Temporal trends in the epidemiology of inflammatory bowel diseases in the public healthcare system in Brazil: A large population-based study
Notice bibliographique
Résumé
Background: Population-based data on epidemiology of Inflammatory Bowel Diseases (IBD) in Brazil is scarce. This study aims to define temporal trends of incidence and prevalence rates of Crohn’s disease (CD) and ulcerative colitis (UC) in Brazil. Methods: All IBD patients from the public healthcare national system were included from January 2012 to December 2020. Average Annual Percent Change (AAPC) and 95% confidence intervals (CI) were calculated using log-linear regression for incidence and binomial regression for prevalence. Moran’s I autocorrelation index was used to analyze clustering of cities by level of prevalence. Results: A total of 212,026 IBD patients. Incidence of IBD rose from 9.41 in 2012 to 9.57 per 100,000 in 2020 (AAPC=0.80%; 95% CI -0.37, 1.99); for UC, incidence increased from 5.69 to 6.89 per 100,000 (AAPC=3.04; 95% CI 1.51, 4.58) and for CD incidence decreased from 3.71 to 2.68 per 100,000 (AAPC=-3.24%; 95% CI -4.45, -2.02). Prevalence of IBD increased from 30.01 in 2012 to 100.13 per 100,000 in 2020 (AAPC=14.87%; CI 14.78-14.95); for UC, from 15.77 to 56.53 per 100,000 (AAPC=16.06%; CI 15.94, 16.17); for CD from 12.61 33.68 per 100,000 (AAPC=12.09% CI 11.95, 12.02). A south-north gradient was observed in 2020 prevalence rates of IBD [i=0.404052 (p<0.001)], CD [i=0.218942 (p<0.001)] and UC [i=0.416051 (p<0.001)]. Conclusions: Incidence of CD is decreasing whereas of UC is increasing, leading to stabilization in the incidence of IBD from 2012 to 2020 in Brazil. Prevalence of IBD has been climbing with 0.1% of Brazilians living with IBD in 2020. Funding Information: None Declaration of Interests: Quaresma AB has received honoraria for speaking from AbbVie, Apsen and Janssen. Aderson OMCD has received honoraria for speaking from AbbVie, Janssen, Pfizer, and Takeda; he has been a consultant for Takeda, AbbVie, and Janssen. Coy CSR has no conflicts of interest. Magro DO has no conflicts of interest. Hino AAF has no conflicts of interest. Valverde DA is CEO of Techtrials a Healthcare Data Science Company. Panaccione R reports consulting from AbbVie, Abbott, Alimentiv (formerly Robarts), Amgen, Arena Pharmaceuticals, AstraZeneca, Bristol-Myers Squibb, Boehringer Ingelheim Celgene, Celltrion, Cosmos Pharmaceuticals, Eisai, Elan, Eli Lilly, Ferring, Galapagos, Genentech, Gilead Sciences, Glaxo-Smith Kline, Janssen, Merck, Mylan, Oppilan Pharma, Pandion Pharma, Pfizer, Progenity, Protagonist Therapeutics, Roche, Satisfai Health, Sandoz, Schering-Plough, Shire, Sublimity Therapeutics, Theravance Biopharma, UCB, and Takeda Pharmaceuticals. He has received speaker’s fees from AbbVie, Arena Pharmaceuticals, Celgene, Eli Lilly, Ferring, Gilead Sciences, Janssen, Merck, Pfizer, Roche, Sandoz, Shire, and Takeda Pharmaceuticals. Coward SB has no conflicts of interest. Ng SC has received consulting and speaker fees from AbbVie, Ferring, Janssen, Menarini, and Takeda; served as a Scientific Advisory Board member for AbbVie, Ferring, and Takeda; and received research grants from AbbVie, Ferring, and Janssen. Kaplan GG has received honoraria for speaking or consultancy from AbbVie, Janssen, Pfizer, Amgen, and Takeda. He has received research support from Ferring, Janssen, AbbVie, GlaxoSmith Kline, Merck, and Shire. He has been a consultant for Gilead. He shares ownership of a patent: TREATMENT OF INFLAMMATORY DISORDERS, AUTOIMMUNE DISEASE, AND PBC. UTI Limited Partnership, assignee. Patent WO2019046959A1. PCT/CA2018/051098. 7 Sept. 2018. Kotze PG has received consulting and speaker fees from AbbVie, Janssen, Pfizer, Takeda and Takeda. He also received scientific grants from Pfizer and Takeda Ethics Approval Statement: This study was approved by the Research Ethics Committee of the University of the West of Santa Catarina (UNOESC), in accordance with the Certificate of Presentation for Ethical Appreciation (CAAE) 97905918.7.0000.5367. During all stages of this research, all guidelines of Resolution 466/2012 of the National Health Council were strictly followed and complied.
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 enseignantsNi 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.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 source (Gemma direct ou Codex distillé), 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 ».