P722 Symptom-based disease trajectories Identify a population of early super-responders in ulcerative colitis achieving complete disease control under targeted therapy

Tran, F.(1,2)*;Brard, R.(3);Flechsenhar, K.(4);Aden, K.(1,2);Rosenstiel, P.(2);Agueusop, I.(3);Schreiber, S.(1,2);

(1)University Medical Center Schleswig-Holstein, Department of Internal Medicine I, Kiel, Germany;(2)University Medical Center Schleswig-Holstein, Institute of Clinical Molecular Biology, Kiel, Germany;(3)Sanofi, Biostatistics & Programing- Early Development & Research Statistics, Frankfurt am Main, Germany;(4)Sanofi, Immunology and Inflammation Therapeutic Area- Type 1/17 Immunology Cluster, Frankfurt am Main, Germany;


Clinical trials with advanced therapies typically document the efficacy of induction and maintenance therapies as landmark endpoints. In ulcerative colitis (UC), independent assessments of clinical remission, endoscopic improvement, inflammatory biomarker, and histologic response are used, while little is known about the individual patient benefit. Disease control (DC) as a composite of symptomatic, biochemical, and morphologic remission becomes important to achieve for patients. By analysing their symptom trajectories towards the new outcome DC, distinct subpopulations of the seemingly uniform therapy response phenotype in UC can be identified. In a prospective cohort, we investigate UC patients using symptoms (i.e., partial Mayo Clinical Score (PCMS)) to detect different trajectories that may lead to DC.


231 UC patients from Kiel Campus of University Hospital Schleswig-Holstein receiving first time induction and maintenance therapy with anti-TNF, anti-IL-12/23, anti-Integrin or JAK inhibitors (JAKi) between 2010-2022 were enrolled. Patients were assigned by clinical choice to their therapy and received standard care: Symptoms were assessed by PCMS with laboratory investigations at each visit (every 4-12 weeks) and endoscopies (at week 0, 14, 52) were evaluated using Mayo endoscopic score (eMayo) and histology assessment with Nancy index (NI). We defined DC at week 52 (DC52) as the combination of eMayo =0, NI =0-1, PMCS =0-1, C-reactive protein <5 mg/l and leucocyte counts 2.5-12/nl. We performed ANOVA and unpaired Wilcoxon tests at each timepoint as well as ROC analyses to identify thresholds discriminating different trajectories.


24.2% (56) of patients achieved DC52, while 25.6% (59) reached week 52 without DC and 50.2% (116) changed therapy within 52 weeks due to inefficacy. We identified an early separation of PMCS trajectories between DC52 (2.07, ±0.27SEM) vs. non-DC52 (3.49, ±0.27SEM) already 6 weeks after induction (p <0.001; Figure 1&2). At week 6, PMCS ≤2 (41.76% vs. 14.06%; sensitivity 0.47, specificity 0.76) and PMCS change from baseline >3 (40.24% vs. 16.92%; sensitivity 0.79, specificity 0.60) were associated with higher rates of DC52 vs. non-DC52. Linking DC52 with prospective outcomes, we observed higher rates of clinical remission (75.00% vs. 27.12%) and DC at week 104 (57.14% vs. 20.34%) in DC52 vs. non-DC52.


In this real-world cohort, DC52 was characterized by early drop of PMCS and a higher likelihood of DC until week 104. While our results await replication, the observation of discrete super-response trajectories leading to DC could give rise to algorithmic trials investigating early change of therapy for patients not joining an ideal trajectory as early as week 6.