Systemic immunomodulatory treatments for atopic dermatitis: protocol for a systematic review with network meta-analysis
Bibliographic record
Abstract
INTRODUCTION: There are numerous new systemic treatments for atopic dermatitis in various stages of development and most are being compared with placebo rather than active comparators. In order to understand the relative efficacy and safety of existing and new treatments for atopic dermatitis, robust mixed comparisons (ie, direct and indirect) would be beneficial. To address this gap, this protocol describes methods for a systematic review and network meta-analysis of systemic treatments for atopic dermatitis. METHODS AND ANALYSIS: We will update the search of a previous systematic review, including searches of the Cochrane Central Register of Controlled Trials, MEDLINE, Embase, Latin American and Caribbean Health Science Information database and the Global Resource of EczemA Trials database in addition to clinical trial protocol registries. Title, abstract and full paper screening as well as data extraction will be conducted in duplicate by independent researchers. Primary outcomes include efficacy with regards to clinician-reported signs and patient-reported symptoms and safety with regards to withdrawal from treatment due to adverse events and the occurrence of serious adverse events. Secondary outcomes will include change in quality of life and itch severity. Where possible and appropriate, network meta-analysis will be performed for each outcome using a random-effects model within a Bayesian framework. If appropriate, the review will be transitioned to a living review with continuous updating of the analysis. ETHICS AND DISSEMINATION: Dissemination in a peer-reviewed scientific journal is planned. PROSPERO REGISTRATION NUMBER: CRD42018088112; Pre-results.
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 | 0.069 | 0.119 |
| Meta-epidemiology (narrow) | 0.005 | 0.004 |
| Meta-epidemiology (broad) | 0.014 | 0.020 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.106 | 0.010 |
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".