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Updated: Jan 17, 2026
Author Spotlight: Advancing Early Detection and Treatment of Gastrointestinal Tumors
Published on: February 16, 2024
Contour-like model for precision risk stratification in gastric cancer patients underwent neoadjuvant therapy: A
Siwei Pan1, Weiwei Zhu2, Yanqiang Zhang2
1Department of Gastric Surgery, The Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Institutes of Basic Medicine and Cancer (IBMC), Chinese Academy of Sciences, Hangzhou, 310022, China; Key Laboratory of Prevention, Diagnosis and Therapy of Upper Gastrointestinal Cancer of Zhejiang Province, Hangzhou, 310022, China; Zhejiang Provincial Research Center for Upper Gastrointestinal Tract Cancer, Zhejiang Cancer Hospital, Hangzhou, 310022, China.
Background:
Lymph node metastasis (LNM) is a critical determinant of prognosis in gastric cancer (GC). Accurate evaluation of lymph node involvement enhances prognostic accuracy and informs postoperative strategies.
Methods:
This retrospective study included 649 GC patients who received neoadjuvant chemotherapy followed by curative surgery at two centers between 2009 and 2019. An additional cohort of 292 patients was selected from the SEER database using matching criteria. Collected variables included the number of retrieved lymph nodes (rLNs), positive lymph nodes (pLNs), pathological T stage after treatment (ypT), and Tumor Regression Grade. A novel contour-like ypTN (Con-ypTN) model was constructed using a Gaussian process-augmented Cox regression approach to predict the overall prognosis. Model performance was evaluated through receiver operating characteristic curve analysis, the Delong test, calibration plots, and decision curve analysis.
Results:
The Con-ypTN model demonstrated strong prognostic discrimination. AUC values were 0.853 (95 % CI: 0.807-0.900) in the training cohort. Calibration plots and Delong test results showed good agreement between predicted and actual outcomes across all datasets. Notably, the Con-ypTN model significantly outperformed all comparator staging systems (P < 0.05). Patients classified as high risk by the Con-ypTN model had significantly worse survival outcomes than those in the low-risk group (P < 0.05).
Conclusion:
The Con-ypTN model provides a robust and clinically relevant tool for prognostic stratification of GC patients treated with neoadjuvant chemotherapy. The model enables precise identification of high-risk individuals, offering improved guidance for postoperative clinical decision-making.
