Meeting report: the ALPHA project: a stakeholder meeting on lupus clinical trial outcome measures and the patient perspective
Bibliographic record
Abstract
Drug development in lupus has improved over the past 10 years but still lags behind that of other rheumatic disease areas. Assessment of prospective lupus therapies in clinical trials has proved challenging for reasons that are multifactorial including the heterogeneity of the disease, study design limitations and a lack of validated biomarkers which greatly impacts regulatory decision-making. Moreover, most composite outcome measures currently used in trials do not include patient-reported outcomes. Given these factors, the Addressing Lupus Pillars for Health Advancement Global Advisory Committee members who serve on the drug development team identified an opportunity to convene a meeting to facilitate information sharing on completed and existing outcome measure development efforts. This meeting report highlights information presented during the meeting as well as a discussion on how the lupus community may work together with regulatory agencies to simplify and standardise outcome measures to accelerate development of lupus therapeutics.
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 | 0.100 | 0.079 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.015 | 0.021 |
| Insufficient payload (model declined to judge) | 0.017 | 0.007 |
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".