Bibliographic record
Abstract
Canada’s Drug Agency (CDA-AMC) recommends that Opzelura not be reimbursed by public drug plans for topical treatment of nonsegmental vitiligo in adult and pediatric patients aged 12 years and older. Evidence from 2 clinical trials demonstrated that about 30% of patients using Opzelura saw significant improvement in facial repigmentation, compared to around 8% to 11% using a placebo. More patients also reported that their vitiligo became less noticeable or no longer noticeable than those who received placebo. However, the impact of vitiligo on daily life varies, and the treatment did not lead to meaningful improvements in overall health-related quality of life (HRQoL). The studies only compared Opzelura to a placebo; therefore, there is no data on how it performs against other commonly used treatments. The Canadian Drug Expert Committee (CDEC) recognized that vitiligo can seriously affect people’s lives, especially those with darker skin tones, who may face stigma, loss of identity, and low self-esteem. Most trial participants had lighter skin tones, and the treatment did not improve their HRQoL. These limitations make it difficult to know how effective Opzelura would be for those most affected by vitiligo.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".