Treatment Outcomes of IL-17 Inhibitors in Hidradenitis Suppurativa: A Systematic Review
Bibliographic record
Abstract
The IL-17 pathway is a potential therapeutic target shown to be implicated in hidradenitis suppurativa (HS), however, it remains unclear whether evidence from mechanistic studies may translate into clinical practice. This systematic review summarizes available treatment outcomes of IL-17 inhibitors in patients with HS. Embase, MEDLINE, PubMed, and clinicaltrials.gov were comprehensively searched on February 26, 2021 to include 16 original studies representing 128 patients with HS (mean age: 36.5 years; age range: 21-47 years; male: 50.0%). Treatment outcomes were reported for the following biologics: secukinumab ( n = 105), brodalumab ( n = 22), and ixekizumab ( n = 1). Patients were classified as responders or non-responders according to achievement of a positive response/improvement based on criteria established for each included study. For secukinumab 57.1% ( n = 60/105) of patients were responders in a mean response period of 16.2 weeks and 42.9% ( n = 45/105) were non-responders; for brodalumab, 100.0% ( n = 22/22) of patients were responders within 4.4 weeks; and the one patient treated with ixekizumab was a responder within 10 weeks. In conclusion, IL-17 inhibitors may serve as an effective therapeutic target in approximately two-thirds of patients with HS and can be considered in those who are refractory to other treatment modalities. We also stress the importance of consistent outcome measures to enhance evidence synthesis, decrease reporting bias, provide potential for future meta-analysis, and ultimately improve clinical outcomes for patients with HS.
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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 | 0.004 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.008 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".