Association of disease duration and PASI response rates at week 12 in patients with moderate-to-severe plaque psoriasis receiving biologics in the real-world psoriasis study of health outcomes (PSoHO)
Bibliographic record
Abstract
PURPOSE: Currently, in the treatment of moderate-to-severe psoriasis (PsO) there is a lack of evidence demonstrating optimal biologic treatment response with respect to disease duration. The aim of this post-hoc analysis, using real world data from the Psoriasis Study of Health Outcomes (PSoHO), is to provide evidence if early intervention with biologics is associated with better treatment outcomes and if there is any difference among drug classes or individual biologics. MATERIALS AND METHODS: For this post-hoc analysis patients were categorised into two subgroups according to shorter (≤2 years) or longer (>2 years) disease duration. Analysis was performed on anti-interleukin (IL)-17A cohort vs other biologics cohort, anti-IL-17A vs other drug classes, and pairwise comparisons of ixekizumab vs individual biologics, provided that the statistical models converged. Analysis investigated the association of disease duration with the proportion of patients achieving 100% improvement in Psoriasis Area Severity Index score (PASI 100) at week 12. Adjusted comparative analyses, reported as odds ratio (OR), were performed using Frequentist Model Averaging (FMA) for each cohort or treatments within each subcategory of the subgroups. RESULTS: At week 12, anti-IL-17A and other biologics cohorts displayed minimal differences in numerical response rate for PASI 100 with respect to disease duration. The anti-IL-17A cohort showed a higher numerical PASI 100 response rate compared to the other biologic cohort irrespective of disease duration (≤2 years: 36.7% vs 21.8%; >2 years: 35.8% vs 21.9%). CONCLUSION: Overall, the results do not clearly indicate that treating patients early is critical in achieving optimal patient outcomes. Furthermore, patients treated with ixekizumab show numerically higher response rates relative to other individual biologics irrespective of disease duration.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".