A New Risk Prediction Model for Detecting Endoscopic Activity of Ulcerative Colitis

Area of Science:

• Gastroenterology
• Inflammatory Bowel Disease Research
• Biomarker Discovery

Background:

• Ulcerative colitis (UC) is a chronic, relapsing-remitting inflammatory disease with increasing prevalence.
• Mucosal healing is the primary therapeutic goal in UC management.
• Current endoscopic assessments for UC activity are invasive, costly, and inconvenient.

Purpose of the Study:

• To develop and validate a noninvasive predictive model for monitoring endoscopic activity in ulcerative colitis patients.
• To establish a reliable tool for assessing UC disease activity in clinical practice.

Main Methods:

• A retrospective study involving 198 adult UC patients from January 2016 to August 2022.
• Patients were divided into training (70%) and validation (30%) cohorts.
• A nomogram was developed incorporating specific clinical and laboratory parameters.

Main Results:

• The nomogram demonstrated high predictive accuracy in both training (AUC=0.858) and validation (AUC=0.845) cohorts.
• Calibration curves confirmed consistency between predicted and actual probabilities.
• Decision curve analysis indicated the nomogram's clinical utility.

Conclusions:

• A novel nomogram incorporating activated partial thromboplastin time, fecal occult blood test, β2-globulin, and fibrinogen degradation products can effectively evaluate UC activity.
• This noninvasive tool offers a prospective method for monitoring UC in clinical settings.
• The developed nomogram provides a valuable alternative to invasive endoscopic evaluations.