Stereotactic radiotherapy in oligometastatic cancer
Bibliographic record
Abstract
Oligometastatic cancer describes a disease state somewhere between localized and metastatic cancer. Proposed definitions of oligometastatic disease have typically used a cut-off of five or fewer sites of disease. Treatment of oligometastatic disease should have the goal of long-term local control, and in selected cases, disease remission. While several retrospective cohorts argue for surgical excision of limited metastases (metastasectomy) as the preferred treatment option for several clinical indications, limited randomized data exists for treating oligometastases. Alternatively, stereotactic ablative radiotherapy (SABR) is a radiotherapy technique that combines high radiation doses per fraction with precision targeting with the goal of achieving long-term local control of treated sites. Published cohort studies of SABR have demonstrated excellent local control rates of 70-90% in oligometastatic disease, with long-term survival in some series approaching 20-40%. A recent randomized phase 2 clinical trial by Gomez et al. demonstrated significantly improved progression free survival with aggressive consolidative therapy (surgery, radiotherapy ± chemotherapy or SABR) in oli-gometastatic non-small cell lung cancer (NSCLC). As additional randomized controlled trials are ongoing to determine the efficacy of SABR in oligometastatic disease, SABR is increasingly being used within routine clinical practice. This review article aims to sum-marize the history and current paradigm of the oligometastatic state, review recently pub-lished literature of SABR in oligometastatic cancer and discuss ongoing trials and future directions in this context.
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How this classification was reachedexpand
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.007 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".