Dataset Information

Further research on the clinical relevance of the ulcerative colitis colonoscopic index of severity for predicting 5-year relapse.

ABSTRACT:

Purpose

The ulcerative colitis colonoscopic index of severity (UCCIS) evaluates the state of the entire colonic mucosa in ulcerative colitis. However, no cut-off values of scores for predicting clinical relapse in patients with ulcerative colitis have been established. This study aimed to determine the cut-off values for predicting clinical relapse in patients with ulcerative colitis.

Methods

The endoscopic scores (sum of Mayo endoscopic subscores (S-MES) and UCCIS) of 157 patients with ulcerative colitis experiencing clinical remission and their subsequent clinical course were retrospectively reviewed. The optimal cut-off values for predicting relapse and relapse-free rates were analyzed by receiver operating characteristic analysis.

Results

Forty patients with ulcerative colitis experienced relapse within 24 months. The median UCCIS for these patients at the time of study enrollment was significantly higher than that for patients with clinical remission (P < 0.001). The cut-off value of the UCCIS for predicting relapse was 9.8. The relapse-free rate was significantly lower in patients with UCCIS ≥ 9.8 than in those with UCCIS < 9.8 (log-rank test P < 0.001). For patients who experienced relapse within 5 years, the optimal cut-off values for the UCCIS and S-MES were 10.2 and 1, respectively (P = 0.004).

Conclusions

The data from this study indicate that the USSIC is a more relevant score than the S-MES for predicting the time to relapse in patients with ulcerative colitis in remission.

SUBMITTER: Ishida N

PROVIDER: S-EPMC8589779 | biostudies-literature | 2021 Dec

REPOSITORIES: biostudies-literature

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Publications

Further research on the clinical relevance of the ulcerative colitis colonoscopic index of severity for predicting 5-year relapse.

Ishida Natsuki N Onoue Shunya S Miyazu Takahiro T Tamura Satoshi S Tani Shinya S Yamade Mihoko M Iwaizumi Moriya M Hamaya Yasushi Y Osawa Satoshi S Furuta Takahisa T Sugimoto Ken K

International journal of colorectal disease 20210818 12

<h4>Purpose</h4>The ulcerative colitis colonoscopic index of severity (UCCIS) evaluates the state of the entire colonic mucosa in ulcerative colitis. However, no cut-off values of scores for predicting clinical relapse in patients with ulcerative colitis have been established. This study aimed to determine the cut-off values for predicting clinical relapse in patients with ulcerative colitis.<h4>Methods</h4>The endoscopic scores (sum of Mayo endoscopic subscores (S-MES) and UCCIS) of 157 patient ...[more]

PMID: 34409500

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Project description:BackgroundVariability in endoscopic assessment necessitates rigorous investigation of descriptors for scoring severity of ulcerative colitis (UC).ObjectiveTo evaluate variation in the overall endoscopic assessment of severity, the intra- and interindividual variation of descriptive terms and to create an Ulcerative Colitis Endoscopic Index of Severity which could be validated.DesignA two-phase study used a library of 670 video sigmoidoscopies from patients with Mayo Clinic scores 0-11, supplemented by 10 videos from five people without UC and five hospitalised patients with acute severe UC. In phase 1, each of 10 investigators viewed 16/24 videos to assess agreement on the Baron score with a central reader and agreed definitions of 10 endoscopic descriptors. In phase 2, each of 30 different investigators rated 25/60 different videos for the descriptors and assessed overall severity on a 0-100 visual analogue scale. κ Statistics tested inter- and intraobserver variability for each descriptor. A general linear mixed regression model based on logit link and β distribution of variance was used to predict overall endoscopic severity from descriptors.ResultsThere was 76% agreement for 'severe', but 27% agreement for 'normal' appearances between phase I investigators and the central reader. In phase 2, weighted κ values ranged from 0.34 to 0.65 and 0.30 to 0.45 within and between observers for the 10 descriptors. The final model incorporated vascular pattern, (normal/patchy/complete obliteration) bleeding (none/mucosal/luminal mild/luminal moderate or severe), erosions and ulcers (none/erosions/superficial/deep), each with precise definitions, which explained 90% of the variance (pR(2), Akaike Information Criterion) in the overall assessment of endoscopic severity, predictions varying from 4 to 93 on a 100-point scale (from normal to worst endoscopic severity).ConclusionThe Ulcerative Colitis Endoscopic Index of Severity accurately predicts overall assessment of endoscopic severity of UC. Validity and responsiveness need further testing before it can be applied as an outcome measure in clinical trials or clinical practice.

