Title :

A Novel 8-Predictors Signature to Predict Complicated Disease Course in Pediatric-onset Crohn's Disease: A Population-based Study.

Author(s) :

Sarter, Helene [Auteur]
Institut de Recherche Translationnelle sur l'Inflammation (INFINITE) - U1286
Registre EPIMAD
Savoye, Guillaume [Auteur]
Registre EPIMAD
Marot, Guillemette [Auteur]
Inria Lille - Nord Europe
METRICS : Evaluation des technologies de santé et des pratiques médicales - ULR 2694
Ley, Delphine [Auteur]
Hôpital Jeanne de Flandre [Lille]
Institut de Recherche Translationnelle sur l'Inflammation (INFINITE) - U1286
Turck, Dominique [Auteur]
Hôpital Jeanne de Flandre [Lille]
Institute for Translational Research in Inflammation - U 1286 [INFINITE]
Hugot, Jean-Pierre [Auteur]
Centre de recherche sur l'Inflammation [CRI (UMR_S_1149 / ERL_8252 / U1149)]
AP-HP Hôpital universitaire Robert-Debré [Paris]
Vasseur, Francis [Auteur]
Evaluation des technologies de santé et des pratiques médicales - ULR 2694 [METRICS]
Duhamel, Alain [Auteur]
METRICS : Evaluation des technologies de santé et des pratiques médicales - ULR 2694
Wils, Pauline [Auteur]
Centre Hospitalier Régional Universitaire [CHU Lille] [CHRU Lille]
Institute for Translational Research in Inflammation - U 1286 [INFINITE]
Princen, Fred [Auteur]
Colombel, Jean-Frédéric [Auteur]
Icahn School of Medicine at Mount Sinai [New York] [MSSM]
Gower-Rousseau, Corinne [Auteur]
Hôpital universitaire Robert Debré [Reims] [CHU Reims]
Registre EPIMAD
Institute for Translational Research in Inflammation - U 1286 [INFINITE]
Fumery, Mathurin [Auteur]
Registre EPIMAD

Journal title :

Inflammatory Bowel Diseases

Abbreviated title :

Inflamm Bowel Dis

Publication date :

2023-06-02

ISSN :

1536-4844

English keyword(s) :

inflammatory bowel disease
Crohn's disease
prognosis
complication
genetics
prediction

HAL domain(s) :

Sciences du Vivant [q-bio]

English abstract : [en]

Background The identification of patients at high risk of a disabling disease course would be invaluable in guiding initial therapy in Crohn’s disease (CD). Our objective was to evaluate a combination of clinical, serological, ...
Show more >Background The identification of patients at high risk of a disabling disease course would be invaluable in guiding initial therapy in Crohn’s disease (CD). Our objective was to evaluate a combination of clinical, serological, and genetic factors to predict complicated disease course in pediatric-onset CD. Methods Data for pediatric-onset CD patients, diagnosed before 17 years of age between 1988 and 2004 and followed more than 5 years, were extracted from the population-based EPIMAD registry. The main outcome was defined by the occurrence of complicated behavior (stricturing or penetrating) and/or intestinal resection within the 5 years following diagnosis. Lasso logistic regression models were used to build a predictive model based on clinical data at diagnosis, serological data (ASCA, pANCA, anti-OmpC, anti-Cbir1, anti-Fla2, anti-Flax), and 369 candidate single nucleotide polymorphisms. Results In total, 156 children with an inflammatory (B1) disease at diagnosis were included. Among them, 35% (n = 54) progressed to a complicated behavior or an intestinal resection within the 5 years following diagnosis. The best predictive model (PREDICT-EPIMAD) included the location at diagnosis, pANCA, and 6 single nucleotide polymorphisms. This model showed good discrimination and good calibration, with an area under the curve of 0.80 after correction for optimism bias (sensitivity, 79%, specificity, 74%, positive predictive value, 61%, negative predictive value, 87%). Decision curve analysis confirmed the clinical utility of the model. Conclusions A combination of clinical, serotypic, and genotypic variables can predict disease progression in this population-based pediatric-onset CD cohort. Independent validation is needed before it can be used in clinical practice.Show less >

Language :

Anglais

Audience :

Internationale

Popular science :

Non

Administrative institution(s) :

Université de Lille
CHU Lille

Collections :

• METRICS : Evaluation des technologies de santé et des pratiques médicales - ULR 2694

Submission date :

2023-11-15T01:52:07Z
2024-04-03T08:34:13Z