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Prognostic and incremental value of computed tomography-based radiomics from tumor and nodal regions in esophageal squamous cell carcinoma

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收录情况: ◇ SCIE ◇ 统计源期刊 ◇ CSCD-C ◇ 卓越:梯队期刊

机构: [1]Radiation Oncology Key Laboratory of Sichuan Province, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu 610041, China [2]Department of Biobank, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu 610041, China [3]Department of Thoracic Surgery, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu 610041, China [4]Department of Medical Imaging, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu 610041, China [5]Department of Radiation Oncology, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu 610041, China
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关键词: Esophageal squamous cell cancer radiomics lymph node prognosis

摘要:
Objective: This study aimed to evaluate the prognostic value of preoperative radiomics and establish an integrated model for esophageal squamous cell cancer (ESCC). Methods: A total of 931 patients were retrospectively enrolled in this study (training cohort, n=624; validation cohort, n=307). Radiomics features were obtained by contrast-enhanced computed tomography (CT) before esophagectomy. A radiomics index was set based on features of tumor and reginal lymph nodes by using the least absolute shrinkage and selection operator (LASSO) Cox regression. Prognostic nomogram was built based on radiomics index and other independent risk factors. The prognostic value was assessed by using Harrell's concordance index, time-dependent receiver operating characteristics and Kaplan-Meier curves. Results: Twelve radiomic features from tumor and lymph node regions were identified to build a radiomics index, which was significantly associated with overall survival (OS) in both training cohort and validation cohort. The radiomics index was highly correlated with clinical tumor-node-metastasis (cTNM) and pathologic TNM (pTNM) stages, but it demonstrated a better prognostic value compared with cTNM stage and was almost comparable with pTNM stage. Multivariable Cox regression showed that the radiomics index was an independent prognostic factor. An integrated model was constructed based on gender, preoperative serum sodium concentration, pTNM and the radiomics index for clinical usefulness. The integrated model demonstrated discriminatory ability better compared with the traditional clinical-pathologic model and pTNM alone, indicating incremental value for prognosis. Conclusions: CT-based radiomics for primary tumor and reginal lymph nodes was sufficient in predicting OS for patients with ESCC. The integrated model demonstrated incremental value for prognosis and was robust for clinical applications.

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基金编号: 22NSFSC1483 2019YFS0378 2018JY0277 Y-2019Genecast-041

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出版当年[2022]版:
大类 | 3 区 医学
小类 | 3 区 肿瘤学
最新[2023]版:
大类 | 2 区 医学
小类 | 3 区 肿瘤学
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出版当年[2022]版:
Q2 ONCOLOGY
最新[2023]版:
Q1 ONCOLOGY

影响因子: 最新[2023版] 最新五年平均 出版当年[2022版] 出版当年五年平均 出版前一年[2021版] 出版后一年[2023版]

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第一作者机构: [1]Radiation Oncology Key Laboratory of Sichuan Province, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu 610041, China [2]Department of Biobank, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu 610041, China
通讯作者:
通讯机构: [1]Radiation Oncology Key Laboratory of Sichuan Province, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu 610041, China [3]Department of Thoracic Surgery, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu 610041, China [5]Department of Radiation Oncology, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu 610041, China [*1]Radiation Oncology Key Laboratory of Sichuan Province, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu 610041, China [*2]Department of Thoracic Surgery, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu 610041, China
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