Certolizumab Pegol Use in the Treatment of Moderate-to-Severe Psoriasis: Real-World Data From Two Canadian Centers
Bibliographic record
Abstract
BACKGROUND: Certolizumab pegol (CZP) is a TNF-ɑ inhibitor used to treat moderate-to-severe plaque psoriasis (PsO) in adult patients, including women of childbearing potential (WOCBP) and patients with psoriatic arthritis (PsA). There are currently limited real-world data on CZP for treatment of PsO. OBJECTIVES: To examine the use of CZP for treatment of PsO in clinical practice at two dermatology clinics in Canada. METHODS: We conducted a retrospective chart analysis of 59 patients with moderate-to-severe psoriasis receiving CZP. Clinical efficacy was measured using the Psoriasis Area and Severity Index (PASI), Body Surface Area (BSA), and Physician Global Assessment (PGA). Drug survival was analyzed using Kaplan-Meier plots. RESULTS: Of the 59 patients, 36 (61%) were female, of whom 23 (63.9%) were WOCBP. Twenty-three (39.0%) patients received CZP as their first biologic treatment. The main reasons for choosing CZP were its efficacy in both PsO and PsA, and for WOCBP due to little or no cross-placental transfer. Improvement of symptoms was observed after 3 months of treatment and was maintained for the 12-month analysis period. After 12 months of treatment, the patients' mean PASI score decreased from 13.0 (±5.8) at baseline to 2.3 (±4.3), mean BSA score from 13.1% (±6.7%) to 1.7% (±2.6%), and mean PGA score from 3.0 (±0.6) to 0.8 (±0.6). Overall CZP drug survival rate was 76.3% at 12 months, with no difference between biologic-naive and biologic-experienced patients. CONCLUSIONS: CZP was effective and well tolerated in this cohort of patients with moderate-to-severe PsO in a real-world setting.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| 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".