Residual cancer burden is a predictor for all-type breast cancer patients

Residual cancer burden (RCB) after neoadjuvant chemotherapy has shown to be an accurate long-term predictor of recurrence and survival across all breast cancer subtypes, as demonstrated by a large meta-analysis of breast cancer patients.

RCB is assessed through several factors, including the size of the primary tumour, the percentage of the tumour which is invasive versus in situ, and the involvement of lymph nodes. Although many single-institution studies have shown that RCB after neoadjuvant chemotherapy is informative about a patient’s prognosis after surgery, a meta-analysis was done to help determine whether this is true for all subtypes, and how generalisable previous findings might be [1]. Data from 12 cancer centres or clinical trials representing approximately 5,100 patients were compiled and analysed in this study. Using mixed effect models, associations between the RCB index and event-free survival (EFS) and distant recurrence-free survival (DRFS) were examined.

It was shown that the RCB index was tightly associated with both EFS and DRFS, and that this was consistent across 12 clinical sites and all 4 types of breast cancer (hormone receptor (HR)-positive/human epidermal growth factor receptor 2 (HER2)-negative; HR-positive/HER2-positive; HR-negative/HER2-positive; and HR-negative/HER2-negative). Researchers commented that the measurement of the RCB index is strongly prognostic and allows physicians to confidentially measure risk of recurrence. This meta-analysis of RCB provides real-world evidence of how patients are responding to neoadjuvant treatments, and calibration of the RCB index to prognostic risk enables them to determine the most appropriate next steps for breast cancer patients. A limitation of the study was that it was based on data from multiple institutions, which may lead to some variation in clinical methods, the handling of specimens, and possible other factors. Standardising the reporting of RCB will only improve its usefulness in determining long-term prognosis.

1. Yau C, et al. GS5-01. SABCS 2019.



Posted on 13 February, 202030 March, 2021