| For: | Ban B, Shang A, Shi J. Development and validation of a nomogram for predicting metachronous peritoneal metastasis in colorectal cancer: A retrospective study. World J Gastrointest Oncol 2023; 15(1): 112-127 [PMID: 36684053 DOI: 10.4251/wjgo.v15.i1.112] |
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| URL: | https://www.wjgnet.com/1007-9327/full/v15/i1/112.htm |
| Number | Citing Articles |
| 1 |
Mohamed Elsaigh, Safa Baqar, Bakhtawar Awan, Omnia S Saleh, Mohamed Hesham Gamal, Naomi Abara, Alexander Hawkins, Besiana P Beqo. Comparative Effectiveness of Artificial Intelligence Versus Conventional Methods for Detecting Peritoneal Metastasis in Colorectal Cancer: A Systematic Review. Cureus 2025; doi: 10.7759/cureus.95484
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| 2 |
Coca-Mihaela Vieru, Wenceslao Vásquez Jiménez, Olga Mateo Sierra, Emma Sola Vendrell, María Jesús Fernández Aceñero. Factors predicting histopathologic response to neoadjuvant chemotherapy in patients with peritoneal metastases from colorectal cancer. American Journal of Clinical Pathology 2026; 165(6) doi: 10.1093/ajcp/aqag055
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| 3 |
Li Yao, Huan Shao, Xinyi Zhang, Xuan Huang. A novel risk model for predicting peritoneal metastasis in colorectal cancer based on the SEER database. Journal of Cancer Research and Clinical Oncology 2023; 149(17) doi: 10.1007/s00432-023-05368-9
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| 4 |
Michał Stańczak, Wiesław Kruszewski, Maciej Ciesielski, Jakub Walczak, Piotr Kurek, Tomasz Buczek, Mariusz Szajewski. What is worth knowing about peritoneal metastases in colorectal cancer?. Frontiers in Surgery 2026; 12 doi: 10.3389/fsurg.2025.1719153
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| 5 |
Xuesong Li, Zheng Mo, Feng Wang, Zhuo Yu. A clinical prediction model for metachronous distant metastasis in stage II–III pMMR/MSS colorectal cancer: A single-center, retrospective study. Medicine 2025; 104(46) doi: 10.1097/MD.0000000000045842
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