The Argument Against a Biosimilar Switch Policy for Infliximab in Patients with Inflammatory Bowel Disease Living in Alberta
Bibliographic record
Abstract
A nonmedical switch policy is currently being considered in Alberta, which would force patients on originator biologics to biosimilar alternatives with the hypothetical aim of reducing costs to the health care system. The evidence to support the safety of nonmedical switching in patients with inflammatory bowel disease (IBD) is of low to very low quality; in fact, existing data suggest a potential risk of harm. In a pooled analysis of randomized controlled trials, one patient would lose response to infliximab for every 11 patients undergoing nonmedical switching. Switching to a biosimilar has important logistical and ethical implications including potential forced treatment changes without appropriate patient consent and unfairly penalizing patients living in rural areas and those without private drug insurance. Even in the best-case scenario, assuming perfectly executed switching without logistical delays, we predict switching 2,000 patients with Remicade will lead to over 60 avoidable surgeries in Alberta. Furthermore, nonmedical switching has not been adequately studied in vulnerable populations such as children, pregnant women, and elderly patients. While the crux of the argument for nonmedical switching is cost savings, biosimilar switching may not be cost effective: Particularly when originator therapies are being offered at the same price as biosimilars. Canadian patients with IBD have been surveyed, and their response is clear: They are not in support of nonmedical switching. Policies that directly influence patient health need to consider patient perspectives. Solutions to improve cost efficiency in health care exist but open, transparent collaboration between all involved stakeholders is required.
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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 | 0.005 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.006 | 0.009 |
| 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".