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Restaging pN Classification in Early Gastric Cancer with Inadequate Lymph Node Retrieval: Multi-Institutional

Xinyang Nie¹, Gang Li², Zhiqiang Liu³

¹Department of Gastric Surgery, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin Key Laboratory of Digestive Cancer, Tianjin's Clinical Research Center for Cancer, Tianjin, 300060, People's Republic of China.

International Journal of General Medicine

|May 19, 2026

Summary

A new lymph node staging strategy for early gastric cancer (EGC) improves accuracy. Examining 20 or fewer lymph nodes (ELNs) is inadequate, but a corrected model enhances prognostic evaluation for EGC patients.

Keywords:

lymph node metastasis neoplasm prognosis stomach

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Area of Science:

Oncology
Surgical Pathology
Cancer Staging

Background:

Early gastric cancer (EGC) staging is often inaccurate due to insufficient examined lymph nodes (ELNs).
Lack of standardized criteria for ELN retrieval contributes to staging migration and impacts prognostic evaluation.

Purpose of the Study:

To propose and validate a novel lymph node (LN) staging strategy for EGC.
To mitigate staging inaccuracies caused by variable ELN retrieval.
To enhance the accuracy of prognostic evaluation in EGC patients.

Main Methods:

Analysis of a large cohort (6566 patients) from China to determine optimal ELN cutoff and construct a prediction model.
Validation of the new LN staging method using independent multicenter (2094 patients) and SEER database (1944 patients) test cohorts.
Evaluation of model performance, correlation between ELNs and metastatic LNs (MLNs), and survival differences.

Main Results:

≤20 ELNs were identified as inadequate for accurate LN evaluation in EGC.
A positive association was found between MLNs and ELNs in the test cohorts.
The developed model accurately displayed MLNs after correction for patients with inadequate ELNs.
Significant survival differences were observed between patients with different modified pN (pN_M) stages.

Conclusions:

The model-corrected pN_M staging demonstrates improved accuracy over AJCC staging for EGC patients with ≤20 ELNs.
This new strategy shows significant clinical applicability for reducing staging migration and enhancing survival prediction in EGC.
The findings support the adoption of this revised staging approach for better patient management.