Construction a new nomogram prognostic model for predicting overall survival after radical resection of esophageal squamous cancer

Bowen Shi; Chunguang Li; Wenqiang Xia; Yuerong Chen; Hezhong Chen; Li Xu; Ming Qin

doi:10.3389/fonc.2023.1007859

Construction a new nomogram prognostic model for predicting overall survival after radical resection of esophageal squamous cancer

Front Oncol. 2023 Mar 21:13:1007859. doi: 10.3389/fonc.2023.1007859. eCollection 2023.

Authors

Bowen Shi¹, Chunguang Li², Wenqiang Xia¹, Yuerong Chen³, Hezhong Chen¹, Li Xu⁴, Ming Qin⁵

Affiliations

¹ Department of Thoracic Surgery, Changhai Hospital, Naval Medical University, Shanghai, China.
² Department of Thoracic Surgery, Shanghai Chest Hospital, Shanghai Jiaotong University, Shanghai, China.
³ Department of General Surgery, Tengchong People's Hospital, Tengchong, China.
⁴ Department of Thoracic Surgery, Shanghai Pulmonary Hospital, Shanghai Tongji University, Shanghai, China.
⁵ School of Basic Medicine, Naval Medical University, Shanghai, China.

Abstract

Background: Esophageal cancer is one of the deadliest malignancies in the world, and 5-year overall survival (OS) of esophageal cancer ranges from 12% to 20%. Surgical resection remains the principal treatment. The American Joint Commission on Cancer (AJCC) TNM (tumor, node, and metastasis) staging system is a key guideline for prognosis and treatment decisions, but it cannot fully predict outcomes. Therefore, targeting the molecular and biological features of each patient's tumor, and identifying key prognostic biomarkers as effective survival predictors and therapeutic targets are highly important to clinicians and patients.

Methods: In this study, three different methods, including Univariate Cox regression, Lasso regression, and Randomforest regression were used to screen the independent factors affecting the prognosis of esophageal squamous cell carcinoma and construct a nomogram prognostic model. The accuracy of the model was verified by comparing with TNM staging system and the reliability of the model was verified by internal cross validation.

Results: Preoperative neutrophil lymphocyte ratio(preNLR), N-stage, p53 level and tumor diameter were selected to construct the new prognostic model. Patients with higher preNLR level, higher N-stage, lower p53 level and larger tumor diameter had worse OS. The results of C-index, Decision Curve Analysis (DCA), and integrated discrimination improvement (IDI) showed that the new prognostic model has a better prediction than the TNM staging system.

Conclusion: The accuracy and reliability of the nomogram prognostic model were higher than that of TNM staging system. It can effectively predict individual OS and provide theoretical basis for clinical decision making.

Keywords: Cox regression; TNM staging system; esophageal squamous cell carcinoma; nomogram; prognostic model.

Grants and funding

This work was supported by the National Natural Science Foundation of Shanghai (20ZR1456200) and Changhai Hospital Youth Cultivation Fund (2021JCQN16).