Ultrasound-based comparative analysis and nomogram development for predicting triple-negative and non-triple-negative breast cancer: a 4-year institutional study in Quanzhou First Hospital.

OBJECTIVE: The objective of this study was to compare ultrasound features and establish a predictive nomogram for distinguishing between triple-negative breast cancer (TNBC) and non-TNBC. DESIGN: A retrospective cohort study. SETTING: This study was conducted at Quanzhou First Hospital, a grade A tertiary hospital in Quanzhou, China, with the research data set covering the period from September 2019 to August 2023. PARTICIPANTS: The study included a total of 205 female patients with confirmed TNBC and 574 female patients with non-TNBC, who were randomly divided into a training set and a validation set at a ratio of 7:3. MAIN OUTCOME MEASURES: All patients underwent ultrasound examination and received a confirmatory pathological diagnosis. Nodules were classified according to the Breast Imaging-Reporting and Data System standard. Subsequently, the study conducted a comparative analysis of clinical characteristics and ultrasonic features. RESULTS: A statistically significant difference was observed in multiple clinical and ultrasonic features between TNBC and non-TNBC. Specifically, in the logistic regression analysis conducted on the training set, indicators such as posterior echo, lesion size, presence of clinical symptoms, margin characteristics, internal blood flow signals, halo and microcalcification were found to be statistically significant (p<0.05). These significant indicators were then effectively incorporated into a static and dynamic nomogram model, demonstrating high predictive performance in distinguishing TNBC from non-TNBC. CONCLUSION: The results of our study demonstrated that ultrasound features can be valuable in distinguishing between TNBC and non-TNBC. The presence of posterior echo, size, clinical symptoms, margin, internal flow, halo and microcalcification was identified as predictive factors for this differentiation. Microcalcification, hyperechoic halo, internal flow and clinical symptoms emerged as the strongest predictive factors, indicating their potential as reliable indicators for identifying TNBC and non-TNBC.

Effect, sensitivity, specificity and accuracy of ultrasonic assessment of axillary lymph node-negative breast cancer.

Objective: To investigate the diagnostic value of ultrasound for patients with axillary lymph node-negative breast cancer (ALNNBC). Methods: A retrospective analysis was performed on the clinical data of 204 breast cancer patients who were admitted by Quanzhou First Hospital Affiliated to Fujian Medical University between October 2020 and May 2022. According to the results of axillary lymph node (ALN) examination, the patients were assigned to a positive group(n=102) and a negative group(n=102). All patients underwent diagnosis with color Doppler ultrasound, with pathological diagnosis as the "gold standard" to determine the sensitivity and specificity of ultrasonic diagnosis. A receiver operating characteristic(ROC) curve was established to analyze the efficiency of ultrasonic diagnosis and compare the ultrasonographic features and flow grades between the two groups. Results: Differences were statistically significant between the two groups in ultrasonographic features of lesions(negative vs positive, all p<0.05), including morphological irregularity(59.8% vs 85.3%), spiky margins(19.6% vs 63.7%), posterior echo attenuation(19.6% vs 44.1%) and microcalcification(40.2% vs 55.89%). The negative group had a lower proportion of patients with grade 2-3 ultrasound blood flow when compared with the positive group(32.4% vs 56.86%), and the difference was statistically significant(p<0.05). Ultrasonic diagnosis of ALNNBC had a sensitivity of 88.24%(90/102), a specificity of 92.16%(94/102), a coincidence rate of 90.20% (184/204), a 95% CI of 0.845-0.928, and an AUC of 0.879. Conclusions: Ultrasonic diagnosis of ALNNBC is relatively efficient as ultrasonographic features and ultrasound blood flow signals can provide a scientific basis for the diagnosis of ALNNBC.

Development of a risk-stratification scoring system for predicting risk of breast cancer based on non-alcoholic fatty liver disease, non-alcoholic fatty pancreas disease, and uric acid.

Many breast cancer patients have both non-alcoholic fatty liver disease (NAFLD) and non-alcoholic fatty pancreas disease (NAFPD). Consequently, we hypothesized that NAFPD and NAFLD were associated with breast cancer, and aimed to build a novel risk-stratification scoring system based on it. In this study, a total of 961 patients with breast cancer and 1,006 non-cancer patients were recruited. The clinical characteristics were collected and analyzed using logistic analysis. Risk factors were assessed by a risk rating system. Univariate analysis showed that body mass index, triglyceride, total cholesterol, NAFLD, NAFPD, low-density lipoprotein, and uric acid (UA) were significantly related to breast cancer. Among them, NAFLD, NAFPD, and UA were independent risk factors related to breast cancer identified by multivariate analysis. The risk assessment model was established based on these factors and demonstrated that the odds ratio sharply increased with the rising scores. Compared with the low-risk group, the odds ratio in the intermediate- and high-risk groups were 1.662 (1.380-2.001) and 3.185 (2.145-4.728), respectively. In conclusion, the risk-stratification scoring system combining NAFLD, NAFPD, and UA can accurately predict the occurrence of breast cancer.