aceDevelopment and validation of an explainable model for predicting lymph node metastasis in early gastric cancer: a multicenter retrospective study with external and prospective validation
Accurate preoperative prediction of lymph node metastasis (LNM) is essential for treatment selection in early gastric cancer (EGC), particularly when considering endoscopic submucosal dissection. Existing approaches show limited sensitivity for metastatic disease and frequently lack external or prospective validation. We aimed to develop and validate an interpretable machine-learning model for individualized preoperative prediction of LNM in EGC. In this multicenter study, four cohorts from three tertiary center…
An interpretable XGBoost model estimated individual risk of lymph node metastasis in early gastric cancer and held up in external and prospective validation, which may help choose between endoscopic and surgical treatment.
PR-AUC values in validation cohorts (about 0.51 to 0.61) were considerably lower than the training AUC suggests, indicating room for improvement in identifying metastatic cases.
Evidence
- Peer-reviewedEuropean Journal of Surgical Oncology2026-10-14
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Truvace Impact Record TRV-2026-1992, v1: “Development and validation of an explainable model for predicting lymph node metastasis in early gastric cancer: a multicenter retrospective study with external and prospective validation.” Truvace, 2026-10-20. /record/TRV-2026-1992 (accessed at citation time). sha256 d646c1a8d75e8616…
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