Internal mammary node metastasis in breast cancer: Predictive models to determine status & management algorithms

Abstract

Aim Internal mammary node (IMN) metastases are an important prognostic factor in breast cancer. However due to difficulty of access, most surgeons ignore these nodes, hence adjuvant treatment decisions may be compromised. Through mathematical modeling based on large datasets this study aims to estimate the current rate of IMN and sentinel node metastasis. Methods Models were created to estimate the current rate of axillary and IM sentinel node metastasis. Data from historical extended radical mastectomy series were analyzed to project contemporary rates of IMN metastasis. This information was coupled with derived models and contemporary datasets: a single-institution breast lymphoscintigraphy database (1992–2007) to establish lymphatic anatomy; and the Surveillance, Epidemiology and End-Results (SEER) registries in the US (2000–2003). Results Rates of IMN metastasis and positive sentinel nodes were estimated and models derived to assist with predicting IMN status in patients. If high definition peritumoral lymphatic mapping were available, the predicted rates of positive sentinel nodes in the axilla (AN) and internal mammary chain (IMN) would be equal. We predicted the overall rate of IMN metastasis is ∼39% the rate of positive sentinel AN. Conclusion Simplified models and algorithms can predict IMN status.