Dataset Information

Bowel ultrasound enhances predictive value based on clinical indicators: a scoring system for moderate-to-severe endoscopic activities in patients with ulcerative colitis.

ABSTRACT:

Background and aim

The aim was to assess non-invasive factors among clinical features, laboratory, and bowel ultrasound (BUS) characteristics and to develop a scoring system to predict endoscopic activities for ulcerative colitis (UC) patients.

Methods

We performed a retrospective study collecting UC patients between January 2015 to September 2020. Logistic regression was performed to predict moderate-to-severe endoscopic activities, defined as endoscopic Mayo score ⩾2. Model performance was described with discrimination and calibration ability and validated by internal and external methods.

Results

A total of 103 and 29 patients were enrolled in the modeling and validation groups, respectively. Stool frequency ⩾5 times/day, hematochezia, erythrocyte sedimentation rate (ESR), and colonic wall flow in BUS were included into two predictive models for endoscopic activities, both with good discrimination ability [Area under curve (AUC) 0.879 and 0.882, p < 0.001] and a sensitivity of 76.7% and specificity of 92.3%, which showed an adequate calibration ability by using the Hosmer-Lemeshow test (p = 0.14 and 0.07). The external validation displayed consistent results with the above mentioned. Nomograms were also established for these models.

Conclusion

We developed predictive models for endoscopic disease activities by using noninvasive factors based on stool frequency, hematochezia, ESR, and colonic wall blood flow in BUS. These models performed well in the internal and external validation.

SUBMITTER: Zhang M

PROVIDER: S-EPMC8283041 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Bowel ultrasound enhances predictive value based on clinical indicators: a scoring system for moderate-to-severe endoscopic activities in patients with ulcerative colitis.

Zhang Mengmeng M Zhang Huimin H Zhu Qingli Q Bai Xiaoyin X Zhou Qingyang Q Ruan Gechong G Li Wenbo W Ma Li L Xiao Mengsu M Yang Hong H Qian Jiaming J

Therapeutic advances in gastroenterology 20210713

<h4>Background and aim</h4>The aim was to assess non-invasive factors among clinical features, laboratory, and bowel ultrasound (BUS) characteristics and to develop a scoring system to predict endoscopic activities for ulcerative colitis (UC) patients.<h4>Methods</h4>We performed a retrospective study collecting UC patients between January 2015 to September 2020. Logistic regression was performed to predict moderate-to-severe endoscopic activities, defined as endoscopic Mayo score ⩾2. Model perf ...[more]

PMID: 34345250

Similar Datasets

Project description:BackgroundIntestinal ultrasound (IUS) is an emerging modality in monitoring disease activity in ulcerative colitis (UC). Here, we aimed to identify early IUS predictors of treatment response as evaluated by endoscopy and assessed the kinetics of IUS changes.MethodsThis prospective, longitudinal study included UC patients with endoscopic disease activity (endoscopic Mayo score [EMS] ≥2) starting anti-inflammatory treatment. Clinical scores, biochemical parameters and IUS were assessed at baseline (W0), at week 2 (W2), at W6(W6), and at the time of second endoscopy (W8-W26). Per colonic segment, endoscopic remission (EMS = 0), improvement (EMS ≤1), response (decrease in EMS ≥1), and clinical remission (Lichtiger score ≤3) were assessed and correlated with common IUS parameters. Additionally, drug-specific responsiveness of bowel wall thickness (BWT) was assessed.ResultsA total of 51 patients were included and followed, and 33 patients underwent second endoscopy. BWT was lower from W6 onward for patients reaching endoscopic improvement (3.0 ± 1.2 mm vs 4.1 ± 1.3 mm; P = .026), remission (2.5 ± 1.2 mm vs 4.1 ± 1.1 mm; P = .002), and clinical remission (3.01 ± 1.34 mm vs 3.85 ± 1.20 mm; P = .035). Decrease in BWT was more pronounced in endoscopic responders (-40 ± 25% vs -4 ± 28%; P = .001) at W8 to W26. At W6, BWT ≤3.0 mm (odds ratio [OR], 25.13; 95% confidence interval, 2.01-3.14; P = .012) and color Doppler signal (OR, 0.35; 95% confidence interval, 0.14-0.88; P = .026) predicted endoscopic remission and improvement, respectively. Submucosal layer thickness at W6 predicted endoscopic remission (OR, 0.09; P = .018) and improvement (OR, 0.14; P = .02). Furthermore, BWT decreased significantly at W2 for infliximab and tofacitinib and at W6 for vedolizumab.ConclusionsBWT and color Doppler signal predicted endoscopic targets already after 6 weeks of treatment and response was drug specific. IUS allows close monitoring of treatment in UC and is a surrogate marker of endoscopy.

