ArticleFrontiers in oncology2022
Differential Diagnosis of Crohn's Disease and Ulcerative Primary Intestinal Lymphoma: A Scoring Model Based on a Multicenter Study.
Article in Frontiers in oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- A deep learning model using endoscopic images for differential diagnosis of intestinal lymphoma.Chinese medical journal · 2026Article
- A rare case of monomorphic epitheliotropic intestinal T-cell lymphoma, presenting with spontaneous intestinal perforation.International journal of surgery case reports · 2024Article
- Computed tomography-based radiomics combined with machine learning allows differentiation between primary intestinal lymphoma and Crohn's disease.World journal of gastroenterology · 2024Article
- Multimodality imaging features of small bowel cancers complicating Crohn's disease: a pictorial review.Abdominal radiology (New York) · 2024Review
- Primary Gastrointestinal T-cell Lymphoma Presenting as Spontaneous Perforation Peritonitis.Cureus · 2023Article
- Nomogram based on computed tomography images and clinical data for distinguishing between primary intestinal lymphoma and Crohn's disease: a retrospective multicenter study.Frontiers in medicine · 2023Article
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17 authors.
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Abstract
Background: Differential diagnosis of Crohn's disease (CD) and ulcerative primary intestinal lymphoma (UPIL) is a tough problem in clinical practice. Aims: Our study identified key differences between CD and UPIL patients and aimed to further establish a scoring model for differential diagnosis. Methods: A total of 91 CD and 50 UPIL patients from 9 tertiary inflammatory bowel disease centers were included. Univariate and multivariate analyses were used to determine significant markers for differentiating CD and UPIL. A differential scoring model was established by logistic regression analysis. Results: The differential model was based on clinical symptoms, endoscopic and imaging features that were assigned different scores: intestinal bleeding (-2 points), extraintestinal manifestation (2 points), segmental lesions (1 point), cobblestone sign (2 points), homogeneous enhancement (-1 point), mild enhancement (-1 point), engorged vasa recta (1 point). A total score of ≥1 point indicates CD, otherwise UPIL was indicated. This model produced an accuracy of 83.66% and an area under the ROC curve of 0.947. The area under the ROC curve for validation using the 10-fold validation method was 0.901. Conclusion: This study provided a convenient and useful model to differentiate CD from UPIL.
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