ArticleDEN open2024
Differentiation grade as a risk factor for lymph node metastasis in T1 colorectal cancer.
Article in DEN open, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
5 citing papers in PubMed, 1 synthesis or guideline pooled it, 5 citations in OpenAlex.
- Efficacy of a whole slide image-based prediction model for lymph node metastasis in T1 colorectal cancer: A systematic review.Journal of gastroenterology and hepatology · 2024Pooled it
- Construction of a novel prediction model based on albumin-hemoglobin score and serum microRNA-497-5p for prognosis of patients with stage II-III colorectal cancer.Oncology letters · 2026Article
- Development and explanation of a machine learning model for identifying non-localized early-onset T1 colorectal cancer.Discover oncology · 2025Article
- A novel artificial intelligence approach to the prediction of lymph node metastasis using whole-slide imaging in patients with T1 colorectal cancer.Surgical endoscopy · 2025Article
- Comparative prediction of lymph node metastasis in pT1 colorectal cancer among Western and Japanese guidelines.Frontiers in oncology · 2024Article
Corrections and comments
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Authors and funding
20 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objectives: Japanese guidelines include high-grade (poorly differentiated) tumors as a risk factor for lymph node metastasis (LNM) in T1 colorectal cancer (CRC). However, whether the grading is based on the least or most predominant component when the lesion consists of two or more levels of differentiation varies among institutions. This study aimed to investigate which method is optimal for assessing the risk of LNM in T1 CRC. Methods: We retrospectively evaluated 971 consecutive patients with T1 CRC who underwent initial or additional surgical resection from 2001 to 2021 at our institution. Tumor grading was divided into low-grade (well- to moderately differentiated) and high-grade based on the least or predominant differentiation analyses. We investigated the correlations between LNM and these two grading analyses. Results: LNM was present in 9.8% of patients. High-grade tumors, as determined by least differentiation analysis, accounted for 17.0%, compared to 0.8% identified by predominant differentiation analysis. A significant association with LNM was noted for the least differentiation method ( Conclusions: Tumor grading via least differentiation analysis proved to be a more reliable measure for assessing LNM risk in T1 CRC compared to grading by predominant differentiation.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.