Combined Biologic and Immunomodulatory Therapy is Superior to Monotherapy for Decreasing the Risk of Inflammatory Bowel Disease-Related Complications
Bibliographic record
Abstract
BACKGROUND AND AIMS: The combination of infliximab and azathioprine is more efficacious than either therapy alone for Crohn's disease [CD] and ulcerative colitis [UC]. However, it is uncertain whether these benefits extend to real-world clinical practice and to other combinations of biologics and immunomodulators. METHODS: We collected health administrative data from four Canadian provinces representing 78 413 patients with inflammatory bowel disease [IBD] of whom 11 244 were prescribed anti-tumour necrosis factor [anti-TNF] agents. The outcome of interest was the first occurrence of treatment failure: an unplanned IBD-related hospitalization, IBD-related resective surgery, new/recurrent corticosteroid use or anti-TNF switch. Multivariable Cox proportional hazards modelling was used to assess the association between the outcome of interest and receiving combination therapy vs anti-TNF monotherapy. Multivariable regression models were used to assess the impact of choice of immunomodulator or biologic on reaching the composite outcome, and random effects generic inverse variance meta-analysis of deterministically linked data was used to pool the results from the four provinces to obtain aggregate estimates of effect. RESULTS: In comparison with anti-TNF monotherapy, combination therapy was associated with a significant decrease in treatment ineffectiveness for both CD and UC (CD: adjusted hazard ratio [aHR] 0.77, 95% confidence interval [CI] 0.66-0.90; UC: aHR 0.72, 95% CI 0.62-0.84). Combination therapy was equally effective for adalimumab and infliximab in CD. In UC azathioprine was superior to methotrexate as the immunomodulatory agent (aHR = 1.52 [95% CI 1.02-2.28]) but not CD (aHR = 1.22 [95% CI 0.96-1.54]). CONCLUSION: In an analysis of a database of real-world patients with IBD, combination therapy decreased the likelihood of treatment failure in both CD and UC.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".