Development and Validation of a Radiomics-based Model to Predict Local Progression-free Survival After Chemo-radiotherapy in Patients With Esophageal Squamous Cell Cancer

Abstract

\n Purpose: To develop a nomogram model for predicting local progress-free survival (LPFS) in esophageal squamous cell carcinoma (ESCC) patients treated with chemoradiotherapy. 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 radiomics features calculating Rad-score for predicting LPFS in the training cohort. The univariate and multivariate analysis 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. After LASSO COX regression analysis, seventeen radiomics features were selected 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<0.1411 had low risk of local recurrence. Multivariate analysis showed that N stage, CR status and Rad-score were independent predictive factors for LPFS. A nomogram model was built based on the result of multivariate analysis. The C-index of the nomogram was 0.745 (95%CI: 0.7700 -0.790) in training cohort and 0.723(95%CI：0.654-0.791) in validation cohort. The 3-year LPFS rate predicted by the nomogram model was highly consistent with the actual 3-year LPFS rate both in the training cohort and the validation cohort.Conclusion: We developed and validated a prediction model based on radiomics features and clinical factors, which can be used to predict LPFS of patients after CCRT. This model is conducive to making individualized chemoradiotherapy strategy and providing scientific basis for subsequent intensive adjuvant therapy for ESCC patients.