Clinical-Radiomic Analysis for Pretreatment Prediction of Objective Response to First Transarterial Chemoembolization in Hepatocellular Carcinoma
العنوان: | Clinical-Radiomic Analysis for Pretreatment Prediction of Objective Response to First Transarterial Chemoembolization in Hepatocellular Carcinoma |
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المؤلفون: | Jiahao Hu, Jiasheng Cao, Pil Soo Sung, Masatoshi Kudo, Jian Lin, Xiujun Cai, Jennifer Y. Wu, Win Topatana, Amedeo Amedei, Jiliang Shen, Shijie Li, Mingyu Chen, Victor M. Zaydfudim, Christine Pocha, Chenhao Tong, Franco Trevisani, Bin Zhang, Sarun Juengpanich, Tatsuo Kanda |
المساهمون: | Chen M., Cao J., Hu J., Topatana W., Li S., Juengpanich S., Lin J., Tong C., Shen J., Zhang B., Wu J., Pocha C., Kudo M., Amedei A., Trevisani F., Sung P.S., Zaydfudim V.M., Kanda T., Cai X. |
المصدر: | Liver Cancer, Vol 10, Iss 1, Pp 38-51 (2021) Liver Cancer |
بيانات النشر: | S. Karger AG, 2021. |
سنة النشر: | 2021 |
مصطلحات موضوعية: | Oncology, medicine.medical_specialty, Hepatocellular carcinoma, Treatment response, Logistic regression, lcsh:RC254-282, Transarterial chemoembolization, 03 medical and health sciences, 0302 clinical medicine, Internal medicine, medicine, Stage (cooking), Original Paper, Hepatology, Receiver operating characteristic, business.industry, Hazard ratio, Retrospective cohort study, lcsh:Neoplasms. Tumors. Oncology. Including cancer and carcinogens, medicine.disease, Confidence interval, radiomics, 030220 oncology & carcinogenesis, 030211 gastroenterology & hepatology, Radiomic, business, Liver cancer |
الوصف: | Background: The preoperative selection of patients with intermediate-stage hepatocellular carcinoma (HCC) who are likely to have an objective response to first transarterial chemoembolization (TACE) remains challenging. Objective: To develop and validate a clinical-radiomic model (CR model) for preoperatively predicting treatment response to first TACE in patients with intermediate-stage HCC. Methods: A total of 595 patients with intermediate-stage HCC were included in this retrospective study. A tumoral and peritumoral (10 mm) radiomic signature (TPR-signature) was constructed based on 3,404 radiomic features from 4 regions of interest. A predictive CR model based on TPR-signature and clinical factors was developed using multivariate logistic regression. Calibration curves and area under the receiver operating characteristic curves (AUCs) were used to evaluate the model’s performance. Results: The final CR model consisted of 5 independent predictors, including TPR-signature (p < 0.001), AFP (p = 0.004), Barcelona Clinic Liver Cancer System Stage B (BCLC B) subclassification (p = 0.01), tumor location (p = 0.039), and arterial hyperenhancement (p = 0.050). The internal and external validation results demonstrated the high-performance level of this model, with internal and external AUCs of 0.94 and 0.90, respectively. In addition, the predicted objective response via the CR model was associated with improved survival in the external validation cohort (hazard ratio: 2.43; 95% confidence interval: 1.60–3.69; p < 0.001). The predicted treatment response also allowed for significant discrimination between the Kaplan-Meier curves of each BCLC B subclassification. Conclusions: The CR model had an excellent performance in predicting the first TACE response in patients with intermediate-stage HCC and could provide a robust predictive tool to assist with the selection of patients for TACE. |
وصف الملف: | ELETTRONICO |
تدمد: | 1664-5553 2235-1795 |
URL الوصول: | https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fc16eb0c50c2dcfe5771062d07dbc6a5 https://doi.org/10.1159/000512028 |
حقوق: | OPEN |
رقم الأكسشن: | edsair.doi.dedup.....fc16eb0c50c2dcfe5771062d07dbc6a5 |
قاعدة البيانات: | OpenAIRE |
تدمد: | 16645553 22351795 |
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