Dosing of Biologics in Juvenile Idiopathic Arthritis: Is the Sky the Limit?
Bibliographic record
Abstract
In the past decade, biologic therapy has been a valuable new option in the treatment of both adult and pediatric rheumatic diseases. Many patients previously refractory to anti-rheumatic drugs have shown excellent responses to biologic therapy. However, there remains a significant minority of patients who do not respond to these drugs or who lose efficacy after a period of successful treatment. Why are some patients with inflammatory arthritis primary or secondary nonresponders? Part of the problem is likely due to the heterogeneous nature of the disease. But insufficient dosing might be an issue for some patients. In drug research, dosing is evaluated by pharmaco-dynamic and pharmacokinetic (PK) models and then tested in humans for a safe dosage range and possible side effects before a drug is tested for its efficacy1,2. Unfortunately, a large proportion of medicines (50–90%) used in children are prescribed outside the terms of the drug license, i.e., off-label, which can place children at a direct risk of under- or overdosing and a delayed risk of longterm adverse effects3. The US Food and Drug Administration (FDA) has provided an incentive to US pharmaceutical companies since 1997 to study products that could be beneficial for the pediatric population3,4. The European Union (EU) enforced the Paediatric Regulation in 20075. The goals of the EU legislation are similar to those of US pediatric legislation: to improve children’s health through advancements in research and to provide a new framework for evaluating the efficacy and safety of medicines for children3,6. However, in the EU, … Address correspondence to Dr. F.H.M. Prince, Academic Medical Centre, Emma Children’s Hospital, Department of Pediatrics, H7-270, Meibergdreet 9, Amsterdam, 1105 A2, the Netherlands. E-mail: femkeprince{at}gmail.com
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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 | 0.025 | 0.057 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.005 | 0.010 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".