A Clinical-Ultrasound Predictive Model for Upstaging Risk in DCIS: An Exploratory Tool for Active Surveillance Trial Enrollment.

OBJECTIVE: This exploratory study aimed to develop a practical prediction model using clinical and sonographic features to identify patients with biopsy-proven ductal carcinoma in situ (DCIS) who are at low risk of pathological upstaging, with the goal of informing patient selection for DCIS active surveillance trial enrollment. METHODS: We retrospectively analyzed patients with DCIS diagnosed by core needle biopsy who underwent surgery at the National Cancer Center between February 2019 and December 2024. Clinical data and sonographic features were collected, along with selected mammographic and MRI variables for exploratory analysis. A predictive model was constructed by using multivariable logistic regression. RESULTS: We identified 224 patients diagnosed with DCIS through biopsy, including 96 pure DCIS cases (42.9%) and 128 DCIS cases with microinvasion (28.1%) or invasive carcinoma (29.0%) on final pathology. Multivariate analysis identified sonographic size (odds ratio [OR] 2.363, p = 0.02), palpable mass (OR 2.675, p = 0.02), non-parallel growth orientation on ultrasound (OR 4.449, p < 0.001), vascularity (Adler grade II-III) (OR 2.357, p = 0.014) and sonographically detected axillary lymphadenopathy (OR 5.262, p = 0.002) as independent predictors of upstaging. The predictive model constructed from these five variables achieved an area under the curve of 0.784 (95% confidence interval: 0.723-0.845) with overall accuracy of 72.3%. CONCLUSION: The proposed model based on routine clinical and sonographic features provided reasonable discrimination for upstaging risk in patients with biopsy-proven DCIS. It may serve as a useful exploratory reference for refining patient selection in active surveillance trial design.