Project description:BackgroundThe significance of endoscopic evaluation in the diagnosis and management of ulcerative colitis (UC) has been widely recognized. Over the years, scholars have established several endoscopic scores. Herein, we assessed the clinical application value of the Mayo Endoscopic Subscore (Mayo ES), the Degree of Ulcerative Colitis Burden of Luminal Inflammation (DUBLIN) score, and the Ulcerative Colitis Endoscopic Index of Severity (UCEIS) score in UC patients, by comparing their correlation with disease activity and their predictive potential for treatment response and clinical outcomes.MethodsUC patients hospitalized from September 2015 to September 2019 were retrospectively analysed. We employed Spearman's rank correlation coefficient to assess the linear association of the assessed endoscopic scores with the clinical parameters. The receiver-operating characteristic curve was applied to evaluate the predictive capabilities of the endoscopic scores for treatment escalation and 1-year readmission.ResultsA total of 178 patients were enrolled; most of them (82%) suffered moderate or severe colitis. Among them, 48 (27%) patients received treatment escalation and 59 (33%) were readmitted within 1 year. The DUBLIN and UCEIS scores demonstrated higher correlations with clinical parameters than the Mayo ES. The DUBLIN scores significantly differed between patients with mild, moderate, and severe colitis (all P < 0.001). The UCEIS scores demonstrated the best predictabilities for treatment escalation and 1-year readmission with an area under the curve of 0.88 and 0.75, respectively. Compared to the UCEIS and DUBLIN scores, the predictive capabilities of the Mayo ES for treatment escalation (both P < 0.001) and 1-year readmission (P < 0.001 and P = 0.002, respectively) were lower. The UCEIS scores exhibited a significant difference between the steroid-responsive group and the steroid-dependent or steroid-refractory group (both P < 0.001), while no significant differences in the Mayo ES and DUBLIN scores were found among the three groups (both P > 0.05).ConclusionThis study demonstrates that both the DUBLIN and UCEIS scores outperform the Mayo ES in assessing disease severity and predicting treatment response and clinical outcomes in UC patients.

Project description:BackgroundUlcerative colitis is an emerging global health concern that poses a significant threat to human health and can progress to colorectal cancer if not diagnosed and treated promptly. Currently, the biomarkers used clinically for diagnosis and dynamic severity monitoring lack disease specificity.MethodsMouse models induced with 2%, 2.5%, and 3% DSS were utilized to simulate human UC with varying severities of inflammation. Transcriptome sequencing technology was employed to identify differentially expressed genes (DEGs) between the control group and each treatment group. Functional enrichment analysis of the KEGG database was performed for shared DEGs among the three treatment groups. DEGs that were significantly and strongly correlated with DSS concentrations were identified using Spearman correlation analysis. Human homologous genes of the interested DEGs were searched in the HomoloGene database, and their regulation patterns in UC patients were validated using the GSE224758 dataset. These genes were then submitted to the DisGeNET database to identify their known associations with human diseases. Online tools, including SignalP 6.0 and DeepTMHMM 1.0, were used to predict signal peptides and transmembrane helices in the amino acid sequences of human genes homologous to the DEGs of interest.ResultsA total of 1,230, 995, and 2,214 DEGs were identified in the 2%, 2.5%, and 3% DSS-induced groups, respectively, with 668 DEGs common across all three groups. These shared DEGs were primarily associated with signaling transport, pathogenesis, and immune response. Through extensive screening, LGI2 and PRSS22 were identified as potentially novel biomarkers with higher specificity and ease of detection for the early diagnosis and dynamic severity monitoring of human UC, respectively.ConclusionWe have identified two potentially novel biomarkers, LGI2 and PRSS22, which are easy of detection and more specific for human UC. These findings provide new insights into the accurate diagnosis and dynamic monitoring of this persistent disease.

Dataset Information

Further research on the clinical relevance of the ulcerative colitis colonoscopic index of severity for predicting 5-year relapse.

Purpose

Methods

Results

Conclusions

Publications

Further research on the clinical relevance of the ulcerative colitis colonoscopic index of severity for predicting 5-year relapse.

Similar Datasets

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