Construction and Validation of Nomogram Based on Contrast-enhanced Ultrasound for Predicting Platinum Chemotherapy Sensitivity in Breast Cancer Patients

Aiping CAO; Mei WANG; Xiaoshuang LI

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Aiping CAO, Mei WANG, Xiaoshuang LI. Construction and Validation of Nomogram Based on Contrast-enhanced Ultrasound for Predicting Platinum Chemotherapy Sensitivity in Breast Cancer Patients[J]. Journal of Kunming Medical University.

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Construction and Validation of Nomogram Based on Contrast-enhanced Ultrasound for Predicting Platinum Chemotherapy Sensitivity in Breast Cancer Patients

Department of Ultrasound Medicine，Guangyuan Central Hospital，Guangyuan Sichuan 628000，China

Received Date: 2026-03-18

Abstract

Abstract

Objective To explore the predictive value of a nomogram model based on quantitative parameters from contrast-enhanced ultrasound （CEUS） for platinum-based chemotherapy sensitivity in breast cancer patients, providing clinical reference for treatment decisions. Methods A prospective study enrolled 275 breast cancer patients treated at Guangyuan Central Hospital from January 2021 to December 2024 as the modeling cohort, with 118 breast cancer patients from January to July 2025 selected at a 7:3 ratio as the temporal validation cohort. All patients received platinum-based chemotherapy and were stratified based on achievement of pathologic complete response （pCR） following chemotherapy into platinum-resistant group （without pCR, n = 94） and platinum-sensitive group （with pCR, n = 181）. Multivariate logistic regression was used to analyze the influencing factors of platinum-based chemotherapy sensitivity in breast cancer patients, and a nomogram prediction model was constructed. The discrimination, consistency and clinical practicability of the nomogram model were evaluated by receiver operating characteristic （ROC） curve, calibration curve and decision curve （DCA）. Results Clinical characteristics showed no significant differences between the modeling and temporal validation cohorts（P > 0.05）. In the modeling cohort, significant differences were observed between the two groups in molecular subtype, ER expression, Ki-67 expression, blood flow signal grade, lymph node status, peak time （TTP）, arrival time （AT）, and wash-in rate （WiR）（P < 0.05）. Multivariate Logistic regression analysis showed that molecular subtype, ER expression, Ki-67 expression, lymph node status, TTP, AT and WiR were all independent influencing factors for platinum chemotherapy resistance in breast cancer patients （P < 0.05）. Based on the results of Logistic regression analysis, a nomogram prediction model was constructed. ROC curve showed that the nomogram model for predicting platinum-based chemotherapy resistance had an area under the curve （AUC） of 0.886 （95%CI: 0.826-0.946）in the modeling cohort with sensitivity of 92.55% and specificity of 88.95%, and an AUC of 0.830 （95% CI: 0.780-0.880） in the temporal validation cohort with sensitivity of 91.43% and specificity of 86.75%, demonstrating good discrimination. The Hosmer-Lemeshow goodness-of-fit test showed P > 0.05, with Brier scores of 0.122 and 0.141 for calibration curves in the modeling and temporal validation cohorts, respectively. The DCA curve suggests that when the threshold probability ranges from 40% to 80%, using this nomogram model for clinical decision-making provides higher net benefit compared to "treat all" or "treat none" strategies, demonstrating good clinical utility. Conclusion A nomogram model integrating molecular subtype, ER, Ki-67, lymph node status, and CEUS quantitative parameters （TTP, AT, WiR） demonstrates good predictive efficacy for platinum-based chemotherapy resistance risk in breast cancer patients, facilitating individualized clinical treatment decisions.
- Breast cancer,
- Contrast-enhanced ultrasound,
- Nomogram model,
- Chemotherapy,
- Platinum sensitive,
- Platinum resistance

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References(28)

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