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.