Formulary Management of Biologics in Plaque Psoriasis
Bibliographic record
Abstract

 Unlike the new-generation biologics (interleukin [IL]-17 and IL-23 inhibitors), all old-generation biologics (anti–tumour necrosis factor [TNF] and anti–IL-12/23 biologics) for plaque psoriasis (PsO) have now lost their exclusivity status and most were launched prior to the pan-Canadian Pharmaceutical Alliance. In addition, biosimilar versions of the old-generation biologics have had limited uptake and delayed launches in Canada spanning multiple years, suggesting a significant opportunity cost paid for these drugs after loss of exclusivity.
 Modern clinical evidence, which is more rigorous than the evidence supporting the old-generation drugs and includes head-to-head trials comparing IL-17 and IL-23 inhibitors with anti-TNF and anti–IL-12/23 biologics, have demonstrated greater efficacy with the new-generation biologics.
 In Canada, despite access to newer and more efficacious treatments, physicians continue to prescribe old-generation drugs to patients newly initiating a biologic for PsO (25% of patients in 2020), and the new-generation biologics are also less costly on an average per patient basis at list price compared with the most utilized old-generation biologic (ustekinumab).
 Public payers have spent $28 million (at list price) on biologics initiated for PsO beyond their loss of exclusivity from 2016 to 2020 ($600 million for biologics initiated for any indication), and that figure is likely much higher today. Notably, some IL-17 biologics will lose data protection within the next 2 years, which will further increase this opportunity cost.
 It is prudent that decision-makers review the place in therapy of biologics for PsO. Based on the findings of this report, the policy recommendation is to assess the clinical and economic value of old-generation biologics in the context of current evidence standards in PsO. The promotion of the use of new-generation biologics should be considered by payers to support the appropriate use of biologics in PsO, which would improve patient outcomes with budget savings or neutrality (assuming no confidential pricing agreements with the old-generation biologics) versus the status quo.
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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 | 0.001 | 0.000 |
| 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 | 0.000 | 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".