of 52 months, 59 patients(23.23%) developed relapse. Multivariate Cox regression showed that older age (P = 0.022), high Pathologic T stage after NAC (P = 0.023) and a high RCB score(P = 0.003) were risk factors for relapse. The outcomes of the multivariate logistic analysis indicated that RCB 0 (pathologic complete response [pCR]) was associated with HER2-positive patients (P = 0.002) and triple-negative breast cancer (TNBC) patients (P = 0.013). In addition, the RCB and MP scoring systems served as prognostic markers for patients who received NAC, and their area under curves (AUCs) were 0.691 and 0.342, respectively. These data suggest that RCB can be equally applied to predict RFS in Chinese patients with NAC. The application of RCB may help guide the selection of treatment strategies.