Novel targeted therapies in chordoma: an update
Bibliographic record
Abstract
Chordomas are rare, locally aggressive skull base neoplasms known for local recurrence and not-infrequent treatment failure. Current evidence supports the role of maximal safe surgical resection. In addition to open skull-base approaches, the endoscopic endonasal approach to clival chordomas has been reported with favorable albeit early results. Adjuvant radiation is prescribed following complete resection, alternatively for gross residual disease or at the time of recurrence. The modalities of adjuvant radiation therapy reported vary widely and include proton-beam, carbon-ion, fractionated photon radiotherapy, and photon and gamma-knife radiosurgery. As of now, no direct comparison is available, and high-level evidence demonstrating superiority of one modality over another is lacking. While systemic therapies have yet to form part of any first-line therapy for chordomas, a number of targeted agents have been evaluated to date that inhibit specific molecules and their respective pathways known to be implicated in chordomas. These include EGFR (erlotinib, gefitinib, lapatinib), PDGFR (imatinib), mTOR (rapamycin), and VEGF (bevacizumab). This article provides an update of the current multimodality treatment of cranial base chordomas, with an emphasis on how current understanding of molecular pathogenesis provides a framework for the development of novel targeted approaches.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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; 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".