Narrative Review of the Emerging Therapeutic Role of Brodalumab in Difficult-to-Treat Psoriasis
Bibliographic record
Abstract
Psoriatic involvement in areas of the body such as nails, palms and soles (palmoplantar), and scalp is associated with dramatically negative effects on quality of life relative to involvement elsewhere in the body. Although numerous evidence-based studies demonstrate the efficacy of biologics for overall skin clearance in moderate-to-severe plaque psoriasis (including tumor necrosis factor α [TNFα] inhibitors and interleukin [IL]-17A, IL-12/IL-23, IL-23, IL-17F, and IL-17A/F inhibitors), large, randomized, placebo-controlled clinical studies of psoriasis with nail, palmoplantar, and scalp involvement are needed to better inform decision-making in clinical practice. Moreover, biologic failure caused by drug ineffectiveness is a common occurrence in patients who do not respond, lose response, or are intolerant to treatment. Brodalumab is a fully human IL-17 receptor A antagonist that demonstrates high rates of skin clearance among the latest generation of biologic therapies for treatment of moderate-to-severe psoriasis. This review summarizes current literature on the efficacy of brodalumab and other therapies in difficult-to-treat psoriasis including psoriasis in difficult-to-treat locations (such as psoriasis with nail, palmoplantar, or scalp involvement) and psoriasis in patients whose disease did not respond to other biologics.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".