New score models for assessing disease activity in Crohn's disease based on bowel ultrasound

New score models for assessing disease activity in Crohn's disease based on bowel ultrasound and biomarkers: Ideal surrogates for endoscopy or imaging.

Qingyang Zhou, Qingli Zhu, Wei Liu, Wenbo Li, Li Ma, Mengsu Xiao, Jingjuan Liu, Hong Yang, Jiaming Qian

Published in July 2023, American Society of Clinical pharmacology and the therapeutics.

Abstract

Disease activity evaluation is important in Crohn's disease (CD). We aimed to establish new disease activity indices for CD based on noninvasive parameters. The data of 110 patients with CD were retrospectively analyzed. Parameters from bowel ultrasound and biomarkers were measured to select the variables included in the models by univariate analysis. Logistic regression analysis was performed to predict mucosal and transmural activities defined by ileocolonoscopy or computed tomography enterography, respectively.

The models' performance was measured by the area under the receiver operating characteristic (ROC) curve (AUC). Leave-one-out cross validation (LOOCV) was applied to adjust for overconfidence in the newly established score models. To predict mucosal activity, erythrocyte sedimentation rate (ESR) and (LimG × BWT)-SUM (the sum of the product of Limberg grade [LimG] and bowel wall thickness [BWT] of each bowel segment) were selected for model A, and the equation was A = 2 × ESR + 9.3 × (LimG × BWT)-SUM. The AUC of ROC, sensitivity, and specificity were 0.927%, 89.8%, and 86.4%, respectively. The AUC of the ROC curve verified by LOOCV was 0.913.

To predict transmural activity, albumin (ALB) and LimG-SUM (the sum of the LimG of all the bowel segments) were selected for model B, which was established as B = −1.3 × ALB +1.7 × LimG-SUM. The AUC of ROC, sensitivity, and specificity were 0.851%, 78.0%, and 84.2%, respectively. The AUC of the ROC curve verified by LOOCV was 0.833. Nomograms were developed for two score models. New score models based on noninvasive parameters established in this study showed good abilities in detecting active disease and performed well in the validation phase.