Safe Psoriasis Control: A New Outcome Measure for the Composite Assessment of the Efficacy and Safety of Psoriasis Treatment
Bibliographic record
Abstract
BACKGROUND: PASI is an inadequate outcome measure for the assessment of psoriasis treatments. No currently used endpoints provide a benefit: risk assessment of treatment taking into consideration all available efficacy and safety data. OBJECTIVE: To propose a new outcome measure called "safe psoriasis control" (SPC), which assesses multiple dimensions of the disease in a clinically meaningful way through the combined use of appropriate efficacy, quality of life, and safety data. METHODS: Data from 3,500 subjects were used for the purpose of derivation and validation of the SPC endpoint. Advanced statistical methodology was used to evaluate and validate important components in the assessment of therapeutic benefit. RESULTS: SPC was shown to be a simple but meaningful combined endpoint showing the proportion of patients who had treatment benefit without major side effects. CONCLUSION: The SPC endpoint may be a step-forward in providing a composite tool for the evaluation of treatments for psoriasis.
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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 | 0.021 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.006 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".