OC6 Sustained increase in paediatric inflammatory bowel disease incidence across the South-West of the United Kingdom over the last 10 years
Notice bibliographique
Résumé
<h3></h3> Paediatric inflammatory bowel disease (pIBD) incidence has increased over the last 25-years.<sup>1</sup> Datasets demonstrating this change in the United Kingdom have come from single centres or regions.<sup>2 3</sup> Heterogeneity is described in national and international cohorts; particularly in age group and disease subtype.<sup>1 4</sup> This work collected data over a greater population and multiple centres, in order to capture better resolution of incidence. We aimed to establish developing trends in incidence and highlight the demand for changes in service provision. Data were provided from five centres covering the South-West of the United Kingdom, with a total area at-risk population (<18-years) of 2,947,534.<sup>5</sup> Cases were retrieved for 2013–2022. Incident rates were calculated based on referral area populations, with temporal trends analysed through correlation. Subgroup analysis was undertaken for age groups - Very-Early Onset Inflammatory Bowel Disease (VEOIBD) (0–6 years); Early Onset Inflammatory Bowel Disease (EOIBD) (7–11 years); Paediatric-onset Inflammatory Bowel Disease (PIBD) (12–17 years) - gender and disease subtype. Choropleth maps were created for local districts (figure 1). In total 2,497 cases were diagnosed between 2013–2022, mean age 12.6 years (38.7% female). Diagnosis numbers increased from 187 to 376, with corresponding incidence rates of 6.0/100,000/year (2013) and 12.4/100,000/year (2022) (b=0.918, p<0.01) (table 1). Female IBD rose from 5.1/100,000/year (2013) to 11.0/100,000/year (2022) (b=0.865, p=0.01). Male rates increased from 5.7/100,000/year to 14.4/100,000/year (b=0.832, p=0.03). Crohn’s disease incidence increased from 3.1/100,000/year to 6.3/100,000/year (b=0.897, p<0.01). Ulcerative Colitis increased from 2.3/100,000/year to 4.3/100,000/year (b = 0.813, p=0.04). IBD-Unclassified (IBDU) rates also increased, 0.6/100,000/year to 1.8/100,000/year (b= 0.851, p=0.02). Statistically significant increases were seen in PIBD 11.2/100,000/year to 24.6/100,000/year (b=0.912, p<0.01), and EOIBD, with incidence rising from 4.4/100,000/year to 7.6/100,000/year (b=0.878, p=0.01). There was no statistically significant increase in VEOIBD (b=0.417, p=0.231). We demonstrate significant growth in pIBD incidence across a large geographical area and over multiple sites. We report continued increases, particularly in older children, across gender and disease subtype. We note stable incidence in VEOIBD. Rising incidence has significant implications for service provision for healthcare providers managing IBD. Further socioeconomic analysis of this cohort may provide greater insight into the causation of pIBD. <h3>References</h3> Kuenzig ME, Fung SG, Marderfeld L, <i>et al.</i> Twenty-first century trends in the global epidemiology of pediatric-onset inflammatory bowel disease: systematic review. <i>Gastroenterology</i> 2022;<b>162</b>:1147–59. doi:10.1053/J.GASTRO.2021.12.282 Ashton JJ, Barakat FM, Barnes C, <i>et al.</i> Incidence and prevalence of paediatric inflammatory bowel disease continues to increase in the South of England. <i>J Pediatr Gastroenterol Nutr</i> 2022;<b>75</b>:E20–4. doi:10.1097/MPG.0000000000003511 Hamilton B, Green H, Heerasing N, <i>et al.</i> Incidence and prevalence of inflammatory bowel disease in Devon, UK. <i>Frontline Gastroenterol</i> 2021;<b>12</b>:461–70. doi:10.1136/flgastro-2019–101369 Benchimol EI, Bernstein CN, Bitton A, <i>et al.</i> Trends in epidemiology of pediatric inflammatory bowel disease in Canada: distributed network analysis of multiple population-based provincial health administrative databases. <i>American Journal of Gastroenterology</i> 2017;<b>112</b>:1120–34. doi:10.1038/ajg.2017.97 Anon. Office for National Statistics - Census 2021. https://gov.wales/population-and-household-estimates-wales-census-2021. 2022.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».