Real-World Moderate-to-Severe Hidradenitis Suppurativa: Decrease in Disease Burden With Adalimumab
Bibliographic record
Abstract
BACKGROUND: Real-world knowledge of the burden of hidradenitis suppurativa (HS) on patients remains limited. OBJECTIVES: To measure the impact of adalimumab on moderate-to-severe HS patients' health-related quality of life (HRQoL) and work productivity. METHODS: In 23 Canadian centres, 138 adults with moderate-to-severe HS requiring a change in ongoing therapy were treated with adalimumab for up to 52 weeks as per the physician's practice. Patient-reported outcome measures (PROMs) were obtained at baseline, weeks 24 and 52 to measure overall HRQoL, HS severity, levels of anxiety and depression, impact and symptoms of HS, work productivity and activity impairment. A post-hoc analysis further explored the PROMs by abscess and inflammatory nodule (AN) count at baseline (≤5, low; 6-10, medium; ≥11, high). RESULTS: ≤ .0023). The number of patients reporting "good disease control" and "complete disease control" increased from 9.7% to 66.4% over 52 weeks. The score in Health Utility Index Mark 3 (HUI3) pain attribute meaningfully decreased over 52 weeks (mean difference ≥.05). The HS symptoms skin "tenderness" and "itchiness" improved the most. Work productivity loss and activity impairment improved by approximately 20% over 52 weeks. Disease burden improved more in 24 week responders with low and medium AN counts at baseline than in those with high AN count or in 24 week nonresponders. CONCLUSION: At week 24 and maintained at week 52 in a real-world setting, adalimumab meaningfully improved HRQoL, work productivity, and activity impairment in moderate-to-severe HS patients.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".