A Recurrence Predictive Model for Node-negative Esophageal Squamous Cell Carcinoma After Upfront Esophagectomy
Shi-Yu Hu1, Hui-Jiang Gao1, Zhi-Hui Jiang2
1Department of Thoracic Surgery, The Affiliated Hospital of Qingdao University, Qingdao, China.
Seminars in Thoracic and Cardiovascular Surgery
|September 11, 2022
Summary
A new predictive model accurately forecasts recurrence in node-negative esophageal squamous cell carcinoma (ESCC) after surgery. This tool aids personalized treatment strategies for better patient outcomes.
Area of Science:
- Oncology
- Surgical Oncology
- Cancer Prognostics
Background:
- Prognosis for node-negative esophageal squamous cell carcinoma (ESCC) post-surgery is often poor.
- Accurate recurrence prediction is crucial for personalized management of ESCC patients.
Purpose of the Study:
- To develop and validate a precise predictive model for recurrence in pN0 ESCC after upfront complete resection.
- To compare the model's efficacy against the AJCC 8th TNM staging system.
Main Methods:
- Retrospective analysis of clinical and pathological data from 270 completely resected pT1-3N0M0 ESCC patients (2014-2019).
- Cox regression analysis to establish a nomogram, validated using bootstrap resampling and k-fold cross-validation.
- Comparison with AJCC 8th TNM staging using Td-ROC, NRI, IDI, and DCA.
Main Results:
- The predictive model identified pT-category, differentiation, perineural invasion, examined lymph nodes (ELN), and prognostic nutritional index (PNI) as independent risk factors.
- The model achieved a c-index of 0.725 and demonstrated superior predictive ability compared to the AJCC 8th TNM staging system.
- Patients stratified into low-risk and high-risk groups showed significantly different recurrence rates (p < .001).
Conclusions:
- A novel nomogram facilitates precise recurrence prediction in pN0 ESCC post-surgery.
- This model can aid in stratifying patients for personalized management, potentially improving survival benefits.
