Background/Aims: Robust management algorithms are required to reduce the residual risk of colectomy in acute severe ulcerative colitis (ASUC) refractory to standard infliximab salvage therapy. The aim of this study was to evaluate the performance and benefits of alternative ASUC management strategies using simulated prediction models of varying accuracy. Methods: This was a simulation-based modeling study using a hypothetical cohort of 5,000 steroid-refractory ASUC patients receiving standard infliximab induction. Simulated predictive models were used to risk-stratify patients and escalate treatment in patients at high risk of failing standard infliximab induction. The main outcome of interest was colectomy by 3 months. Results: The 3-month colectomy rate in the base scenario where all 5,000 patients received standard infliximab induction was 23%. The best-performing management strategy assigned high-risk patients to sequential Janus kinase inhibitor inhibition and mediumrisk patients to accelerated infliximab induction. Using a 90% area under the curve (AUC) prediction model and optimistic treatment efficacy assumptions, this strategy reduced the 3-month colectomy rate to 8% (65% residual risk reduction). Using an 80% AUC prediction model with only modest treatment efficacy assumptions, the 3-month colectomy rate was reduced to 15% (35% residual risk reduction). Overall management strategy efficacy was highly dependent on predictive model accuracy and underlying treatment efficacy assumptions. Conclusions This is the first study to simulate predictive model-based management strategies in steroid-refractory ASUC and evaluate their effect on short-term colectomy rates. Future studies on predictive model development should incorporate simulation studies to better understand their expected benefit.

Background/Aims: Robust management algorithms are required to reduce the residual risk of colectomy in acute severe ulcerative colitis (ASUC) refractory to standard infliximab salvage therapy. The aim of this study was to evaluate the performance and benefits of alternative ASUC management strategies using simulated prediction models of varying accuracy. Methods: This was a simulation-based modeling study using a hypothetical cohort of 5,000 steroid-refractory ASUC patients receiving standard infliximab induction. Simulated predictive models were used to risk-stratify patients and escalate treatment in patients at high risk of failing standard infliximab induction. The main outcome of interest was colectomy by 3 months. Results: The 3-month colectomy rate in the base scenario where all 5,000 patients received standard infliximab induction was 23%. The best-performing management strategy assigned high-risk patients to sequential Janus kinase inhibitor inhibition and mediumrisk patients to accelerated infliximab induction. Using a 90% area under the curve (AUC) prediction model and optimistic treatment efficacy assumptions, this strategy reduced the 3-month colectomy rate to 8% (65% residual risk reduction). Using an 80% AUC prediction model with only modest treatment efficacy assumptions, the 3-month colectomy rate was reduced to 15% (35% residual risk reduction). Overall management strategy efficacy was highly dependent on predictive model accuracy and underlying treatment efficacy assumptions. Conclusions This is the first study to simulate predictive model-based management strategies in steroid-refractory ASUC and evaluate their effect on short-term colectomy rates. Future studies on predictive model development should incorporate simulation studies to better understand their expected benefit.

Background/Aims: Robust management algorithms are required to reduce the residual risk of colectomy in acute severe ulcerative colitis (ASUC) refractory to standard infliximab salvage therapy. The aim of this study was to evaluate the performance and benefits of alternative ASUC management strategies using simulated prediction models of varying accuracy. Methods: This was a simulation-based modeling study using a hypothetical cohort of 5,000 steroid-refractory ASUC patients receiving standard infliximab induction. Simulated predictive models were used to risk-stratify patients and escalate treatment in patients at high risk of failing standard infliximab induction. The main outcome of interest was colectomy by 3 months. Results: The 3-month colectomy rate in the base scenario where all 5,000 patients received standard infliximab induction was 23%. The best-performing management strategy assigned high-risk patients to sequential Janus kinase inhibitor inhibition and mediumrisk patients to accelerated infliximab induction. Using a 90% area under the curve (AUC) prediction model and optimistic treatment efficacy assumptions, this strategy reduced the 3-month colectomy rate to 8% (65% residual risk reduction). Using an 80% AUC prediction model with only modest treatment efficacy assumptions, the 3-month colectomy rate was reduced to 15% (35% residual risk reduction). Overall management strategy efficacy was highly dependent on predictive model accuracy and underlying treatment efficacy assumptions. Conclusions This is the first study to simulate predictive model-based management strategies in steroid-refractory ASUC and evaluate their effect on short-term colectomy rates. Future studies on predictive model development should incorporate simulation studies to better understand their expected benefit.

