P0817 Large-scale clustering of longitudinal faecal calprotectin and C-reactive protein profiles in Scottish and Danish inflammatory bowel disease

Abstract Background Despite major advances in our understanding of the molecular underpinning of IBD, we remain challenged in deciphering the observed disease heterogeneity. Attempts to characterise longitudinal disease behaviour have either been restricted to symptom-based profiling - as exemplified in the IBSEN cohorts - or reliance on stochastic endpoints of disease “progression” such as hospitalisation, surgery and fibrosis. Here we present a novel method to examine IBD disease behaviour by modelling longitudinal inflammatory patterns in two large, well-characterised cohorts. Methods We conducted a retrospective study in two population cohorts, the Lothian IBD Registry (LIBDR),1 based in Scotland, and IBD patients described in national Danish registries.2,3 Using latent class mixed models,4 we independently clustered subjects by their FC and CRP profiles across 7 and 5 year post-diagnosis for the Lothian and Danish data respectively. The number of assumed clusters for the Danish models were dictated by the number chosen for the LIBDR data. Montreal classification was available for the LIBDR, and prescribing data were available for both cohorts. Results 1036 LIBDR subjects (544 CD, 492 UC/IBDU) and 7880 Danish subjects (3931 CD, 3949 UC) were included in the FC analysis. In the LIBDR, 10545 (median 9 per subject, IQR 6–13) FC observations were available, with 67986 observations available in the Danish registry (7, 4-11). For the CRP analysis, 1838 (805 CD, 1033 UC/IBDU) LIBDR subjects and 10041 (4415 CD, 5626) Danish subjects were included, with 49364 (median 20, IQR 10-36) and 241689 (19, 9-32) CRP observations respectively. When modelling the FC data, we found eight clusters (Figure 1), with the major clusters (FC1-4,7,8) replicating in the Danish data (Figure 2). The longitudinal trajectories characterising the clusters appear to reflect commonly reported clinical behaviours (e.g rapid remitters, delayed remitters, relapsing remitters and non-remitters). No association was found between ileal vs a colonic disease and cluster assignment. The use and timing of advanced therapies differed by cluster with rapid remitters more likely to receive therapy earlier in the disease course. However, prescribing trends described only a proportion of cluster assignments. When modelling the CRP data, we again found eight clusters, although there was broadly poor agreement between FC and CRP clusters. The follow-up required for reliable cluster assignments depended on the shape of the trajectories. Conclusion Distinct patterns of inflammatory behaviour over time are evident in patients with IBD. These data pave the way for a deeper understanding of disease heterogeneity in IBD and enhanced patient stratification in the clinic. References 1.Jones GR, Lyons M, Plevris N, et al. IBD prevalence in Lothian, Scotland, derived by capture–recapture methodology. Gut. 2019;68(11):1953-1960. doi:10.1136/gutjnl-2019-318936 2.Arendt JFH, Hansen AT, Ladefoged SA, Sørensen HT, Pedersen L, Adelborg K. Existing data sources in clinical epidemiology: Laboratory information system databases in Denmark. Clin Epidemiol. 2020;Volume 12:469-475. doi:10.2147/CLEP.S245060 3.Vestergaard MV, Allin KH, Poulsen GJ, Lee JC, Jess T. Characterizing the pre-clinical phase of inflammatory bowel disease. Cell Rep Med. 2023;4(11):101263. doi:10.1016/j.xcrm.2023.101263 4.Proust-Lima C, Philipps V, Liquet B. Estimation of extended mixed models using latent classes and latent processes: The R package lcmm. J Stat Softw. 2017;78(2):1-56. doi:10.18637/jss.v078.i02

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