PS1 - 177 Diagnosing and Treating Leptomeningeal Metastasis across Europe: A Web-Based Survey
Bibliographic record
Abstract
Leptomeningeal metastasis is a serious complication of systemic cancer commonly occurring in later disease stages which affects approximately 10% of patients with solid tumors. The risk is highest for patients with lung cancer, melanoma and breast cancer. Survival at one year is in the range of 10%. Cerebrospinal fluid analysis and magnetic resonance imaging are the most important diagnostic measures. Treatment recommendations vary by primary tumor and pattern of disease, that is, e.g., the absence or presence of concurrent systemic or solid brain metastasis. To explore the current practice of diagnosing and treating leptomeningeal metastasis across Europe, a web-based survey was sent to members of the European Association of Neuro-Oncology (EANO) and the Brain Tumor Group of the European Organisation for Research and Treatment of Cancer (EORTC) in April 2016 which contains 24 questions on current practice patterns as well as 8 case presentations. The results of this survey will be presented for the first time. They shall serve as the basis for treatment recommendations for this complication of systemic cancer that reflects current knowledge as well as current practice.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".