Stereotactic body radiotherapy for Ultra-Central lung Tumors: A systematic review and Meta-Analysis and International Stereotactic Radiosurgery Society practice guidelines
Bibliographic record
Abstract
BACKGROUND: Stereotactic body radiotherapy (SBRT) is an effective and safe modality for early-stage lung cancer and lung metastases. However, tumors in an ultra-central location pose unique safety considerations. We performed a systematic review and meta-analysis to summarize the current safety and efficacy data and provide practice recommendations on behalf of the International Stereotactic Radiosurgery Society (ISRS). METHODS: We performed a systematic review using PubMed and EMBASE databases of patients with ultra-central lung tumors treated with SBRT. Studies reporting local control (LC) and/or toxicity were included. Studies with <5 treated lesions, non-English language, re-irradiation, nodal tumors, or mixed outcomes in which ultra-central tumors could not be discerned were excluded. Random-effects meta-analysis was performed for studies reporting relevant endpoints. Meta-regression was conducted to determine the effect of various covariates on the primary outcomes. RESULTS: 602 unique studies were identified of which 27 (one prospective observational, the remainder retrospective) were included, representing 1183 treated targets. All studies defined ultra-central as the planning target volume (PTV) overlapping the proximal bronchial tree (PBT). The most common dose fractionations were 50 Gy/5, 60 Gy/8, and 60 Gy/12 fractions. The pooled 1- and 2-year LC estimates were 92 % and 89 %, respectively. Meta-regression identified biological effective dose (BED10) as a significant predictor of 1-year LC. A total of 109 grade 3-4 toxicity events, with a pooled incidence of 6 %, were reported, most commonly pneumonitis. There were 73 treatment related deaths, with a pooled incidence of 4 %, with the most common being hemoptysis. Anticoagulation, interstitial lung disease, endobronchial tumor, and concomitant targeted therapies were observed risk factors for fatal toxicity events. CONCLUSION: SBRT for ultra-central lung tumors results in acceptable rates of local control, albeit with risks of severe toxicity. Caution should be taken for appropriate patient selection, consideration of concomitant therapies, and radiotherapy plan design.
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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 | 0.025 | 0.048 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.033 |
| Bibliometrics | 0.010 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".