Development of a scoring system for predicting the severity of ulcerative colitis

Abstract

Background and study aims: Monitoring disease activity in ulcerative colitis (UC) is critical in preventing long-term complications. This study aims to develop a scoring system using non-invasive indicators to predict endoscopic activities for ulcerative colitis (UC) patients.

Patients and methods: All enrolled patients with UC admitted to Shanghai Xinhua Hospital between June 2017 and January 2021 were enrolled, and their clinical data were retrospectively collected and a number of serological biomarkers concentrations were analyzed. Patients were categorized into mild and moderate-to-severe disease groups. Univariate and multivariate logistic regression was used to predict moderate-to-severe endoscopic activities, which were then incorporated into a nomogram to establish a prediction scoring model.

Result: Overall, 231 patients were divided into a mild group (n = 111, 48.0%) and a moderate-to-severe group (n = 120, 52.0%). The following variables were independently associated with the disease severity and were subsequently included into the prediction model: Proteinase 3 antineutrophil cytoplasmic antibody (PR3-ANCA), C-reactive protein (CRP), hemoglobin(Hb), IL-10, stool frequency ≥ 5 times/day and hematochezia. Incorporating these 6 factors, the nomogram showed good discrimination with C-index of 0.819 and reliable calibration. A scoring model was established with the area under the curve 0.818. Moreover, PR3-ANCA and CRP correlated with the duration of hospital stay.

Conclusion: We developed a predictive model for endoscopic disease activities by using noninvasive factors based on PR3-ANCA, CRP, Hb, IL-10, stool frequency and hematochezia. This prediction model might assist clinicians in managing patients with UC.

Keywords: Disease activity; Nomogram; Prediction; Ulcerative colitis.