Radiation in the Treatment of Oligometastatic and Oligoprogressive Disease
Bibliographic record
Abstract
The use of local ablative therapy or metastasis-directed therapy is an emerging management paradigm in oligometastatic and oligoprogressive cancer. Recent randomized evidence has demonstrated that stereotactic ablative radiotherapy (SABR) targeting all metastatic deposits is tolerable and can improve progression-free and overall survival. While SABR is noninvasive, minimally toxic, and generally safe, rare grade 5 events have been reported. Given this and recognizing the often-uncertain prognosis of patients with metastatic disease, equipoise persists regarding the therapeutic window within which to deploy SABR for this indication. Ongoing phase III trials are aimed at validating the demonstrated safety, tolerability, and survival benefits while also refining patient selection, possibly with the aid of novel biomarkers. This narrative review of the role of SABR in oligometastatic and oligoprogressive disease summarizes recent randomized evidence and ongoing clinical trials, discusses our rationale for treatment and key management principles, and posits that SABR should be considered the preferred modality for multisite, metastasis-directed ablative therapy.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".