Establishment and validation of an ultrasound‐based nomogram with risk stratification for short disease‐free survival in breast cancer

Purpose This retrospective study aimed to develop and validate an Ultrasound (US)‐based nomogram to predict short disease‐free survival (short‐DFS, less than 120 months DFS) in breast cancer (BC). Methods Nomogram was established based on a training data of 311 BC patients by multivariable logistic regression, and were assessed by discrimination, calibration, and clinical usefulness. Risk stratification was performed by X‐tile. An independent testing data of 200 patients with BC was used for external validation. Results Nine predictors including three US features and six clinical parameters were screened into the nomogram by Lasso (log λ = −3.594) in training data. Better performance was obtained in the training data (C‐index: 0.942) and testing data (C‐index: 0.914). Calibration analysis indicated optimal agreement between nomogram predictions and actual observations (p = 0.67). Decision curve analysis showed a great clinical benefit (Youden index: 0.634). Three risk levels are low‐risk (345.3). Our nomograms had larger area under the receiver operating characteristic (ROC) curves compared with Magee Equation and Nottingham Prognostic models (0.942 vs. 0.824, 0.790). Conclusion The US‐based nomogram and the practical score system facilitate individualized prediction of short‐DFS to optimize clinical decisions and improve prognosis in patients with BC. A nomogram was established based on ultrasound features of breast cancer in training data, which can predict short disease‐free survival (less than 120 months DFS) of breast cancer, and showed good performance by discrimination, calibration, and clinical usefulness in an independent testing data.