Effect of Age of Onset of Psoriasis on Clinical Outcomes with Systemic Treatment in the Psoriasis Longitudinal Assessment and Registry (PSOLAR)
Bibliographic record
Abstract
OBJECTIVE: Our objective was to compare therapeutic response among patients with early-onset psoriasis (EOP) and late-onset psoriasis (LOP) receiving adalimumab, etanercept, infliximab, ustekinumab, or methotrexate in the Psoriasis Longitudinal Assessment and Registry (PSOLAR). METHODS: Patients were grouped by age of onset: EOP (age ≤ 40 years) or LOP (age > 40 years). Repeated-measures analysis with logistic regression was used to calculate the adjusted odds ratio (AOR; adjusted for baseline characteristics) for achieving a Physician's Global Assessment score of cleared/minimal (PGA 0/1) or a percentage of body surface area involved with psoriasis < 3% (%BSA < 3) or %BSA < 1 for all patients; similar sensitivity analyses were performed for each treatment group. RESULTS: Of 7511 patients, 5479 (72.9%) had EOP. The LOP group had a higher likelihood of achieving PGA 0/1 after treatment than did the EOP group in all patients (AOR 1.14 [95% confidence interval (CI) 1.05-1.25]; p = 0.0019); the same was true in subgroups of etanercept-treated (AOR 1.38 [95% CI 1.14-1.66]; p = 0.0010) and methotrexate-treated (AOR 1.62 [95% CI 1.16-2.26]; p = 0.0049) patients. No significant difference was found between the EOP and LOP groups with regard to the likelihood of achieving %BSA < 3 or %BSA < 1 among all patients. However, LOP patients were more likely than EOP patients to achieve %BSA < 3 or %BSA < 1 in subgroups treated with infliximab (AOR 1.45 [95% CI 1.09-1.93; p = 0.0103] and AOR 1.36 [95% CI 1.03-1.78; p = 0.0290], respectively) and etanercept (AOR 1.30 [95% CI 1.06-1.61; p = 0.0123] and AOR 1.34 [95% CI 1.09-1.64; p = 0.0053], respectively). CONCLUSION: Our real-world data from PSOLAR indicate that there are differences in some patient characteristics between EOP and LOP and that patients with EOP are less likely than those with LOP to respond to certain systemic treatments. (ClinicalTrials.gov identifier: NCT00508547).
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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 | 0.012 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".