Prevalence, Characteristics, Management, and Outcomes of Difficult-to-Treat Inflammatory Bowel Disease
Bibliographic record
Abstract
BACKGROUND AND AIMS: Criteria for "difficult-to-treat" inflammatory bowel disease (DTT-IBD) have recently been proposed to standardize terminology. We aimed to evaluate the prevalence, characteristics, management, and outcomes of DTT-IBD. METHODS: We conducted a retrospective study in 2 tertiary centers in Italy. RESULTS: Among 1736 IBD patients treated with biologics/advanced small molecules, 430 (24.8%) met at least 1 DTT-IBD criterion, of which 331 (77%) failed at least 2 mechanisms of action. In ulcerative colitis (UC), left-sided and extended colitis were risk factors for DTT compared to proctitis (odds ratio [OR] 6.55; 95% confidence interval [CI], 1.93-40.98; p = 0.011 and OR 10.12; 95% CI, 3.01-63.14; p = 0.002, respectively). In Crohn's disease (CD), multiple localizations (L3+L4) (OR 3.04; 95% CI, 1.09-8.34; p = 0.03), stricturing (OR 2.24; 95% CI, 1.52-3.34; p < 0.001), and penetrating (OR 2.33; 95% CI, 1.55-3.53; p < 0.001) behaviors, and perianal disease (OR 2.49; 95% CI, 1.75-3.53; p < 0.001) were the main risk factors for DTT. Delay in advanced treatment initiation was positively associated with DTT-CD (OR 1.74; 95% CI, 1.27-2.41; p = 0.001) but protective in UC (OR 0.65; 95% CI, 0.45-0.93; p = 0.019). The rates of symptomatic, biochemical, and endoscopic remission were lower in DTT-IBD compared to non-DTT-IBD. The difference was most evident for endoscopic remission (25% vs 62%). Drug persistency in each following line of treatment progressively decreased in CD and UC. All advanced drugs used in DTT-IBD had similar persistence. CONCLUSIONS: DTT-IBD was prevalent in approximately one-quarter of patients with IBD in a tertiary care setting. Certain IBD phenotypes and the delay in initiating treatment in CD were risk factors for DTT. Drug persistency decreased progressively with every subsequent line of therapy.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".