Adalimumab (Humira) for the Treatment of Hidradenitis Suppurativa.
Bibliographic record
Abstract
Adalimumab (Humira®) is a novel therapy approved by the US Food and Drug Administration, Health Canada, and the European Commission for the treatment of hidradenitis suppurativa (HS). Results of two Phase III trials of adalimumab demonstrate significantly higher efficacies compared to placebo. Primary efficacy outcome of 50% reduction in abscess and inflammatory nodule count was seen in 41.8% and 58.9% of participants receiving adalimumab in PIONEER I and PIONEER II studies, respectively, showing substantial improvement compared with placebo groups in both trials (26.0% and 27.6%, respectively). Although the significance of secondary efficacy measures of adalimumab every week treatment (EW) was not consistent between PIONEER I and PIONEER II studies, participants achieving abscess and inflammatory nodule counts of 0, 1, or 2 were significant (EW 51.8%) compared to placebo (32.2%) in the PIONEER II trial. Participants also demonstrated a marked decrease in skin pain measurements from baseline between EW patients (45.7%) and placebo (20.7%) in the PIONEER II trial. Modified Sartorius scores were decreased from baseline in both PIONEER I (-24.4) and PIONEER II (-28.9) trials versus placebo (-15.7 and -9.5, respectively). Adverse events were mild to moderate and comparable between all treatment groups including placebo. Taken together, these data conclude that treatment of HS with adalimumab is a safe and effective therapy resulting in a significant decrease in abscess and inflammatory nodule counts within the first 12 weeks of treatment.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.004 |
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".