1. A nomogram based on CT texture features to predict the response of patients with advanced pancreatic cancer treated with chemotherapy
- Author
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Jingjing Li, Jiadi Du, Yuying Li, Mingzhu Meng, Junjie Hang, and Haifeng Shi
- Subjects
CT texture features ,Advanced pancreatic cancer ,Treatment response ,Nomogram ,Radiomics signature ,Diseases of the digestive system. Gastroenterology ,RC799-869 - Abstract
Abstract Objective This study aimed to evaluate the predictive value of computed tomography (CT) texture features in the treatment response of patients with advanced pancreatic cancer (APC) receiving palliative chemotherapy. Methods This study enrolled 84 patients with APC treated with first-line chemotherapy and conducted texture analysis on primary pancreatic tumors. 59 patients and 25 were randomly assigned to the training and validation cohorts at a ratio of 7:3. The treatment response to chemotherapy was evaluated according to the Response Evaluation Criteria in Solid Tumors (RECIST1.1). The patients were divided into progressive and non-progressive groups. The least absolute shrinkage selection operator (LASSO) was applied for feature selection in the training cohort and a radiomics signature (RS) was calculated. A nomogram was developed based on a multivariate logistic regression model incorporating the RS and carbohydrate antigen 19-9 (CA19-9), and was internally validated using the C-index and calibration plot. We performed the decision curve analysis (DCA) and clinical impact curve analysis to reflect the clinical utility of the nomogram. The nomogram was further externally confirmed in the validation cohort. Results The multivariate logistic regression analysis indicated that the RS and CA19-9 were independent predictors (P
- Published
- 2023
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