Stereotactic ablative radiation therapy in lung cancer
Bibliographic record
Abstract
PURPOSE OF REVIEW: Significant advances have been made in the field of stereotactic ablative radiotherapy (SABR) for the treatment of pulmonary neoplasms in recent years. This review aims to summarize recent salient evidence on SABR for early-stage nonsmall cell lung cancer (ES-NSCLC). RECENT FINDINGS: In medically inoperable patients, SABR remains the standard of care. The optimal SABR dosing regimen is being studied. Comparisons with non-SABR radiotherapy regimens with lower doses per fraction revealed benefit of SABR. In operable patients, no prospective clinical trial comparing SABR and surgery has been completed, although multiple trials are currently underway to address this question. SABR is generally cost-effective and safe in most patients, with preserved patient-reported quality of life. However, increased toxicity with SABR is noted in patients with disease close to, or invading the proximal tracheobronchial tree. Significant SABR-related toxicity and mortality is also reported in patients with coexisting interstitial lung disease. Considerations on pathologic confirmation, surveillance and multiple primaries are also addressed. SUMMARY: SABR is an effective and safe treatment for inoperable ES-NSCLC. Ongoing trials and comparative effectiveness research will help to clarify SABR's role in various lung cancer indications going forward.
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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 | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".