Development of a prognostic nomogram and risk stratification system for upper thoracic esophageal squamous cell carcinoma

Yu Lin; Binglin Zheng; Junqiang Chen; Qiuyuan Huang; Yuling Ye; Yong Yang; Yuanmei Chen; Bijuan Chen; Mengxing You; Qifeng Wang; Yuanji Xu

doi:10.3389/fonc.2023.1059539

Development of a prognostic nomogram and risk stratification system for upper thoracic esophageal squamous cell carcinoma

Front Oncol. 2023 Apr 12:13:1059539. doi: 10.3389/fonc.2023.1059539. eCollection 2023.

Authors

Yu Lin¹, Binglin Zheng¹, Junqiang Chen¹, Qiuyuan Huang¹, Yuling Ye¹, Yong Yang², Yuanmei Chen³, Bijuan Chen¹, Mengxing You⁴, Qifeng Wang⁵, Yuanji Xu¹

Affiliations

¹ Department of Radiation Oncology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, China.
² Department of Radiation Oncology, Fujian Medical University Union Hospital, Fuzhou, China.
³ Department of Thoracic Surgery, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, China.
⁴ Department of Medical Oncology, The First Hosptial of Putian, Fujian Medical University Teaching Hospital, Putian, 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, China.

Abstract

Background: The study aimed to develop a nomogram model to predict overall survival (OS) and construct a risk stratification system of upper thoracic esophageal squamous cell carcinoma (ESCC).

Methods: Newly diagnosed 568 patients with upper ESCC at Fujian Medical University Cancer Hospital were taken as a training cohort, and additional 155 patients with upper ESCC from Sichuan Cancer Hospital Institute were used as a validation cohort. A nomogram was established using Cox proportional hazard regression to identify prognostic factors for OS. The predictive power of nomogram model was evaluated by using 4 indices: concordance statistics (C-index), time-dependent ROC (ROCt) curve, net reclassification index (NRI) and integrated discrimination improvement (IDI).

Results: In this study, multivariate analysis revealed that gender, clinical T stage, clinical N stage and primary gross tumor volume were independent prognostic factors for OS in the training cohort. The nomogram based on these factors presented favorable prognostic efficacy in the both training and validation cohorts, with concordance statistics (C-index) of 0.622, 0.713, and area under the curve (AUC) value of 0.709, 0.739, respectively, which appeared superior to those of the American Joint Committee on Cancer (AJCC) staging system. Additionally, net reclassification index (NRI) and integrated discrimination improvement (IDI) of the nomogram presented better discrimination ability to predict survival than those of AJCC staging. Furthermore, decision curve analysis (DCA) of the nomogram exhibited greater clinical performance than that of AJCC staging. Finally, the nomogram fairly distinguished the OS rates among low, moderate, and high risk groups, whereas the OS curves of clinical stage could not be well separated among clinical AJCC stage.

Conclusion: We built an effective nomogram model for predicting OS of upper ESCC, which may improve clinicians' abilities to predict individualized survival and facilitate to further stratify the management of patients at risk.

Keywords: AJCC stage; nomogram model; prognosis; risk stratification; upper thoracic ESCC.

Grants and funding

This study was supported in part by grants from Fujian Provincial Health Technology Project, China (#2020TG006), Fujian Provincial Clinical Research Center for Cancer Radiotherapy and Immunotherapy (#2020Y2012), and the National Clinical Key Specialty Construction Program.