Project description:BackgroundEndoscopic healing is an established treatment target for ulcerative colitis (UC). We have recently validated the Milan ultrasound criteria (MUC) to assess endoscopic activity in UC; a MUC score > 6.2 is a valid cut-off to discriminate endoscopic activity (Mayo endoscopic subscore > 1).ObjectiveThe aim of this study was to assess the predictive value of MUC on disease course in a prospective cohort of UC patients.MethodsUC patients regardless of disease activity and current therapy, underwent colonoscopy and bowel ultrasound (US) at baseline in a blinded fashion. Correlations between baseline MUC and Mayo endoscopic subscore were assessed using Spearman's rank correlation. UC-related negative course (defined as the need for corticosteroids, or treatment escalation, or hospitalization, or need for colectomy: a composite outcome) over a median 20 months follow-up, was investigated using the Kaplan-Meier method and Cox regression analysis.Results98 UC patients were followed up for a median time of 1.6 years (IQR 0.9¬2.7). Milan ultrasound criteria and Mayo endoscopic subscore significantly correlated at baseline (ρ = 0.653; p < 0.001). 70 patients (71%) had negative disease course during the follow-up period. Milan ultrasound criteria > 6.2 at baseline was statistically significantly associated with negative disease course (HR: 3.87, 95% CI: 2.25-6.64, p < 0.001). Kaplan-Meier analyses drawed a statistically significantly lower cumulative probability of treatment escalation, need of corticosteroids, hospitalization and colectomy, among patients who had MUC ≤ 6.2 at baseline as compared to patients with MUC > 6.2 (p < 0.05 for all outcomes).Conclusionwe have demonstrated for the first time the value of bowel US and an US score in predicting disease course in UC. Milan ultrasound criteria, a validated US-based score, predicts disease course in UC. Milan ultrasound criteria ≤ 6.2 may be the new treatment target to achieve to reduce the risk of worse outcomes.

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:BackgroundEndoscopic disease activity monitoring is important for the long-term management of patients with ulcerative colitis (UC), there is currently no widely accepted non-invasive method that can effectively predict endoscopic disease activity. We aimed to develop and validate machine learning (ML) models for predicting it, which are desired to reduce the frequency of endoscopic examinations and related costs.MethodsThe patients with a diagnosis of UC in two hospitals from January 2016 to January 2021 were enrolled in this study. Thirty nine clinical and laboratory variables were collected. All patients were divided into four groups based on MES or UCEIS scores. Logistic regression (LR) and four ML algorithms were applied to construct the prediction models. The performance of models was evaluated in terms of accuracy, sensitivity, precision, F1 score, and area under the receiver-operating characteristic curve (AUC). Then Shapley additive explanations (SHAP) was applied to determine the importance of the selected variables and interpret the ML models.ResultsA total of 420 patients were entered into the study. Twenty four variables showed statistical differences among the groups. After synthetic minority oversampling technique (SMOTE) oversampling and RFE variables selection, the random forests (RF) model with 23 variables in MES and the extreme gradient boosting (XGBoost) model with 21 variables in USEIS, had the greatest discriminatory ability (AUC = 0.8192 in MES and 0.8006 in UCEIS in the test set). The results obtained from SHAP showed that albumin, rectal bleeding, and CRP/ALB contributed the most to the overall model. In addition, the above three variables had a more balanced contribution to each classification under the MES than the UCEIS according to the SHAP values.ConclusionThis proof-of-concept study demonstrated that the ML model could serve as an effective non-invasive approach to predicting endoscopic disease activity for patients with UC. RF and XGBoost, which were first introduced into data-based endoscopic disease activity prediction, are suitable for the present prediction modeling.

Dataset Information

Bowel ultrasound enhances predictive value based on clinical indicators: a scoring system for moderate-to-severe endoscopic activities in patients with ulcerative colitis.

Background and aim

Methods

Results

Conclusion

Publications

Bowel ultrasound enhances predictive value based on clinical indicators: a scoring system for moderate-to-severe endoscopic activities in patients with ulcerative colitis.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets