Real‐World Guselkumab Response and Drug Survival in Australian Patients With Psoriasis: Results From the Australasian Psoriasis Registry
Bibliographic record
Abstract
Aims: Guselkumab’s real‐world efficacy, drug survival, and patient characteristics from the Australasian Psoriasis Registry (APR) were compared with the data from the Phase III VOYAGE 1 trial. Methods: Data from patients with severe plaque psoriasis prescribed guselkumab through the Australian Pharmaceutical Benefits Scheme (PBS) were derived from the APR. Demographic and treatment data (including psoriasis area and severity index [PASI]) at defined timepoints from 4th September 2018 to 1st October 2022 were analyzed. The baseline was PASI at the commencement of the first biologic. APR and VOYAGE 1 data were compared using 2‐sample t‐tests and chi‐square tests. Associations between patient characteristics and drug survival/time to PASI score were assessed using Cox proportional hazards regression and Kaplan–Meier estimates. Results: 102 patients were eligible; 87.3% (n = 89) had received prior biologic therapy versus 21.6% patients in VOYAGE 1. Overall drug survival in APR was 99.0%, 93.1%, 83.3% and 77.1% at 3, 9, 15, and 27 months, respectively. At 9 months, drug survival was 100% for bionaïve and 92.1% for bioexperienced patients. In VOYAGE 1, 91.5% continued guselkumab through Week 48 (∼11 months). In the APR, the median PASI was 24.0 (IQR: 17.9–32.2) at baseline, and 1.1 (IQR: 0–2.7) at 9 months. Absolute PASI ≤ 3 and PASI90 were attained by 73.8% and 64.8%, respectively. In VOYAGE 1, 76.3% reached PASI90 at Week 48. Bionaïve patients in the APR had longer drug survival than bioexperienced. Conclusions: Guselkumab was efficacious in the real‐world treatment of psoriasis, consistent with RCT results. Drug retention rates were high through 27 months, despite a higher proportion of bioexperienced patients in the APR than in VOYAGE 1.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".