Latest Highlights from Guselkumab in Psoriasis from EADV 2019
Bibliographic record
Abstract
Guselkumab was the first monoclonal antibody targeting the p19 subunit of IL-23 (IL-23p19) to be approved for the treatment of psoriasis. The registrational trials VOYAGE 1 and 2 established the efficacy and safety profile of guselkumab to Week 48 and demonstrated the superiority of guselkumab over placebo and adalimumab. A 5-year, open-label extension phase of both trials is currently ongoing. The poster and oral presentations reviewed here represent the latest data to emerge from the guselkumab clinical trial programme in psoriasis, as presented at the 28th European Academy of Dermatology and Venereology (EADV) Congress. The ECLIPSE study was the first head-to-head trial between guselkumab and the IL-17A inhibitor secukinumab. Both agents were the first to be approved in their respective class with proven efficacy for the treatment of moderate-to-severe psoriasis but, until now, no direct comparisons were available to assist clinical decision making. Together with efficacy and safety, ECLIPSE also sought to understand the differential impact of IL-23 versus IL-17 inhibition on the immune profile of psoriatic skin and effector cytokines, providing insights into their respective mechanisms of action. Switching focus to the long term, the latest 3-year safety data from VOYAGE 1 and 2 are now available to accompany the established 3-year efficacy profile, providing unprecedented insights into the long-term response and tolerability of guselkumab for the treatment of psoriasis.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.012 | 0.006 |
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".