A pathological classification for predicting recurrence and guiding adjuvant therapy in esophageal squamous cell carcinoma following neoadjuvant immunochemotherapy: a two-center cohort study

Background Neoadjuvant immunochemotherapy (nICT) has emerged as a promising treatment modality for locally advanced esophageal squamous cell carcinoma (ESCC). However, optimal post-nICT adjuvant strategies remain undefined, and a classification system that integrates both prognosis and recurrence patterns to guide treatment decisions is currently lacking. Methods This retrospective study enrolled 283 patients with locally advanced ESCC who underwent nICT with R0 resection between January 2019 and December 2023 at two participating institutions. The primary endpoint was recurrence-free survival (RFS). Secondary endpoints included recurrence patterns, overall survival (OS), locoregional recurrence-free survival (LRFS), and distant metastasis-free survival (DMFS). Survival curves were generated using the Kaplan-Meier method. Propensity score matching was employed for group comparisons and a Cox proportional hazards model was used to identify prognostic factors. Results The pathological complete response (pCR) and major pathological response (MPR) rates were 22.6% and 52.3%, respectively. Multivariate analysis identified the tumor regression grade (TRG) and ypN stage as independent predictors of RFS. Both ypN status and TRG were key determinants of recurrence patterns. Based on this, patients were stratified into four subgroups: Group 1 (TRG0-1 ypN0), Group 2 (TRG0-1 ypN+), Group 3 (TRG2-3 ypN0), and Group 4 (TRG2-3 ypN+). This classification demonstrated significant prognostic stratification, with Group 1 having the best prognosis and Group 4 having the worst prognosis. In the entire matched cohort, adjuvant therapy did not significantly improve survival. However, subgroup analyses revealed that adjuvant therapy was associated with a significant improvement in RFS in Group 2 (TRG0-1 ypN+)(HR = 0.16, 95% CI 0.06–0.42, P <0.001). Conclusion The proposed classification system based on TRG and ypN status effectively stratified the prognosis of patients with ESCC after nICT. This classification enabled the identification of a specific subgroup (TRG0-1 ypN+) that may benefit from postoperative adjuvant treatment.

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Journal
Frontiers in Oncology
Published
2026-03-13
DOI
https://doi.org/10.3389/fonc.2026.1778731
Primary Topic
Esophageal Cancer Research and Treatment
Type
article
Field-Weighted Citation Impact
0.00

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article

A pathological classification for predicting recurrence and guiding adjuvant therapy in esophageal squamous cell carcinoma following neoadjuvant immunochemotherapy: a two-center cohort study

Zhekai Zhang, Jiaming Huang, Zhifeng Zhang, Guiqing Zeng et al.
Frontiers in Oncology
Esophageal Cancer Research and Treatment
article

A pathological classification for predicting recurrence and guiding adjuvant therapy in esophageal squamous cell carcinoma following neoadjuvant immunochemotherapy: a two-center cohort study

Zhekai Zhang, Jiaming Huang, Zhifeng Zhang, Guiqing Zeng, Qijun Zheng, Hongsheng Xie, Manhong Yao
article en

Abstract

Background Neoadjuvant immunochemotherapy (nICT) has emerged as a promising treatment modality for locally advanced esophageal squamous cell carcinoma (ESCC). However, optimal post-nICT adjuvant strategies remain undefined, and a classification system that integrates both prognosis and recurrence patterns to guide treatment decisions is currently lacking. Methods This retrospective study enrolled 283 patients with locally advanced ESCC who underwent nICT with R0 resection between January 2019 and December 2023 at two participating institutions. The primary endpoint was recurrence-free survival (RFS). Secondary endpoints included recurrence patterns, overall survival (OS), locoregional recurrence-free survival (LRFS), and distant metastasis-free survival (DMFS). Survival curves were generated using the Kaplan-Meier method. Propensity score matching was employed for group comparisons and a Cox proportional hazards model was used to identify prognostic factors. Results The pathological complete response (pCR) and major pathological response (MPR) rates were 22.6% and 52.3%, respectively. Multivariate analysis identified the tumor regression grade (TRG) and ypN stage as independent predictors of RFS. Both ypN status and TRG were key determinants of recurrence patterns. Based on this, patients were stratified into four subgroups: Group 1 (TRG0-1 ypN0), Group 2 (TRG0-1 ypN+), Group 3 (TRG2-3 ypN0), and Group 4 (TRG2-3 ypN+). This classification demonstrated significant prognostic stratification, with Group 1 having the best prognosis and Group 4 having the worst prognosis. In the entire matched cohort, adjuvant therapy did not significantly improve survival. However, subgroup analyses revealed that adjuvant therapy was associated with a significant improvement in RFS in Group 2 (TRG0-1 ypN+)(HR = 0.16, 95% CI 0.06–0.42, P <0.001). Conclusion The proposed classification system based on TRG and ypN status effectively stratified the prognosis of patients with ESCC after nICT. This classification enabled the identification of a specific subgroup (TRG0-1 ypN+) that may benefit from postoperative adjuvant treatment.

Frontiers in OncologyVol. 16
Southern University of Science and Technology (CN), Fuyang City People's Hospital (CN), The Fifth People's Hospital of Anyang (CN), Shenzhen Second People's Hospital (CN)
National Science Foundation, National Natural Science Foundation of China
Good health and well-being
Openalex Percentile: Top 25%
Esophageal Cancer Research and Treatment
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