ObjectiveThe study was aimed to further explore risk factors of axillary lymph node metastasis in Luminal A breast cancer and revealed high-risk clinicopathological features.MethodsFrom January 2017 to December 2019, the clinical and pathological data of 237 Luminal A breast cancer patients diagnosed in our hospital were retrospectively analyzed. For the identification of related risk factors of axillary lymph node metastasis in Luminal A breast cancer, χ2 test for univariate analysis and logistic regression model for multivariate analysis were conducted.ResultsAmong the 237 patients with Luminal A breast cancer, 115 patients were associated with lymph node metastasis (48.5%). The univariate analysis indicated that multifocal tumor (P=0.001), p53 mutation (P=0.012), and lymphovascular invasion (P=0.022) were correlated with axillary lymph node metastasis in the Luminal A breast cancer. The multivariate analysis identically showed that multifocal tumor (P=0.009), p53 mutation (P=0.019), and lymphovascular invasion (P=0.021) were independent risk factors of axillary lymph node metastasis.ConclusionMultifocal breast cancer, p53 mutation, and lymphovascular invasion are risk factors of axillary lymph node metastasis in Luminal A breast cancer.
Objective To analyze the correlation among the clinicopathologic features, ultrasound imaging features, and axillary lymph node metastasis in breast cancer patients with negative clinical evaluation of axillary lymph nodes (cN0), and to establish a logistic regression model to predict axillary lymph node metastasis, so as to provide a reference for more accurate evaluation of axillary lymph node status in cN0 breast cancer patients. Methods The data of 501 female patients with cN0 breast cancer who were hospitalized and operated in the Affiliated Hospital of Wuhan University of Science and Technology (Xiaogan Central Hospital) from December 2013 to October 2020 were collected. Among them, 376 patients from December 2013 to December 2019 were selected to establish a prediction model for axillary lymph node metastasis of cN0 breast cancer. In the modeling group, the basic information, clinical pathological characteristics, and ultrasound imaging features of patients were analyzed by single factor analysis. The factors with statistical significance were included in the multivariate logistic regression analysis, and the logistic regression prediction model was established. The model was evaluated by the correction curve and Hosmer-Lemeshow test goodness of fit. The model was validated in the validation group (125 patients from January to October 2020), and the receiver operation characteristic (ROC) curve was drawn. Results The probability of positive axillary lymph nodes in 501 patients with cN0 breast cancer was 28.14% (141/501). The univariate analysis results of the modeling group showed that the histological grade, vascular invasion, progesterone receptor (PR), Ki-67, age, molecular typing, ultrasound breast imaging-reporting and data system (BI-RADS) grade were associated with axillary lymph node metastasis. Multivariate logistic regression analysis showed that the vascular infiltration, positive estrogen receptor (ER) , ultrasound BI-RADS grade 4C and Ki-67≥14% increased the probability of axillary lymph node metastasis (P<0.05). Using the above prediction factors to establish the prediction nomogram, the area under the ROC curve (AUC) of the modeling group was 0.72 [95%CI (0.66, 0.78)], the cut-off value was 0.30, the sensitivity was 61.00%, and the specificity was 71.20%. The newly established axillary lymph node transfer logistic regression model was applied to the validation group (n=125), and the AUC was 0.72 [95%CI (0.53, 0.76)]. The truncation value was 0.40, and the total coincidence rate was 69.60% (87/125), positive predictive value was 47.37% (18/38), and negative predictive value was 91.95% (80/87). Conclusions Vascular invasion, positive ER , ultrasound BI-RADS grade 4C, and Ki-67≥14% are risk predictors of axillary lymph node metastasis in cN0 breast cancer patients. The negative predictive value of the model is 91.95%, which has a higher value in predicting axillary lymph node metastasis in early breast cancer patients, and can provide a reference for screening exempt sentinel lymph node biopsy population.
Objective To investigate the effect of radiotherapy after neoadjuvant chemotherapy and modified radical surgery on breast cancer specific survival (BCSS) of patients with stage cT1–2N1M0 breast cancer. Methods A total of 917 cT1–2N1M0 stage breast cancer patients treated with neoadjuvant chemotherapy and modified radical surgery from 2010 to 2017 were extracted from the The Surveillance, Epidemiology, and End Results (SEER) database. Of them 720 matched patients were divided into radiotherapy group (n=360) and non-radiotherapy group (n=360) by using propensity score matching (PSM). Cox proportional hazard regression model was used to explore the factors affecting BCSS. Results Patients were all interviewed for a median follow-up of 65 months, and the 5-year BCSS was 91.9% in the radiotherapy group and 93.2% in the non-radiotherapy group, there was no significant difference between the 2 groups (χ2=0.292, P=0.589). The results were the same in patients with no axillary lymph node metastasis, one axillary lymphnode metastasis, two axillary lymph node metastasis and 3 axillary lymph node metastasis group (χ2=0.139, P=0.709; χ2=0.578, P=0.447; χ2=2.617, P=0.106; χ2=0.062, P=0.803). The result of Cox proportional hazard regression analysis showed that, after controlling for Grade grade, time from diagnosis to treatment, efficacy of neoadjuvant chemotherapy, number of positive axillary lymph nodes, molecular typing, and tumor diameter at first diagnosis, radiotherapy had no statistically significant effect on BCSS [HR=1.048, 95%CI (0.704, 1.561), P=0.817]. Conclusions The effect of radiotherapy on the BCSS of patients with stage cT1–2N1M0 breast cancer who have received neoadjuvant chemotherapy and modified radical surgery with 0 to 3 axillary lymph nodes metastases is limited, but whether to undergo radiotherapy should still be determined according to the comprehensive risk of individual tumor patients.