Epithelioid hemangioendothelioma, an ultra-rare cancer: a consensus paper from the community of experts
Bibliographic record
Abstract
Epithelioid hemangioendothelioma (EHE) is an ultra-rare, translocated, vascular sarcoma. EHE clinical behavior is variable, ranging from that of a low-grade malignancy to that of a high-grade sarcoma and it is marked by a high propensity for systemic involvement. No active systemic agents are currently approved specifically for EHE, which is typically refractory to the antitumor drugs used in sarcomas. The degree of uncertainty in selecting the most appropriate therapy for EHE patients and the lack of guidelines on the clinical management of the disease make the adoption of new treatments inconsistent across the world, resulting in suboptimal outcomes for many EHE patients. To address the shortcoming, a global consensus meeting was organized in December 2020 under the umbrella of the European Society for Medical Oncology (ESMO) involving >80 experts from several disciplines from Europe, North America and Asia, together with a patient representative from the EHE Group, a global, disease-specific patient advocacy group, and Sarcoma Patient EuroNet (SPAEN). The meeting was aimed at defining, by consensus, evidence-based best practices for the optimal approach to primary and metastatic EHE. The consensus achieved during that meeting is the subject of the present publication.
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 | 0.015 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".