Optimization of placebo use in clinical trials with systemic treatments for atopic dermatitis: an International Eczema Council survey‐based position statement
Bibliographic record
Abstract
BACKGROUND: As novel systemic therapeutics for patients with atopic dermatitis (AD) are developed, ethical and methodological concerns regarding placebo-controlled-trials (PCT) have surfaced. OBJECTIVE: To guide the design and implementation of PCT in AD, focusing on trials with systemic medications. METHODS: A subgroup of the International Eczema Council (IEC) developed a consensus e-survey, which was disseminated to IEC members. RESULTS: The response rate was 43/82 (52%). Consensus was reached on 24/27 statements and on 3/11 options from multiple-selection statements, including: performing monotherapy studies in proof-of-concept phases; avoiding concomitant topical corticosteroids or calcineurin inhibitors until a predefined timepoint as rescue (borderline consensus); selection of sites and assessors with recognized expertise in AD clinical trials; clear definition and identification of baseline disease severity; minimizing time and proportion of patients on placebo; using daily emollients with several options provided; instigating open-label extension studies for enrolment after a predefined timepoint; and including outcomes which set a higher bar for disease clearance. CONCLUSION: Conducting PCT in AD requires balancing several, sometimes opposing principles, including ethics, methodology, regulatory requirements and real-world needs. This paper can provide a framework for conducting PCT with systemic medications for patients with AD.
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 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 | 0.734 | 0.631 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.005 | 0.009 |
| Research integrity | 0.014 | 0.010 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".