Revised Airlie House consensus guidelines for design and implementation of ALS clinical trials
Bibliographic record
Abstract
OBJECTIVE: To revise the 1999 Airlie House consensus guidelines for the design and implementation of preclinical therapeutic studies and clinical trials in amyotrophic lateral sclerosis (ALS). METHODS: A consensus committee comprising 140 key members of the international ALS community (ALS researchers, clinicians, patient representatives, research funding representatives, industry, and regulatory agencies) addressed 9 areas of need within ALS research: (1) preclinical studies; (2) biological and phenotypic heterogeneity; (3) outcome measures; (4) disease-modifying and symptomatic interventions; (5) recruitment and retention; (6) biomarkers; (7) clinical trial phases; (8) beyond traditional trial designs; and (9) statistical considerations. Assigned to 1 of 8 sections, committee members generated a draft set of guidelines based on a "background" of developing a (pre)clinical question and a "rationale" outlining the evidence and expert opinion. Following a 2-day, face-to-face workshop at the Airlie House Conference Center, a modified Delphi process was used to develop draft consensus research guidelines, which were subsequently reviewed and modified based on comments from the public. Statistical experts drafted a separate document of statistical considerations (section 9). RESULTS: In this report, we summarize 112 guidelines and their associated backgrounds and rationales. The full list of guidelines, the statistical considerations, and a glossary of terms can be found in data available from Dryad (appendices e-3-e-5, doi.org/10.5061/dryad.32q9q5d). The authors prioritized 15 guidelines with the greatest potential to improve ALS clinical research. CONCLUSION: The revised Airlie House ALS Clinical Trials Consensus Guidelines should serve to improve clinical trial design and accelerate the development of effective treatments for patients with ALS.
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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 | 0.527 | 0.621 |
| Meta-epidemiology (narrow) | 0.003 | 0.005 |
| Meta-epidemiology (broad) | 0.006 | 0.010 |
| Bibliometrics | 0.018 | 0.013 |
| Science and technology studies | 0.006 | 0.007 |
| Scholarly communication | 0.017 | 0.010 |
| Open science | 0.018 | 0.014 |
| Research integrity | 0.018 | 0.025 |
| Insufficient payload (model declined to judge) | 0.011 | 0.014 |
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".