1. Clinical TNM staging for esophageal, gastric, and colorectal cancers in the era of neoadjuvant therapy: A systematic review of the literature
- Author
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Hideaki Shimada, Takeo Fukagawa, Yoshio Haga, Shin‐ichi Okazumi, and Koji Oba
- Subjects
colorectal cancer ,distant metastases ,esophageal cancer ,gastric cancer ,lymph node metastases ,T4 ,Surgery ,RD1-811 ,Diseases of the digestive system. Gastroenterology ,RC799-869 - Abstract
Abstract Aim Clinical staging is vital for selecting appropriate candidates and designing neoadjuvant treatment strategies for advanced tumors. The aim of this review was to evaluate diagnostic abilities of clinical TNM staging for gastrointestinal, gastrointestinal cancers. Methods We conducted a systematic review of recent publications to evaluate the accuracy of diagnostic modalities on gastrointestinal cancers. A systematic literature search was performed in PubMed/MEDLINE using the keywords “TNM staging,” “T4 staging,” “distant metastases,” “esophageal cancer,” “gastric cancer,” and “colorectal cancer,” and the search terms used in Cochrane Reviews between January 2005 to July 2020. Articles focusing on preoperative diagnosis of: (a) depth of invasion; (b) lymph node metastases; and (c) distant metastases were selected. Results After a full‐text search, a final set of 55 studies (17 esophageal cancer studies, 26 gastric cancer studies, and 12 colorectal cancer studies) were used to evaluate the accuracy of clinical TNM staging. Positron emission tomography–computed tomography (PET‐CT) and/or magnetic resonance imaging (MRI) were the best modalities to assess distant metastases. Fat and fiber mode of CT may be useful for T4 staging of esophageal cancer, CT was a partially reliable modality for lymph node staging in gastric cancer, and CT combined with MRI was the most reliable modality for liver metastases from colorectal cancer. Conclusion The most reliable diagnostic modality differed among gastrointestinal cancers depending on the type of cancer. Therefore, we propose diagnostic algorithms for clinical staging for each type of cancer.
- Published
- 2021
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