Clinical radiology · 2026
Prediction of recurrence-free survival in patients with invasive ductal carcinoma of the breast on the basis of clinicopathological, conventional ultrasound and contrast-enhanced ultrasound imaging characteristics.
СтатьяПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод в очереди
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Kuang Y, Zheng Y, Li G, Du Y, Jia C, Wu T, Diao X, Wu R
Аннотация
AIM: This study aimed to incorporate clinicopathological, conventional ultrasound (US) and contrast-enhanced US (CEUS) imaging features to establish a predictive model for evaluating recurrence-free survival (RFS) in patients with invasive ductal carcinoma (IDC) of the breast.
MATERIALS AND METHODS: Patients confirmed with IDC in our hospital between 2016 and 2020 were retrospectively analysed. We performed Cox regression analyses based on the clinicopathological and USdata to identify independent factors. A nomogram model was constructed and verified to predict the 1-, 3-, and 5-year RFS. Nomogram performance, calibration, and clinical applicability were evaluated with the area under the receiver operating characteristic curve (AUC), calibration curves, and decision curve analysis.
RESULTS: A total of 377 patients were included and divided into training group (n=226) and validation group (n=151). Axillary lymph node burden, oestrogen receptor status, colour Doppler flow imaging blood flow, maximum length diameter on CEUS, and perfusion defects were independent risk factors for poor RFS. The AUC values of nomogram model were 0.876, 0.823, and 0.753 in the training group and 0.731, 0.763, and 0.714 in the validation group. The calibration curves exhibited good concordance between the predicted survival probabilities and the actual values.
CONCLUSION: The nomogram, which integrates clinicopathological and US features, serves as a supplementary prognostic tool for IDC patients. It offers individualised risk stratification to support clinical decision-making, potentially minimising interventions for low-risk patients and prioritising monitoring for high-risk cases, while complementing traditional staging systems.
MATERIALS AND METHODS: Patients confirmed with IDC in our hospital between 2016 and 2020 were retrospectively analysed. We performed Cox regression analyses based on the clinicopathological and USdata to identify independent factors. A nomogram model was constructed and verified to predict the 1-, 3-, and 5-year RFS. Nomogram performance, calibration, and clinical applicability were evaluated with the area under the receiver operating characteristic curve (AUC), calibration curves, and decision curve analysis.
RESULTS: A total of 377 patients were included and divided into training group (n=226) and validation group (n=151). Axillary lymph node burden, oestrogen receptor status, colour Doppler flow imaging blood flow, maximum length diameter on CEUS, and perfusion defects were independent risk factors for poor RFS. The AUC values of nomogram model were 0.876, 0.823, and 0.753 in the training group and 0.731, 0.763, and 0.714 in the validation group. The calibration curves exhibited good concordance between the predicted survival probabilities and the actual values.
CONCLUSION: The nomogram, which integrates clinicopathological and US features, serves as a supplementary prognostic tool for IDC patients. It offers individualised risk stratification to support clinical decision-making, potentially minimising interventions for low-risk patients and prioritising monitoring for high-risk cases, while complementing traditional staging systems.