Practical Management of Biosimilar Use in Inflammatory Bowel Disease (IBD): A Global Survey and an International Delphi Consensus
Bibliographic record
Abstract
As the patents for biologic originator drugs expire, biosimilars are emerging as cost-effective alternatives within healthcare systems. Addressing various challenges in the clinical management of inflammatory bowel disease (IBD) remains crucial. To shed light on physicians' current knowledge, beliefs, practical approaches, and concerns related to biosimilar adoption-whether initiating a biosimilar, transitioning from an originator to a biosimilar, or switching between biosimilars (including multiple switches and reverse switching)-a global survey was conducted. Fifteen physicians with expertise in the field of IBD from 13 countries attended a virtual international consensus meeting to develop practical guidance regarding biosimilar adoption worldwide, considering the survey results. This consensus centered on 10 key statements covering biosimilar effectiveness, safety, indications, rationale, multiple switches, therapeutic drug monitoring of biosimilars, non-medical switching, and future perspectives. Ultimately, the consensus affirmed that biosimilars are equally effective and safe when compared to originator drugs. They are considered suitable for both biologic-naïve patients and those who have previously been treated with originator drugs, with cost reduction being the primary motivation for transitioning from an originator drug to a biosimilar.
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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 | 0.076 | 0.056 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".