Stereotactic body radiation therapy for lung, spine and oligometastatic disease: current evidence and future directions
Bibliographic record
Abstract
Stereotactic body radiation therapy (SBRT) also referred to as stereotactic ablative radiotherapy (SABR), is a technique which has emerged over the past two decades due to improvements in radiation technology. Unlike conventional external beam radiotherapy (cEBRT) which traditionally delivers radiation in small doses [approximately 2 Gray (Gy) per fraction] over several weeks, SBRT, typically delivered in one to eight fractions, is a technique whereby potentially ablative doses of radiotherapy (usually 7.5-20 Gy per fraction) can be delivered with steeper dose gradients and sub millimetre precision, minimising risk to surrounding normal tissues. The potential benefits of excellent tumor control with low toxicity has led to the increasing use of SBRT in a number of clinical situations. Due to compelling evidence, SBRT is now the treatment of choice for medically inoperable patients with peripherally located stage I non-small cell lung cancer (NSCLC). Controversy remains however as to its efficacy and safety for central or ultra-central lung tumors. The evidence base supporting the use of SBRT as a novel treatment for spinal metastases and oligometastases is rapidly expanding but challenges remain in these difficult patient populations. In an era where targeted therapy and improved systemic treatments for stage IV cancer have resulted in increased disease-free survival, and our knowledge of the oligometastatic state is ever expanding, using SBRT to treat metastatic disease and gain durable local control is increasingly desirable. Several randomized trials are currently underway and are sure to provide valuable information on the benefit and utility of SBRT across many tumor sites including early-stage NSCLC, spinal metastases and oligometastatic disease. Recognizing the evolving role of SBRT in clinical practice, this paper provides a critical review of recent developments in each of these areas particularly highlighting the challenges facing clinicians and discusses potential areas for future research.
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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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".