The Role of Stereotactic Body Radiotherapy in Oligometastatic Non-Small Cell Lung Cancer
Bibliographic record
Abstract
Non-small cell lung cancer (NSCLC) is a major cause of mortality in Canada, with many patients presenting with metastatic disease. The oligometastatic state (OM-NSCLC) may be amenable to cure using aggressive local consolidative therapies. Stereotactic body radiotherapy (SBRT), which entails the utilization of a high dose of radiation in one or few fractions, has many benefits in this setting, including its applicability in varied patient populations to ablate lesions in varied anatomical locations. It has also been demonstrated to prolong the time to next-line systemic therapy, to reduce financial burden, to improve quality-adjusted life years, and reduce adverse events caused by these lesions. This review outlines the published phase II and III trials that have already demonstrated the utility of SBRT in OM-NSCLC, as well as the many ongoing trials aiming to further define its role, including the largest phase II/III trial to date, NRG-LU002. Overall, SBRT appears to improve outcomes when combined with a broad range of standard-of-care therapies and is generally well tolerated; however, careful patient selection is necessary to maximize benefits while minimizing harm. Ongoing trials will help define the optimal patients for SBRT and the best timing for this intervention.
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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) | 0.002 | 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".