Using item response theory (IRT) to improve the efficiency of the Simple Clinical Colitis Activity Index (SCCAI) for patients with ulcerative colitis

Abstract

Abstract Background The SCCAI was designed to facilitate assessment of disease activity in ulcerative colitis (UC). We aimed to interrogate the metric properties of individual items of the SCCAI using item response theory (IRT) analysis, to simplify and improve its performance. Methods The original 9-item SCCAI was collected through TrueColours, a real-time software platform which allows remote entry and monitoring of patients with UC. Data were securely uploaded onto Dementias Platform UK Data Portal, where they were analysed in Stata 16.1 SE. A 2-parameter (2-PL) logistic IRT model was estimated to evaluate each item of the SCCAI for its informativeness (discrimination). A revised scale was generated and re-assessed following systematic removal of items. Results SCCAI data for 516 UC patients (41 years, SD = 15) treated in Oxford were examined. After initial item deletion (Erythema nodosum, Pyoderma gangrenosum), a 7-item scale was estimated. Discrimination values (information) ranged from 0.41 to 2.52 indicating selected item inefficiency with three items < 1.70 which is a suggested discriminatory value for optimal efficiency. Systematic item deletions found that a 4-item scale (bowel frequency day; bowel frequency nocturnal; urgency to defaecation; rectal bleeding) was more informative and discriminatory of trait severity (discrimination values of 1.50 to 2.78). The 4-item scale possesses higher scalability and unidimensionality, suggesting that the responses to items are either direct endorsement (patient selection by symptom) or non-endorsement of the trait (disease activity). Conclusion Reduction of the SCCAI from the original 9-item scale to a 4-item scale provides optimum trait information that will minimise response burden. This new 4-item scale needs validation against other measures of disease activity such as faecal calprotectin, endoscopy and histopathology.