Predictors of Topical Use in Psoriasis Patients in the REFINE Study
Bibliographic record
Abstract
BACKGROUND: The factors influencing the use of topical agents in combination with biologic therapies for the treatment of plaque psoriasis (PsO) are not well understood. OBJECTIVE: To examine potential predictors of topical use in patients with moderate to severe plaque PsO receiving etanercept (ETN). METHODS: Post hoc descriptive analyses and a multinomial regression of the REFINE study data were used to examine associations between topical agent potency and covariates, including Psoriasis Area and Severity Index (PASI) score, study site, and province. RESULTS: Not achieving PASI 90 at week 12 predicted topical use, with a lower PASI 90 rate in patients who used high-potency topical agents post randomization (P = .003). Additionally, statistically significant differences were found in patterns of topical use among Canadian provinces (P = .007), with the use of high-potency topical agents being greater in Ontario and Quebec than the rest of Canada. CONCLUSION: This analysis revealed that region and PASI 90 status at week 12 predict topical use.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".