To investigate the prognostic factors of breast cancer brain metastasis（BCBM）, and to construct and validate a prediction model for prognosis of BCBM patients.

A case-control trial was designed and conducted in this study. A total of 1 133 BCBM patients were screened out from the Surveillance, Epidemiology, and End Results（SEER）database from 2016 to 2020, and were randomly assigned to a training set（n=793）and an internal validation set（n=340）at a ratio of 7∶3. The prognostic factors were determined with univariate and multivariate Cox regression analyses, and a nomogram prediction model was constructed. The discrimination, prediction and calibration of the nomograms were evaluated by C-index, receiver operating characteristic（ROC）curve and calibration curve. External validation of the nomogram prediction model was performed in 73 BCBM patients admitted to our hospital from 2004 to 2019.

Multivariate Cox regression analysis revealed that age, molecular type, surgery, radiotherapy, chemotherapy, lung metastasis and liver metastasis were identified as independent factors（P<0.05）, and a prediction model of the nomogram was thus established. The C-index of the SEER training set, internal validation set and external validation set were 0.720（95%CI: 0.674~0.766）, 0.705（95%CI: 0.633~0.777）and 0.667（95%CI: 0.610~0.724）, respectively. The ROC curve of the training set showed that our nomogram could accurately predict the survival rate of BCBM patients at 6 months（AUC=0.793）, and 1（AUC=0.759）and 2 years（AUC=0.724）. The predictive values of the calibration curve are in good agreement with the observed values.

Age, molecular type, surgery, radiotherapy, chemotherapy, and lung and liver metastases are independent prognostic factors of BCBM. Our constructed nomogram can effectively predict the 6-month, 1-year and 2-year survival probability of BCBM patients.

To investigate the associated factors of BRAF V600E gene mutation in patients classified as Bethesda I~V nodes by fine needle aspiration cytology (FNAC) but confirmed as papillary thyroid carcinoma (PTC) by postoperative histopathology.

A retrospective analysis was performed on the clinical data of the patients with FNAC classification of Bethesda I~V but confirmed by postoperative histopathology as PTC who were treated in our hospital from June 2020 to June 2021. According to the results of BRAF V600E gene test in preoperative puncture specimens, the patients were divided into mutation positive group and negative group. The clinical data were compared between the 2 groups, and the indicators associated with BRAF V600E gene mutation were analyzed.

Of the 127 enrolled patients, they were 27 males (21.26%) and 100 females (78.74%), with a mean age of 42.51 years (median age: 42 years). Eight-two patients (64.57%) harbored the BRAF V600E gene mutation, and 45 (35.43%) did not. Univariate analysis showed that there were significant differences in the capsular boundary, nodule morphology, abnormal cervical lymph nodes, TIRADS grade, FNAC class, and T-stage between the 2 groups (P<0.05). Multivariate logistic regression analysis indicated that capsular boundary and abnormal cervical lymph nodes were independent influencing factors of BRAF V600E gene mutation in these patients. ROC curve analysis suggested that the area under the curve (AUC) was 0.921 (95%CI: 0.876~0.967), with a sensitivity and specificity of 82.9% and 86.7%, respectively, when taking capsular boundary, nodule morphology, abnormal cervical lymph nodes and TIRADS grade combined together.

BRAF V600E gene mutation is associated with capsular boundary, nodule morphology, abnormal cervical lymph nodes on ultrasonogram, TIRADS grade, FNAC class, and T-stage in PTC patients. Among them, ultrasonographic indication of abnormal cervical lymph nodes and the boundary between nodules and capsule can be used to predict BRAF V600E gene mutation.

Ultrasound‑guided vacuum‐assisted excision (UGVAE) and breast biopsy are widely used for the diagnosis and treatment of both benign and suspicious breast lesions. In this retrospective study, we aimed to determine the safety of UGVAE for benign breast lesions and provide guidance for clinical practice.

We analyzed clinical and pathological data of female patients who had undergone UGVAE between January 2015 and December 2017 at our institution. All breast lesions were categorized according to the Breast Imaging Reporting and Data System (BI‐RADS) before performing UGVAE.

In our study cohort, UGVAE was used to resect 10,378 breast lesions from 5789 patients, and selected clinical and histopathological data were analyzed. The most common adverse events were postoperative bleeding (0.24%) and skin hypersensitivity (0.67%). The residual lesion rate was 2.27%. Fibroadenomas accounted for most of the benign lesions (7932 of 10,193; 77.82%). Breast cancer was diagnosed in 150 lesions from 128 patients. Multivariable binary logistic regression analyses showed that older age (odds ratio [OR] = 2.034, 95% confidence interval [CI]: 1.668–2.480, p < 0.001), higher BI‐RADS category (OR = 9.514, 95% CI: 6.790–13.332, p < 0.001), and larger legion size (OR = 1.048, 95% CI: 1.019–1.077, p = 0.001) were associated with an increased likelihood of breast cancer. Ninety‐six patients with breast cancer had undergone follow‐up treatment, achieving a 3‐year disease‐free survival rate of 97.2% and a 3‐year overall survival rate of 100%.

UGVAE is a safe and effective means of removing benign breast lesions, causing minimal postoperative trauma and fewer complications compared with open surgery. Moreover, UGVAE had little impact on the follow‐up treatment and survival of patients diagnosed with breast cancer.