| [1] | Lorenzen S., Götze T.O., Thuss-Patience P., et al. (2024). Perioperative atezolizumab plus fluorouracil, leucovorin, oxaliplatin, and docetaxel for resectable esophagogastric cancer: Interim results from the randomized, multicenter, phase II/III DANTE/IKF-s633 trial. J. Clin. Oncol. 42:410−420. DOI:10.1200/JCO.23.00975 |
| [2] | Shitara K., Rha S.Y., Wyrwicz L., et al. (2025). Pembrolizumab plus chemotherapy versus chemotherapy as perioperative therapy in locally advanced gastric and gastroesophageal junction cancer: Final analysis of the randomized, phase III KEYNOTE-585 study. J. Clin. Oncol. 43:3152−3159. DOI:10.1200/JCO-25-00486 |
| [3] | Janjigian Y.Y., Al-Batran S.E., Wainberg Z.A., et al. (2025). Perioperative durvalumab in gastric and gastroesophageal junction cancer. N. Engl. J. Med. 393:217−230. DOI:10.1056/NEJMoa2503701 |
| [4] | Huang W., Wang X., Zhong R., et al. (2025). Multimodal radiopathomics signature for prediction of response to immunotherapy-based combination therapy in gastric cancer using interpretable machine learning. Cancer Lett. 631:217930. DOI:10.1016/j.canlet.2025.217930 |
| [5] | Collins G.S., Moons K.G.M., Dhiman P., et al. (2024). TRIPOD+AI statement: Updated guidance for reporting clinical prediction models that use regression or machine learning methods. BMJ 385:e078378. DOI:10.1136/bmj-2023-078378 |
| Xin X., Li Y. and Zheng G. (2026). The value and limits of artificial intelligence in perioperative immunotherapy for gastric cancer. The Innovation Oncology 1:100019. https://doi.org/10.59717/j.xinn-oncol.2026.100019 |
To request copyright permission to republish or share portions of our works, please visit Copyright Clearance Center's (CCC) Marketplace website at marketplace.copyright.com.
From multimodal evidence to executable multidisciplinary decisions: AI-enabled decision support for perioperative immunotherapy in gastric cancer