Survival outcome assessment for triple-negative breast cancer: a nomogram analysis based on integrated clinicopathological, sonographic, and mammographic characteristics.

OBJECTIVE: This study aimed to incorporate clinicopathological, sonographic, and mammographic characteristics to construct and validate a nomogram model for predicting disease-free survival (DFS) in patients with triple-negative breast cancer (TNBC). METHODS: Patients diagnosed with TNBC at our institution between 2011 and 2015 were retrospectively evaluated. A nomogram model was generated based on clinicopathological, sonographic, and mammographic variables that were associated with 1-, 3-, and 5-year DFS determined by multivariate logistic regression analysis in the training set. The nomogram model was validated according to the concordance index (C-index) and calibration curves in the validation set. RESULTS: A total of 636 TNBC patients were enrolled and divided into training cohort (n = 446) and validation cohort (n = 190). Clinical factors including tumor size > 2 cm, axillary dissection, presence of LVI, and sonographic features such as angular/spiculated margins, posterior acoustic shadows, and presence of suspicious lymph nodes on preoperative US showed a tendency towards worse DFS. The multivariate analysis showed that no adjuvant chemotherapy (HR = 6.7, 95% CI: 2.6, 17.5, p < 0.0005), higher axillary tumor burden (HR = 2.7, 95% CI: 1.0, 7.1, p = 0.045), and ≥ 3 malignant features on ultrasound (HR = 2.4, CI: 1.1, 5.0, p = 0.021) were identified as independent prognostic factors associated with poorer DFS outcomes. In the nomogram, the C-index was 0.693 for the training cohort and 0.694 for the validation cohort. The calibration plots also exhibited excellent consistency between the nomogram-predicted and actual survival probabilities in both the training and validation cohorts. CONCLUSIONS: Clinical variables and sonographic features were correlated with the prognosis of TNBCs. The nomogram model based on three variables including no adjuvant chemotherapy, higher axillary tumor load, and more malignant sonographic features showed good predictive performance for poor survival outcomes of TNBC. KEY POINTS: • The absence of adjuvant chemotherapy, heavy axillary tumor load, and malignant-like sonographic features can predict DFS in patients with TNBC. • Mammographic features of TNBC could not predict the survival outcomes of patients with TNBC. • The nomogram integrating clinicopathological and sonographic characteristics is a reliable predictive model for the prognostic outcome of TNBC.

Quantitative shear wave elastography for noninvasive assessment of solid pancreatic masses.

PURPOSE: To evaluate the diagnostic value of quantitative shear wave elastography (SWE) for the differential diagnosis of solid pancreatic tumors. MATERIALS AND METHODS: A total of 66 solid pancreatic masses were enrolled in this study and all the lesions underwent quantitative SWE. The stiffness of the masses was expressed in shear wave velocity (SWV, m/s). The receiver operating characteristic (ROC) curve was plotted to assess the diagnostic performance of quantitative SWE. The optimal cutoff value for SWV in the differentiation of benign from malignant masses was determined. RESULTS: The final diagnoses were 26 benign and 40 malignant masses. The SWVs were statistically higher for pancreatic malignant masses compared with those for benign masses (3.30±1.22 m/s versus 1.31±0.64 m/s; P < 0.001). The area under the curve (AUC, 0.93) was obtained. When the best cut-off point was 1.77 m/s, the accuracy, sensitivity, and specificity were 92.4%, 90.0%, and 96.2%, respectively. CONCLUSIONS: Quantitative SWE is a novel technique that can be considered as a quantitative and objective diagnostic tool for prediction of pancreas malignancy.