Background/Aims: Robust management algorithms are required to reduce the residual risk of colectomy in acute severe ulcerative colitis (ASUC) refractory to standard infliximab salvage therapy. The aim of this study was to evaluate the performance and benefits of alternative ASUC management strategies using simulated prediction models of varying accuracy. Methods: This was a simulation-based modeling study using a hypothetical cohort of 5,000 steroid-refractory ASUC patients receiving standard infliximab induction. Simulated predictive models were used to risk-stratify patients and escalate treatment in patients at high risk of failing standard infliximab induction. The main outcome of interest was colectomy by 3 months. Results: The 3-month colectomy rate in the base scenario where all 5,000 patients received standard infliximab induction was 23%. The best-performing management strategy assigned high-risk patients to sequential Janus kinase inhibitor inhibition and mediumrisk patients to accelerated infliximab induction. Using a 90% area under the curve (AUC) prediction model and optimistic treatment efficacy assumptions, this strategy reduced the 3-month colectomy rate to 8% (65% residual risk reduction). Using an 80% AUC prediction model with only modest treatment efficacy assumptions, the 3-month colectomy rate was reduced to 15% (35% residual risk reduction). Overall management strategy efficacy was highly dependent on predictive model accuracy and underlying treatment efficacy assumptions. Conclusions This is the first study to simulate predictive model-based management strategies in steroid-refractory ASUC and evaluate their effect on short-term colectomy rates. Future studies on predictive model development should incorporate simulation studies to better understand their expected benefit.

Background/Aims: The residual risk of colectomy after infliximab salvage in steroid-refractory acute severe ulcerative colitis (ASUC) is required to inform the need for subsequent maintenance biologic therapy. The aim of this study was to determine the dynamic response of common serum biomarkers to infliximab salvage and assess their utility in predicting subsequent colectomy. Methods: A retrospective single-center cohort study was conducted on all patients who received infliximab salvage for steroid-refractory ASUC between January 1, 2010, and July 31, 2019. Biomarkers were assessed on admission and days 1 and 3 post infliximab, and included C-reactive protein (CRP)-albumin-ratio (CAR), CRP-lymphocyte-ratio (CLR), platelet-lymphocyte-ratio (PLR) and neutrophil-lymphocyte-ratio (NLR). Results: Of 94 patients (median age, 35 years; 67% of male), 20% required colectomy at 12 months. Biomarkers on day 3 post-infliximab best differentiated nonresponders, who had higher CRP, lower albumin and lower lymphocyte count (each P< 0.05). Day 3 predictive performance (area under the curve) for 12-month colectomy was best for CAR (0.871) and CLR (0.874), which were similar to Lindgren (0.829; P> 0.05) but superior to Mayo (0.726), partial Mayo (0.719), PLR (0.719), Ho index (0.714), NLR (0.675), Travis score (0.657) and endoscopic Mayo (0.609) (each P< 0.05). A day 3 CAR cutoff of 0.47 mg/g had 79% sensitivity, 80% specificity, 94% negative predictive value (NPV) to predict colectomy; while a day 3 CLR cutoff of 6.0 mg/109 had 84% sensitivity, 84% specificity, 96% NPV. Conclusions CAR and CLR measured on day 3 post infliximab salvage for steroid-refractory ASUC represent simple and routinely performed biomarkers that appear to be strong predictors of colectomy. Prospective studies are required to confirm the utility of these predictive scores.

Background/Aims: Assessment of quality of magnetic resonance enterography (MRE) in small bowel Crohn’s disease (CD) activity evaluation has received little attention. We assessed the impact of bowel distention and motion artifact on MRE activity indices in ileal CD. Methods: A cohort of patients who underwent contemporaneous MRE and colonoscopy for ileal CD assessment between 2014 and 2021 at 2 centers were audited. An abdominal radiologist blinded to clinical data reviewed each MRE, graded bowel distention and motion artifact upon a pre-specified 3-point scale and calculated the original magnetic resonance index of activity (MaRIA) and simplified MaRIA (sMaRIA), London index and CD MRE index (CDMI). Ileal endoscopic activity was graded via the Simplified Endoscopy Score for CD (SES-CD). The performance of MRE indices in discriminating active disease (SES-CD ≥3) stratified by MRE quality was measured by receiver operator characteristic analyses. Results: One hundred and thirty-seven patients had MRE and colonoscopy within a median of 16 days (range, 0–30 days) with 63 (46%) exhibiting active disease (SES-CD ≥3). Forty-four MREs (32%) were deemed low quality due to motion artifact and/or moderate to poor distention. Low-quality MREs demonstrated reduced discriminative performance between ileal SES-CD ≥3 and MRE indices (MaRIA 0.838 vs. 0.634, sMaRIA 0.834 vs. 0.527, CDMI 0.850 vs. 0.595, London 0.748 vs. 0.511, P<0.05 for all). Individually the presence of any motion artifact markedly impacted the discriminative performance (e.g., sMaRIA area under the curve 0.544 vs. 0.814, P<0.05). Conclusions Image quality parameters can significantly impact MRE disease activity interpretation. Quality metrics should be reported, enabling cautious interpretation in lower-quality studies.