A study comparing the biologic drugs ixekizumab and guselkumab for the treatment of moderate‐to‐severe plaque psoriasis
Bibliographic record
Abstract
Psoriasis is a skin disease that causes red, scaly and itchy patches of skin all over the body. It affects about 125 million people worldwide. As well as causing decreased quality of life, more widespread psoriasis often affects internal health. New drugs developed in the last few years often help people with psoriasis to achieve completely clear skin, and improve overall health. Two of these drugs are ixekizumab (IXE) and guselkumab (GUS). IXE and GUS work in different ways, however, and some prior research showed that IXE may work faster than GUS. In this study, researchers from the U.S.A. and Canada tested these drugs head‐to‐head, measuring speed of clearance and complete skin clearance rates over the first 12 weeks after starting drug. People in this study received either IXE or GUS. After 12 weeks, completely clear skin was achieved by 16% more people if they were treated with IXE compared to GUS (41% of people who took IXE versus 25% of people who took GUS). More people on IXE than GUS had 50% clearer skin after just one week and 75% clearer skin after two weeks. Itching, skin pain, and quality of life also improved faster with IXE compared to GUS. The number of patients with serious side effects was similar for IXE and GUS. Overall, people with psoriasis who take IXE may get clear skin faster and feel better more quickly than people who take GUS. This is a summary of the study: A head‐to‐head comparison of ixekizumab vs. guselkumab in patients with moderate‐to‐severe plaque psoriasis: 12‐week efficacy, safety and speed of response from a randomized, double‐blinded trial
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".