Comparison of three lymph node staging methods for predicting outcome in breast cancer patients with mastectomy.

backgroundAxillary lymph node (ALN) staging is essential in predicting the clinical outcome of breast cancer (BC) patients. Traditionally, it follows the tumor-node-metastasis (TNM) staging, but its accuracy needs further improvement.

methodsA total of 9,616 BC patients from the Surveillance, Epidemiology, and End Results (SEER) database and 675 patients from the First Affiliated Hospital of China Medical University underwent mastectomy together with ALN dissection were reviewed. Univariate and multivariate logistic analyses were conducted to find the most meaningful factors relevant to prognosis.

resultsAfter univariate and multivariate analyses, age, race, primary site, radiation, chemotherapy, grade, T-stage, estrogen receptor (ER), progesterone receptor (PR), total number of positive lymph nodes (pN), positive lymph node ratio (LNR) and log odds of positive LNs (LODDS) were found to be significantly associated with overall survival (OS). Using these non-LN risk factors, we further compared the efficacy of three different ALN staging methods in prognosis via nomograms. Harrell's concordance index (C-index) and Akaike Information Criterion (AIC) were used to measure nomogram performance of the ALN staging methods: pN: C-index=0.687 (95% CI: 0.678-0.696), AIC =61,398.24; LNR: C-index =0.691 (95% CI: 0.683-0.701), AIC =61,313.56; and LODDS: C-index =0.691 (95% CI: 0.682-0.700), AIC =61,315.60. We found that the nomogram incorporating LODDS had better predictive ability compared with other two methods. Furthermore, an external validation revealed a C-index of 0.753 (95% CI: 0.690-0.816) for the Asian population, which indicates the nomogram based on LODDS may have universality for both Western and Asian populations.

conclusionsCompared with pN and LNR, LODDS showed higher homeostasis in LN evaluation, and showed marked efficacy in evaluating survival differences among patients with negative LN staging. We constructed a BC prognosis model by incorporating highly relevant clinical pathological factors and a new method of LN staging, which may greatly aid in guiding postoperative treatment.