Questions and answers on immunization
Bibliographic record
Abstract
QUESTION: Does regular topical use of tacrolimus or pimecrolimus alter the antibody response to immunization? COMMENT: Atopic dermatitis (AD) is a common chronic inflammatory skin disease that causes significant suffering and has limited treatment options. Because of a perception by physicians and patients that topical tacrolimus (Protopic, Astellas Pharma Canada) and pimecrolimus (Elidel, Novartis Pharmaceuticals Canada Inc) are safer than steroid preparations, abetted by heavy direct-to-consumer advertising, these topical immunomodulators (TIMs) have been increasingly used as first-line therapy in paediatrics. TIMs are indicated for children two years and older with refractory AD, or those who have experienced local or systemic side effects with topical steroids. TIMs act by suppressing T cell and mast cell activation, inhibiting inflammatory cytokine release and downregulating aberrant expression of high-affinity immunoglobulin E receptors on Langerhans cells. In early 2005, public attention was focused on these new medications when the United States Food and Drug Administration posted an advisory warning of a potential cancer risk from the use of TIMs (1,2). This advisory was based on animal studies, case reports in a small number of patients and mechanisms of action of the drugs. Beyond the possible cancer risk, many other questions are now being raised concerning these new medications, including whether TIMs have any effect on the immune response following immunization.
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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 | 0.004 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.019 | 0.008 |
| Insufficient payload (model declined to judge) | 0.137 | 0.046 |
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".