1. Development and validation of a radiomics-based model to predict local progression-free survival after chemo-radiotherapy in patients with esophageal squamous cell cancer
- Author
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He-San Luo, Ying-Ying Chen, Wei-Zhen Huang, Sheng-Xi Wu, Shao-Fu Huang, Hong-Yao Xu, Ren-Liang Xue, Ze-Sen Du, Xu-Yuan Li, Lian-Xin Lin, and He-Cheng Huang
- Subjects
Chemo-radiotherapy ,Esophageal squamous cell cancer ,Radiomics ,LPFS ,Nomogram ,Medical physics. Medical radiology. Nuclear medicine ,R895-920 ,Neoplasms. Tumors. Oncology. Including cancer and carcinogens ,RC254-282 - Abstract
Abstract Purpose To develop a nomogram model for predicting local progress-free survival (LPFS) in esophageal squamous cell carcinoma (ESCC) patients treated with concurrent chemo-radiotherapy (CCRT). Methods We collected the clinical data of ESCC patients treated with CCRT in our hospital. Eligible patients were randomly divided into training cohort and validation cohort. The least absolute shrinkage and selection operator (LASSO) with COX regression was performed to select optimal radiomic features to calculate Rad-score for predicting LPFS in the training cohort. The univariate and multivariate analyses were performed to identify the predictive clinical factors for developing a nomogram model. The C-index was used to assess the performance of the predictive model and calibration curve was used to evaluate the accuracy. Results A total of 221 ESCC patients were included in our study, with 155 patients in training cohort and 66 patients in validation cohort. Seventeen radiomic features were selected by LASSO COX regression analysis to calculate Rad-score for predicting LPFS. The patients with a Rad-score ≥ 0.1411 had high risk of local recurrence, and those with a Rad-score
- Published
- 2021
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