Hwang KT, et al. J Breast Cancer. 2019 Jul;22:e55. https://doi.org/10.4048/jbc.2019.22.e55

Background: To investigate the influence of metabolic syndrome and its components on the risk of breast cancer. Methods: Retrospective nationwide cohort study analyzing data of 13,377,349 women older than 19 years from Korean National Health Insurance Service was performed. Cox proportional hazards model was used to calculate HR and 95% confidence interval (CI) of breast cancer risk. Results: The presence of metabolic syndrome decreased the risk of all breast cancer types in all subjects (HR, 0.954; 95% CI, 0.939–0.970). In women with age ≤50 years, metabolic syndrome decreased the risk of all breast cancer types, with similar findings for all subject groups (HR, 0.915; 95% CI, 0.892–0.939). In women with age >50 years, metabolic syndrome increased the risk of all breast cancer types (HR, 1.146; 95% CI, 1.123–1.170), especially in age groups of more than 55 years. In women with age >50 years, HRs increased as the number of metabolic syndrome components increased, while HRs decreased as the number of metabolic syndrome components increased in women with age ≤50 years. Conclusions: The presence of metabolic syndrome increased the risk of breast cancers in postmenopausal women, but decreased the risk in premenopausal women. Every metabolic syndrome component played similar roles on the risk of breast cancer as metabolic syndrome, and their effects became stronger when the number of components increased. Impact: Metabolic syndrome is associated with the risk of breast cancer having different effect according to age groups.

The Z0011 trial demonstrated that axillary lymph node dissection (ALND) could be omitted in spite of 1–2 metastatic sentinel lymph nodes. This study aimed to validate the results on a population-based database. The Surveillance, Epidemiology, and End Results (SEER) database was searched for patients comparable to the Z0011 participants. The type of axillary surgery was estimated using the total number of examined axillary lymph nodes (ALNs). Breast cancer-specific mortality (BCSM) was compared between patients with ≥10 ALNs (the sentinel lymph node dissection (SLND) and ALND group, or “SLND + ALND group”) and patients with one or two ALNs (the “SLND group”). During 2010–2015, the SEER database included 7077 and 6620 patients categorized in the SLND group and the SLND + ALND group, respectively. Death was observed for 515 patients (7.3%) in the SLND group and 589 patients (8.9%) in the SLND + ALND group based on a median follow-up of 41 months. After propensity-score matching, the adjusted hazard ratio for BCSM in the SLND group (vs. the SLND + ALND group) was 1.038 (95% confidence interval: 0.798–1.350). Regardless of the SLND criteria, the outcomes were not significantly different between the two groups. This retrospective cohort study of Z0011-comparable patients revealed that ALND could be omitted based on the Z0011 strategy, even among patients with ≤2 dissected ALNs.

Regarding TNM staging in breast cancer, T2 category is currently not divided into subcategories even though it covers a wider range of tumor sizes than T1 category. Using Korean Breast Cancer Registry database, data of 41 071 women diagnosed as non‐metastatic T2 breast cancer between 2001 and 2014 were analyzed. Cutoff value for optimal tumor size was approximated by receiver operating characteristic (ROC) curve to subcategorize T2 tumors. Overall survival (OS) was compared between two subcategories. Median follow‐up period was 65 months. Of 41 071 patients, 4504 (11.0%) died. Based on ROC curve analysis, 3.0 cm was selected as the cutoff value. Five‐year OS rate was 91% in patients with breast tumors ≤3.0 cm (T2a) and 86% in patients with breast tumors >3.0 cm (T2b) (log‐rank P < 0.001). T2b subcategory showed worse OS than T2a subcategory regardless of node status (log‐rank P < 0.001 for all node categories). Within every subgroup defined by primary OS analysis covariates, T2b subcategory consistently showed worse outcome compared to T2a subcategory. By multivariate analysis, T2b subcategory was a significant independent prognostic factor of OS (hazard ratio: 1.26, 95% CI = 1.18‐1.34). T2 category of breast cancer could be subcategorized into T2a and T2b with a cutoff value of 3 cm. These subcategories definitely showed different OSs even after adjusted for known prognostic factors. Subcategorization of T2 category might be useful for predicting prognosis more accurately and tailoring adjuvant therapy.