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Record W4410019431 · doi:10.1038/s41586-025-08940-0

Global evolution of inflammatory bowel disease across epidemiologic stages

2025· article· en· W4410019431 on OpenAlexafffund
Lindsay Hracs, Joseph W. Windsor, Julia Gorospe, Stephanie Coward, Michael Buie, Joshua Quan, Quinn Goddard, Léa Caplan, Ante Markovinović, Tyler Williamson, Yvonne Abbey, Murdani Abdullah, María T. Abreu, Vineet Ahuja, Raja Affendi Raja Ali, Mansour Altuwaijri, Domingo Balderramo, Rupa Banerjee, Eric I. Benchimol, Çharles N. Bernstein, Eduard Brunet, Johan Burisch, Vui Heng Chong, Iris Dotan, Usha Dutta, Sara El Ouali, Angela Forbes, Anders Forss, Richard B. Gearry, Hang Viet Dao, Juanda Leo Hartono, Ida Hilmi, Phoebe Hodges, Gareth‐Rhys Jones, Fabián Juliao Baños, Jamilya Kaibullayeva, Paul Kelly, Taku Kobayashi, Paulo Gustavo Kotze, Péter L. Lakatos, Charlie W. Lees, Julajak Limsrivilai, Bobby Lo, Edward V. Loftus, Jonas F. Ludvigsson, Joyce Wing Yan Mak, Yinglei Miao, Ka Kei Ng, Shinji Okabayashi, Ola Olén, Remo Panaccione, Mukesh S Paudel, Abel Botelho Quaresma, David T. Rubin, Marcellus Simadibrata, Yang Sun, Hidekazu Suzuki, Martín Toro, Dan Turner, Beatriz Iade, Shu‐Chen Wei, Jesús K. Yamamoto‐Furusho, Suk‐Kyun Yang, Siew C. Ng, Gilaad G. Kaplan

Bibliographic record

VenueNature · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInflammatory Bowel Disease
Canadian institutionsUniversity of ManitobaMcGill UniversityUniversity of CalgaryInstitute for Clinical Evaluative SciencesSickKids FoundationUniversity of Toronto
FundersCilagJanssen PharmaceuticalsCanadian Institutes of Health ResearchGenentechBausch HealthKarolinska InstitutetAstellas PharmaCelltrionEisaiMitsubishi Tanabe Pharma CorporationKisseiMylanDouglas PharmaceuticalsLeona M. and Harry B. Helmsley Charitable TrustEA Pharma Co., Ltd.National Cancer InstituteGilead SciencesImpact FundSanofiCelgenePfizerBiogenHong Kong GovernmentGlaxoSmithKlineEli Lilly and CompanyBristol-Myers SquibbAstraZenecaTillotts PharmaAmgenHospital for Sick Children
KeywordsIncidence (geometry)DemographyPopulationInflammatory bowel diseaseDiseaseLatin AmericansDeveloped countryMedicineGeographyEnvironmental healthPathology

Abstract

fetched live from OpenAlex

During the twentieth century, inflammatory bowel disease (IBD) was considered a disease of early industrialized regions in North America, Europe and Oceania1. At the turn of the twenty-first century, IBD incidence increased in newly industrialized and emerging regions in Africa, Asia and Latin America, while the prevalence in early industrialized regions continued to grow steadily2–4. Changes in the incidence and prevalence denote the evolution of IBD across four epidemiologic stages: stage 1 (emergence), characterized by low incidence and prevalence; stage 2 (acceleration in incidence), marked by rapidly rising incidence and low prevalence; and stage 3 (compounding prevalence), where the incidence decelerates, plateaus or declines while the prevalence steadily increases. A fourth stage (prevalence equilibrium) has been proposed in which the prevalence slope plateaus due to demographic shifts in an ageing IBD population, but it has not yet been evidenced. To date, these stages have remained theoretical, lacking specific numerical indicators to define transition points. Here, using real-world data from 522 population-based studies encompassing 82 global regions and spanning more than a century (1920–2024), we show spatiotemporal transitions across stages 1–3 and model stage 4 progression. Understanding the evolution of IBD across epidemiologic stages enables healthcare systems to better anticipate the future worldwide burden of IBD. An analysis of data from 522 population-based studies encompassing 82 global regions and spanning more than a century (1920–2024) shows spatiotemporal transitions across epidemiologic stages 1 to 3 of inflammatory bowel disease, and models stage 4 progression.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score0.703

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.004
GPT teacher head0.284
Teacher spread0.280 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations308
Published2025
Admission routes2
Has abstractyes

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