Treatment of Moderate to Severe Psoriasis With High-Dose (450-mg) Secukinumab: Case Reports of Off-Label Use
Bibliographic record
Abstract
Treatment of moderate to severe psoriasis often requires systemic therapy, including biologics. Partial response to biologics and relapses are commonly managed with dose escalation. Secukinumab is a relatively new biologic that is currently used to treat moderate to severe psoriasis. There has been no literature published on dose escalation of secukinumab. This article describes the off-label use of a higher dose of secukinumab (450 mg every 4 weeks) instead of the standard dosing (300 mg every 4 weeks) in 2 patients with moderate to severe psoriasis. The first case involves a male patient with a high body mass index (BMI) (≥30 kg/m 2 ) and severe psoriasis who was started on secukinumab at 450 mg following a partial response to treatment with the standard 300-mg dose. His psoriasis significantly improved with the higher dose of secukinumab. The second case discusses a female patient with treatment-resistant psoriasis and a BMI of 31.6 kg/m 2 who initially achieved a complete remission with standard dosing of secukinumab. Later, her psoriasis relapsed and she was dose-escalated to secukinumab 450 mg in an attempt to recapture response, but this dose escalation was unsuccessful. In both cases, there were no adverse events observed with a higher dose of secukinumab. These cases demonstrate that dose escalation of secukinumab (450 mg rather than on-label 300 mg every 4 weeks) may be considered in selected patients with incomplete clearance, particularly for those with a high BMI. However, secukinumab dose escalation may not be as beneficial in patients with loss of efficacy.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".