Maintenance of Early Responses and Delayed Responses to Tralokinumab Treatment in Moderate-to-Severe Atopic Dermatitis: A 48-Week Real-World Study
Bibliographic record
Abstract
Abstract: Background: An anti-interleukin-13 monoclonal antibody, tralokinumab, provided favorable efficacy and safety for atopic dermatitis (AD) in clinical trials. However, its long-term sustainability of early responses and delayed responses is unknown in real world. Objective: This study aimed to assess whether clinical outcomes achieved at week 16 of tralokinumab treatment are maintained through week 48 and whether patients without early outcomes achieve delayed outcomes. Methods: This prospective study included 143 Japanese patients with moderate-to-severe AD who received tralokinumab with topical corticosteroids. Patients who achieved an eczema area and severity index (EASI) 0f 50, EASI 75, EASI 90, EASI 100, investigator’s global assessment (IGA) 0/1, or a peak pruritus-numerical rating scale (PP-NRS) 4 at week 16 were evaluated for maintenance rates of each outcome, while week 16 non-achievers were evaluated for later achievement rates at weeks 24, 36, and 48. Results: In week 16, achievers of each outcome, the week 48 maintenance rates of EASI 50, EASI 75, and EASI 90 were 100%; those of EASI 100, IGA 0/1, and PP-NRS 4 were 80.0%, 95.0%, and 90.9%, respectively. In week 16 non-achievers, week 48 achievement rates for EASI 50, EASI 75, EASI 90, and EASI 100 were 53.8%, 76.5%, 48.3%, and 12.5%, and those for IGA 0/1 and PP-NRS 4 were 45.5% and 29.6%, respectively. Conclusions: The improvements of rash or pruritus achieved at week 16 of tralokinumab treatment were mostly sustained through week 48, while some patients without early improvements achieved delayed improvements. These results support the importance of longer-term evaluation of treatment responses.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".