Systematic review with meta‐analysis: prevalence, risk factors and costs of aminosalicylate use in Crohn's disease
Bibliographic record
Abstract
BACKGROUND: Aminosalicylates are the most frequently prescribed drugs for patients with Crohn's disease (CD), yet evidence to support their efficacy as induction or maintenance therapy is controversial. AIMS: To quantify aminosalicylate use in CD clinical trials, identify factors associated with use and estimate direct annual treatment costs of therapy. METHODS: MEDLINE, Embase and CENTRAL were searched to April 2017 for placebo-controlled trials in adults with CD treated with corticosteroids, immunosuppressants or biologics. The proportion of patients co-prescribed aminosalicylates in placebo arms was pooled using a random-effects model. Meta-regression was used to identify factors associated with aminosalicylate use. Annual treatment costs were estimated using the 2016 Ontario Drug Benefit Program. RESULTS: = 86.0%, 91.8% for induction and maintenance trials, respectively). In multivariable meta-regression, aminosalicylate use has decreased over time in induction trials (OR 0.50 [95% CI: 0.34-0.74] per 10-year increment). While a decline has been seen over time, 35% of CD patients were still using aminosalicylates in contemporary trials from the last 5 years. The estimated annual cost for the lowest price mesalazine (mesalamine) formulation is approximately $32 million for the Canadian CD population. CONCLUSIONS: Over one-third of CD patients entering clinical trials are still co-prescribed aminosalicylates. A definitive trial is needed to inform the conventional practice of using aminosalicylates as CD maintenance 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 | 0.014 | 0.038 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.018 | 0.053 |
| Bibliometrics | 0.007 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".