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Enregistrement W4323351151 · doi:10.1093/jcag/gwac036.035

A35 FORECASTING THE INCIDENCE AND PREVALENCE OF INFLAMMATORY BOWEL DISEASE: A CANADIAN NATION-WIDE ANALYSIS

2023· article· en· W4323351151 sur OpenAlexaffabout
Stephanie Coward, Eric I. Benchimol, Çharles N. Bernstein, J. Antonio Aviña‐Zubieta, Alain Bitton, Lindsay Hracs, J. B. Jones, E Kuenzig, L. Lu, Sanjay K. Murthy, Zoann Nugent, Anthony Otley, Remo Panaccione, Juan Nicolás Peña-Sánchez, Harmeet Singh, Laura E. Targownik, Joseph W. Windsor, Gilaad G. Kaplan

Notice bibliographique

RevueJournal of the Canadian Association of Gastroenterology · 2023
Typearticle
Langueen
DomaineBiochemistry, Genetics and Molecular Biology
ThématiqueInflammatory Bowel Disease
Établissements canadiensUniversity of SaskatchewanUniversity of TorontoDalhousie UniversityUniversity of CalgaryMcGill UniversityHospital for Sick ChildrenUniversity of British ColumbiaOttawa HospitalResearch CanadaUniversity of Manitoba
Organismes subventionnairesnon disponible
Mots-clésIncidence (geometry)EpidemiologyMedicineDemographyPoisson regressionPopulationConfidence intervalInflammatory bowel diseaseDiseaseEnvironmental healthInternal medicineMathematics

