Development and validation of a nomogram model based on pretreatment ultrasound and contrast-enhanced ultrasound to predict the efficacy of neoadjuvant chemotherapy in patients with borderline resectable or locally advanced pancreatic cancer

作者：Xiaoyi Yan, Xian-Shui Fu, Yang Gui, Xueqi Chen, Yuejuan Cheng, Menghua Dai, Weibin Wang, Mengsu Xiao, Li Tan, Jing Zhang, Yuming Shao, Huanyu Wang, Xiaoyan Chang, Ke Lv · 发表于：Cancer Imaging · 年份：2024 · DOI：10.1186/s40644-024-00662-2 · 被引用次数：6 · 研究领域：Pancreatic and Hepatic Oncology Research、Lung Cancer Diagnosis and Treatment、Lung Cancer Research Studies

OBJECTIVES: To develop a nomogram using pretreatment ultrasound (US) and contrast-enhanced ultrasound (CEUS) to predict the clinical response of neoadjuvant chemotherapy (NAC) in patients with borderline resectable pancreatic cancer (BRPC) or locally advanced pancreatic cancer (LAPC). METHODS: A total of 111 patients with pancreatic ductal adenocarcinoma (PDAC) treated with NAC between October 2017 and February 2022 were retrospectively enrolled. The patients were randomly divided (7:3) into training and validation cohorts. The pretreatment US and CEUS features were reviewed. Univariate and multivariate logistic regression analyses were used to determine the independent predictors of clinical response in the training cohort. Then a prediction nomogram model based on the independent predictors was constructed. The area under the curve (AUC), calibration plot, C-index and decision curve analysis (DCA) were used to assess the nomogram's performance, calibration, discrimination and clinical benefit. RESULTS: (OR:1.51; p = 0.03) were independent predictors of clinical response to NAC. The predictive nomogram developed based on the above imaging features showed AUCs were 0.852 and 0.854 in the primary and validation cohorts, respectively. Good calibration was achieved in the training datasets, with C-index of 0.852. DCA verified the clinical usefulness of the nomogram. CONCLUSIONS: The nomogram based on pretreatment US and CEUS can effectively predict the clinical response of NAC i...