Efficacy of Brodalumab in Patients with Psoriasis and Risk Factors for Treatment Failure: A Review of Post Hoc Analyses
Bibliographic record
Abstract
Factors such as obesity, alcohol consumption, and tobacco use are associated with both increased psoriasis severity and inadequate response to systemic and biologic therapies. Obesity is linked to chronic inflammation, which can contribute to psoriasis pathogenesis. Fixed-dose therapies may have reduced efficacy in patients with a higher body mass index, while weight-based dosing can increase the burden of drug-specific side effects. Alcohol and nicotine from tobacco have also been shown to stimulate keratinocyte and immune cell proliferation and production of proinflammatory cytokines. While these risk factors are prevalent among patients with moderate-to-severe psoriasis, their influence on treatment outcomes may be overlooked when evaluating therapeutic options. Brodalumab is a fully human interleukin-17 receptor A antagonist approved for the treatment of moderate-to-severe psoriasis. In this review, we describe the lifestyle-related risk factors associated with decreased response to treatment. We further summarize the post hoc analyses of brodalumab in participant subgroups with moderate-to-severe psoriasis and a history of prior biologic failure, obesity, and alcohol or tobacco use from two phase 3 clinical trials (AMAGINE-2 and AMAGINE-3; ClinicalTrials.gov identifiers: NCT01708603 and NCT01708629, respectively). Our review of clinical trial and real-world data suggests that brodalumab is an efficacious and safe treatment option for patients with lifestyle factors that increase the likelihood of treatment failure, allowing them to achieve skin clearance and improve quality of life.
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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 | 0.011 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.008 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".