A study of the drug tildrakizumab for plaque psoriasis
Bibliographic record
Abstract
Tildrakizumab is a fairly new type of medicine called a biologic, used for the treatment of moderate‐to‐severe psoriasis. The drug prevents the action of a specific molecule in the body involved in inflammation, known as cytokine interleukin (IL)‐23p19. Previous studies have shown it to be superior to a placebo (an inactive substance, like a “sugar pill”) and to an older biologic drug, the TNF inhibitor etanercept. However, trials rarely reflect real‐world experience, where patients may switch from one drug to another, change drug dosage or interrupt treatment, e.g. because of an infection. The authors, based in U.S.A., Canada and Germany, reviewed results from two studies, one comparing two different doses of tildrakizumab (100mg or 200mg per day) with placebo, and the other comparing it with etanercept, including a total of 1862 adults with moderate‐to‐severe plaque psoriasis. Treatments were re‐randomised during the course of the study. They found that the response to tildrakizumab was sustained (meaning it kept working), without the secondary failure (decreasing responsiveness to a drug after an initial satisfactory response) seen in some patients on etanercept, and the drug regained effective control of the psoriasis after treatment was interrupted. Overall the drug was well tolerated, meaning that side effects were minimal. This is a summary of the study: Efficacy and safety of tildrakizumab for plaque psoriasis with continuous dosing, treatment interruption, dose adjustments and switching from etanercept: results from phase III studies
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".