Core Outcome Sets for Meningioma In Clinical studies (COSMIC): An international patient and healthcare professional consensus for research studies
Bibliographic record
Abstract
Background: Core Outcome Sets (COS) define the minimum outcomes that should be measured and reported in all clinical trials for a specific health condition or health area. The aim was to develop 2 COS for intracranial meningioma to be used in future clinical studies: COSMIC: Intervention for effectiveness trials and COSMIC: Observation for studies of incidental/untreated meningioma. Methods: A study advisory group was formed with representation from international stakeholder groups: EORTC BTG, ICOM, EANO, SNO, RANO-PRO, BNOS, SBNS, BIMS, TBTC, International Brain Tumour Alliance, and Brainstrust. Outcomes of potential relevance to key stakeholders were identified and rationalized to populate 2 eDelphi surveys. Participants were recruited internationally and asked to rate each outcome on its importance for inclusion in the COS. The 2 final COS were ratified through 2, one-day, online consensus meetings. Results: The COSMIC: Intervention eDelphi survey contained 25 items and was completed by 199 participants. Following the consensus meeting, 15 outcomes were included. The COSMIC: Observation eDelphi survey contained 17 items and was completed by 129 participants. Sixteen outcomes were included. Eight core outcomes were common to both COS; tumor growth, physical, emotional, and neurocognitive functioning, overall quality of life, progression-free survival, meningioma-specific mortality and overall survival. Role and social functioning were core outcomes in COSMIC: Observation but not COSMIC: Intervention. Conclusions: Uptake of these COS in relevant future meningioma clinical studies will ensure that stakeholder-determined, critically important outcomes are consistently measured and reported across similar clinical studies.
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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 | 0.753 | 0.675 |
| Meta-epidemiology (narrow) | 0.004 | 0.004 |
| Meta-epidemiology (broad) | 0.012 | 0.015 |
| Bibliometrics | 0.021 | 0.015 |
| Science and technology studies | 0.009 | 0.014 |
| Scholarly communication | 0.017 | 0.013 |
| Open science | 0.016 | 0.034 |
| Research integrity | 0.018 | 0.025 |
| Insufficient payload (model declined to judge) | 0.003 | 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".