A Recurrence Predictive Model for Node-negative Esophageal Squamous Cell Carcinoma After Upfront Esophagectomy

Abstract

The prognosis for pathologically node-negative (pN0) esophageal squamous cell carcinoma (ESCC) with surgery alone remains poor. We aimed to develop a model for a more precise prediction of recurrence, which will allow personalized management for pN0 ESCC after upfront complete resection. Clinical and pathological records of patients with completely resected pT1-3N0M0 ESCC were retrospectively analyzed between January 2014 and December 2019. A nomogram for the prediction of recurrence was established based on the Cox regression analysis and evaluated by C-index, AUC, and calibration curves. The model was further validated using bootstrap resampling and k-fold cross-validation and compared with the 8th edition of the AJCC TNM staging system using Td-ROC, NRI, IDI, and DCA. Two-hundred-and seventy cases were included in this study. The median follow-up was 45 months. Distant and/or loco-regional recurrences were noted in 89 (33.0%) patients. The predictive model revealed pT-category, differentiation, perineural invasion, examined lymph nodes (ELN), and prognostic nutritional index (PNI) as independent risk factors for recurrence, with a c-index of 0.725 in the bootstrapping cohort. Td-ROC, NRI, and IDI showed a better predictive ability than the AJCC 8th TNM staging system. Based on this model, patients in the low-risk group had a significantly lower recurrence incidence than those in the high-risk group (p < .001). The predictive model developed in this study may facilitate the precise prediction of recurrences for pN0 ESCC after upfront surgery. Stratifying management of those patients might bring significantly better survival benefits.