RMTD-09 ‘CORE OUTCOME SET’ FOR LEPTOMENINGEAL DISEASE (LEPTOCOS): A MULTI-DISCIPLINARY, INTERNATIONAL, CONSENSUS EFFORT
Bibliographic record
Abstract
Abstract BACKGROUND Leptomeningeal disease (LMD) represents a stage of metastatic cancer when tumor cells have seeded the leptomeninges and cerebrospinal fluid (CSF)-containing subarachnoid space. Despite decades of efforts by the neuro-oncology community, response assessment remains challenging, and the prognosis of this whole neuroaxial disease remains extremely poor, ranging typically between 3-8 months despite standard of care therapy. The extensive heterogeneity in outcomes observed in randomized controlled trials (RCTs) for LMD has been thoroughly documented by prior consensus reviews and systematic reviews, warranting the development and implementation of a standardized core outcome set (COS) for LMD. Objective: This ongoing project aims to develop a COS for LMD (LeptoCOS) through a multidisciplinary, international effort, following current methodological recommendations. METHODS The LeptoCOS collaborative has been established in order to develop COS for use in clinical effectiveness trials of LMD, including RCTs and NRTs, through a collaboratorship framework working with multiple stakeholder groups and to help drive its global adoption. This project has been pre-registered with Core Outcome Measures in Effectiveness Trials (COMET ID 3224) database: https://www.comet-initiative.org/Studies/Details/3224. COS are being developed following Core Outcome Set–Standards for Development (COS-STAD) and COMET guidelines, with pre-registration in COMET database. Long-list of outcomes of potential relevance are being generated based on updated systematic review of published literature and searches of trial registries (rapid review). After eDelphi process and consensus meetings with various stakeholders, short-list of outcomes will be generated for inclusion and the final LeptoCOS. With the endorsement of professional societies and non-profit organizations, this effort will help standardize the use and reporting of outcomes reported in future clinical studies of LMD, thereby enabling efficient evidence synthesis.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".