Lebrikizumab improves head/neck/face dermatitis and erythema and does not increase treatment-emergent adverse events of head/neck/face erythema in patients with moderate-to-severe atopic dermatitis
Bibliographic record
Abstract
PURPOSE OF THE STUDY: Head, neck (HN), and face involvement in atopic dermatitis (AD) poses a major psychological burden and can be challenging to effectively treat. New appearance of HN dermatitis has been reported with biologics used to treat AD. Lebrikizumab (LEBRI), a monoclonal targeting IL-13, is approved for AD treatment in the US, Europe and Asia. We evaluated HN dermatitis improvement using the HN Eczema Area and Severity Index (EASI) and a facial dermatitis questionnaire, along with safety evaluations focusing on HN and facial erythema. MATERIALS AND METHODS: Efficacy analyses were performed on placebo (PBO) controlled modified intention-to-treat (mITT) populations from the 16-week induction periods of ADvocate1 and ADvocate2 (pooled) and ADhere studies. Treatment-emergent adverse events (TEAEs) of HN and facial erythema were summarized from eight Phase 2 and 3 clinical trials. RESULTS: LEBRI resulted in significantly greater improvements than PBO in EASI HN subscore as early as Week 2 (ADvocate 1&2), with 68.1% improvement at Week 16. CONCLUSIONS: LEBRI improved EASI HN subscore and HN EASI clinical signs of erythema and facial dermatitis at Week 16. During the PBO-controlled period, an increased reporting of HN and facial erythema as TEAE was not observed in the LEBRI group and HN and facial TEAEs reporting did not increase with longer exposure.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".