Real‐world effectiveness of adalimumab in patients with moderate‐to‐severe hidradenitis suppurativa: the 1‐year SOLACE study
Bibliographic record
Abstract
BACKGROUND: Long-term, real-word data are needed to help manage patients with hidradenitis suppurativa (HS) through this recurrent, painful and debilitating disease. OBJECTIVES: To primarily measure real-world effectiveness of adalimumab in HS and to secondarily observe clinical course of HS in the light of patients' response. METHODS: In SOLACE, adults with moderate-to-severe HS in need for change in ongoing therapy were treated with adalimumab for up to 52 weeks as per physician's medical practice. Treatment effectiveness was measured by Hidradenitis Suppurativa Clinical Response (HiSCR). Inflammatory nodules, abscesses and draining fistulas were counted, Hurley stage was assessed, and disease severity was rated using the International HS Severity Scoring System (IHS4). A post hoc analysis further explored the HiSCR response by abscess and inflammatory nodule (AN) count at baseline (low, medium and high) and gender. Spontaneously reported safety events were collected. RESULTS: From 23 Canadian centres, 69% of the 138 patients achieved HiSCR at week 24, which increased to 82% and 75% at week 52 in patients with medium and high AN counts, respectively. Gender (4 times the odds for female) and age at HS onset (5% decrease with each additional year) had an effect on achieving HiSCR. Treatment with adalimumab led to an important decrease in number of lesions in responders, with most gains observed in inflammatory nodules, more frequently in the lower body area of patients in the high AN count group. The IHS4 scores of responders were substantially lowered, with a larger decrease in patients of the high AN count group. No new safety signal was detected. CONCLUSIONS: The effectiveness of adalimumab was maintained during this 1-year period, and an optimal gain was documented for patients with medium and high AN counts. These real-world data support a prompt treatment of HS patients and the use of IHS4 to monitor 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 | 0.005 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".