P743 A personalised algorithm predicting the risk of intravenous corticosteroid failure in acute ulcerative colitis

Abstract

Abstract Background An episode of acute ulcerative colitis (UC) represents an important watershed moment in a patient’s disease course. Foreknowledge of a patient's likely response to intravenous corticosteroid therapy has significant clinical utility. Using a large prospectively collected acute UC patient database and machine learning-based techniques we aimed to derive and validate a personalised algorithm for identifying patients at high risk of corticosteroid therapy failure from variables available at hospital presentation. Methods A prospectively collected database of 600 consecutive presentations of acute UC was collated at a single referral centre between 1996 and 2022. An AIC-based Elastic Net model was used to select variables on the 419 earliest presentations of acute UC (1996-2017). Two risk-scoring algorithms, with and without utilising additional endoscopic variables, were constructed using logistic regression models. These risk scores were then validated on a separate cohort of 181 acute UC presentations (2018-2022). Results The partial risk of rescue (ROR) score included the admission indices of oral corticosteroid treatment; bowel frequency ≥6/24 hours; albumin; CRP ≥12mg/ml and log10CRP. The full ROR score incorporates the same variables with the addition of the Mayo endoscopic subscore and disease extent. The ROC AUCs in the validation cohort were 0.76 (95% CI: 0.69-0.83) and 0.78 (95% CI: 0.71-0.85) for the partial and full ROR scores, respectively. When incomplete cases were excluded, the full ROR score validation cohort ROC AUC increased from 0.78 to 0.80. Conclusion These pragmatic personalised risk scores (available at www.severecolitis.com) have comparably strong performance characteristics and usability enabling the identification of individuals at high risk of corticosteroid treatment failure before or after endoscopic assessment. These patients may be suitable for consideration of early treatment escalation or screening for participation in clinical trials.