Résumé

récupéré en direct d'OpenAlex

Abstract Background Canada is currently in the third epidemiological stage in the evolution of IBD: compounding prevalence. A high incidence of IBD, in conjunction with low mortality, leads to a steadily rising prevalence over time. By understanding historical epidemiological trends, we can forecast incidence and prevalence into the future to inform healthcare systems in Canada of the rising burden of IBD to society. Purpose To analyze past epidemiological trends in order to forecast the overall incidence and prevalence of IBD, Crohn’s disease (CD), and ulcerative colitis (UC) and stratified by age (<18, 18-64, 65+). Method Canadian population-based administrative data was acquired from: AB, BC, SK, MB, QC, and ON. Data were age and sex standardized to the matching year and provincial data aggregated into a representative sample of the Canadian population for prevalence (2002-2014) and incidence (2007-2014: 5-year washout period). Incidence and prevalence (per 100,000 persons) were calculated, with 95% confidence intervals (CI), using Canadian population estimates from Statistics Canada for IBD, CD, UC (IBD-unclassifiable+UC). Autoregressive Integrated Moving Average models were created, and rates forecasted from 2014 to 2035 with 95% prediction intervals (PI). Poisson (or negative binomial) for incidence and log binomial regression for prevalence estimated the Average Annual Percentage Change (AAPC), with 95% CIs, of the forecasted data. Result(s) The 2014 incidence of IBD in Canada was 28.4 per 100,000 (95%CI: 27.8, 29.0) and forecasted to significantly increase (AAPC: 0.58%; 95%CI: 0.04, 1.04) from 30.0 per 100,000 in 2023 to 32.1 (95%PI: 27.9, 36.3) in 2035. Pediatric onset IBD was 13.9 per 100,000 (95%CI: 13.0, 14.9) in 2014 and is forecasted to significantly increase to 18.0 per 100,000 (95%PI: 15.7, 20.2) in 2035 with an AAPC of 1.23% (95%CI: 0.76, 1.63). Adult and elderly onset incidence rates were forecasted to remain stable. Prevalence of IBD increased between 2002 (389 per 100,000) and 2014 (636 per 100,000) and is forecasted to continue to climb by an AAPC of 2.44% (95%CI: 2.34, 2.53). In 2023, the prevalence of IBD is 825 per 100,000. By 2035 prevalence is forecasted to climb to 1075 per 100,000 (95%PI: 1047, 1103) with 470,000 Canadians living with IBD. Prevalence across all age strata were forecasted to significantly increase. The highest AAPC was seen in the elderly (2.76%; 95%CI: 2.73, 2.79) with a prevalence of 841 per 100,000 (95%CI: 834, 849) in 2014 and forecasted to climb to 1534 per 100,000 (95%PI: 1519, 1550) in 2035. Image Conclusion(s) Incidence of IBD continues to rise in Canada, driven by pediatric-onset IBD. In 2023, over 320,000 Canadians (0.83%) will be living with IBD. By 2035 prevalence will exceed 1% of the population with approximately 470,000 individuals in Canada with IBD. Future research should establish the environmental determinates of IBD that may influence temporal trends in the incidence of IBD, while healthcare systems adapt to the compounding prevalence of IBD. Please acknowledge all funding agencies by checking the applicable boxes below CIHR, Other Please indicate your source of funding; The Leona M. and Harry B. Helmsley Charitable Trust Disclosure of Interest S. Coward: None Declared, E. Benchimol Consultant of: Hoffman La-Roche Limited and Peabody & Arnold LLP for matters unrelated to medications used to treat inflammatory bowel disease and McKesson Canada and the Dairy Farmers of Ontario for matters unrelated to medications used to treat inflammatory bowel disease., C. Bernstein Grant / Research support from: Unrestricted educational grants from Abbvie Canada, Janssen Canada, Pfizer Canada, Bristol Myers Squibb Canada, and Takeda Canada. Has received research grants from Abbvie Canada, Amgen Canada, Pfizer Canada, and Sandoz Canada and contract grants from Janssen, Abbvie and Pfizer, Consultant of: Abbvie Canada, Amgen Canada, Bristol Myers Squibb Canada, JAMP Pharmaceuticals, Janssen Canada, Pfizer Canada, Sandoz Canada, and Takeda., Speakers bureau of: Abbvie Canada, Janssen Canada, Pfizer Canada and Takeda Canada, J. A. Avina-Zubieta: None Declared, A. Bitton: None Declared, L. Hracs: None Declared, J. Jones Consultant of: Janssen, Abbvie, Pfizer, Takeda, Speakers bureau of: Janssen, Abbvie, Pfizer, Takeda, E. Kuenzig: None Declared, L. Lu: None Declared, S. Murthy: None Declared, Z. Nugent: None Declared, A. Otley Grant / Research support from: Unrestricted educational grants from AbbVie Canada and Janssen Canada, Consultant of: Advisory boards of AbbVie Canada, Janssen Canada and Nestle, R. Panaccione Consultant of: Abbott, AbbVie, Alimentiv (formerly Robarts), Amgen, Arena Pharmaceuticals, AstraZeneca, Biogen, Boehringer Ingelheim, Bristol-Myers Squibb, Celgene, Celltrion, Cosmos Pharmaceuticals, Eisai, Elan, Eli Lilly, Ferring, Galapagos, Fresenius Kabi, Genentech, Gilead Sciences, Glaxo-Smith Kline, JAMP Bio, Janssen, Merck, Mylan, Novartis, Oppilan Pharma, Organon, Pandion Pharma, Pendopharm, Pfizer, Progenity, Protagonist Therapeutics, Roche, Sandoz, Satisfai Health, Shire, Sublimity Therapeutics, Takeda Pharmaceuticals, Theravance Biopharma, Trellus, Viatris, UCB. Advisory Boards for: AbbVie, Alimentiv (formerly Robarts), Amgen, Arena Pharmaceuticals, AstraZeneca, Biogen, Boehringer Ingelheim, Bristol-Myers Squibb, Celgene, Eli Lilly, Ferring, Fresenius Kabi, Genentech, Gilead Sciences, Glaxo-Smith Kline, JAMP Bio, Janssen, Merck, Mylan, Novartis, Oppilan Pharma, Organon, Pandion Pharma, Pfizer, Progenity, Protagonist Therapeutics, Roche, Sandoz Shire, Sublimity Therapeutics, Takeda Pharmaceuticals, Speakers bureau of: AbbVie, Amgen, Arena Pharmaceuticals, Bristol-Myers Squibb, Celgene, Eli Lilly, Ferring, Fresenius Kabi, Gilead Sciences, Janssen, Merck, Organon, Pfizer, Roche, Sandoz, Shire, Takeda Pharmaceuticals, J.-N. Pena-Sanchez: None Declared, H. Singh Consultant of: Pendopharm, Amgen Canada, Bristol Myers Squibb Canada, Roche Canada, Sandoz Canada, Takeda Canada, and Guardant Health, Inc., L. Targownik Grant / Research support from: Investigator initiated funding from Janssen Canada, Consultant of: [Advisory board] AbbVie Canada, Takeda Canada, Merck Canada, Pfizer Canada, Janssen Canada, Roche Canada, and Sandoz Canada, J. Windsor: None Declared, G. Kaplan Grant / Research support from: Ferring, Janssen, AbbVie, GlaxoSmith Kline, Merck, and Shire, Consultant of: Gilead, Speakers bureau of: AbbVie, Janssen, Pfizer, Amgen, and Takeda

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,003
score de la tête « metaresearch » (Gemma)0,008
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Simulation ou modélisation · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,028
Score d'incertitude au seuil0,205

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0030,008
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0010,002
Bibliométrie0,0040,007
Études des sciences et des technologies0,0010,000
Communication savante0,0020,000
Science ouverte0,0020,001
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0030,000

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.

Tête enseignante Opus0,007
Tête enseignante GPT0,209
Écart entre enseignants0,202 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSimulation ou modélisation
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations4
Publié2023
Routes d'admission2
Résumé présentoui

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