Long-term disease course of ulcerative colitis in a prospective European population-based inception cohort—an Epi-IBD cohort study
Bibliographic record
Abstract
BACKGROUND AND AIMS: The Epi-IBD cohort is a population-based inception cohort of patients with inflammatory bowel disease from 22 European centers. The aim was to assess the 10-year disease course of patients with ulcerative colitis (UC) across Europe. METHODS: Patients were followed prospectively from the time of diagnosis in 2010 and 2011, with a uniform collection of data to the end of 2020. Associations between covariates and colectomy, progression to extensive disease, and hospitalization were analyzed separately by multivariable Cox regression analyses in a propensity-score-matched subpopulation to address regional differences. RESULTS: A total of 873 UC patients were recruited (Eastern Europe: 196 [22.4%], Western Europe: 677 [77.5%]). The 10-year crude rate for the use of advanced therapy was comparable in Eastern (13%) and Western Europe (16%) (P > 0.9), and the median time from diagnosis until initiation of advanced treatment was similar, at 3 years. The need for colectomy remained comparable in Eastern and Western Europe, with a 10-year crude rate of 4% and 6% (Cox: P = 0.6), respectively. Likewise, disease progression to extensive disease (10-year rate: 17%, Cox: P = 0.06) and hospitalization (10-year rate: 23%, Cox: P = 0.2) were comparable across Europe. The use of advanced therapy and the early use of corticosteroids were both associated with an increased risk of colectomy (Cox: both P < 0.05). CONCLUSIONS: While the introduction of advanced therapies for UC has transformed the therapeutic landscape, their impact on colectomy rates, disease progression, and hospitalizations remains modest. Our findings highlight the need for continued innovation in UC treatment and the importance of individualized and targeted care to achieve optimal long-term outcomes.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".