New Strategies in Stereotactic Radiotherapy for Oligometastases
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Patients with metastatic solid tumors are usually treated with palliative intent. Systemic therapy and palliative radiation are often used, with the goals of prolonging survival or maintaining quality of life, but not of cure. In contrast to this paradigm, the theory of oligometastasis suggests that some patients who have a small number of metastases may be amenable to cure if all lesions can be eradicated. Aggressive treatment of patients with oligometastases, using either surgery or radiotherapy, has become more common in the past decade, yet in most situations, no randomized evidence is available to support such an approach. Stereotactic ablative radiotherapy (SABR) is a novel treatment for oligometastases, delivering large doses of radiotherapy in only a few treatments, with excellent rates of local control, and appears to be an excellent noninvasive alternative to surgical resection of metastases. This article reviews recent biologic and clinical data that support the existence of the oligometastatic state and discusses gaps in this evidence base. The emerging role for SABR in the management of this challenging patient population is discussed with a focus on ongoing clinical trials in an attempt to improve overall survival, delay progression, or induce immunologic anticancer effects through the abscopal effect.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 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) | 0.001 | 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 it