Stereotactic Body Radiotherapy for Oligometastasis
Bibliographic record
Abstract
Oligometastasis refers to a state of limited metastatic disease burden, in which surgical or ablative treatment to all known visible metastases holds promise to extend survival or even effect cure. Stereotactic body radiotherapy is a form of radiation treatment capable of delivering a high biologically effective dose of radiation in a highly conformal manner, with a favorable toxicity profile. Enthusiasm for oligometastasis ablation, however, should be counterbalanced against the limited supporting evidence. It remains unknown to what extent (if any) ablation influences survival or quality of life. Rising clinical equipoise necessitates the completion of randomized controlled trials to assess this, several of which are underway. However, a lack of clear identification criteria or biomarkers to define the oligometastatic state hampers optimal patient selection.This narrative review explores the evolutionary origins of oligometastasis, the steps of the metastatic process at which oligometastases may arise, and the biomolecular mediators of this state. It discusses clinical outcomes with treatment of oligometastases, ongoing trials, and areas of basic and translational research that may lead to novel biomarkers. These efforts should provide a clearer, biomolecular definition of oligometastatic disease and aid in the accurate selection of patients for ablative therapies.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".