Excellent Cancer Outcomes Following Patient-adapted Robotic Lung SBRT But a Case for Caution in Idiopathic Pulmonary Fibrosis
Why this work is in the frame
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Bibliographic record
Abstract
The aim of this study is to report outcomes and prognostic factors for early stage non-small cell lung cancer treated with patient-adapted Cyberknife stereotactic body radiotherapy. A retrospective analysis of 150 patients with T1-2N0 non-small cell lung cancer treated with stereotactic body radiotherapy was conducted. An algorithm based on tumor and patient's characteristics was used to orient patients towards soft tissue (Xsight Lung), fiducials or adjacent bone (Xsight Spine) tracking. Median biological effective dose without correction for tissue inhomogeneities was 180 Gy10 for peripheral tumors and 113 Gy10 for central tumors. Median follow-up was 22 months. Actuarial 2 years local control, overall survival and disease-specific survival were respectively 96%, 87% and 95%. Every 1 cm increase in tumor diameter was associated with a relative risk for regional or distant relapse of 2 (95%CI = 1.2-3.6, p = 0.009). With doses ≥132 Gy10 and <132 Gy10, local control was 98% vs. 82% (p = 0.07), disease-specific survival 97% vs. 78% (p = 0.02) and overall survival 93% vs. 76% (p = 0.01), respectively. Better disease-specific survival and a trend for better overall survival was observed for peripheral vs. central tumors (96% vs. 79%, p = 0.05 and 92% vs. 74%, p = 0.08, respectively). A higher Charlson comordibity score (≥4) predicted lower overall survival (79% vs. 98%, p = 0.01). Toxicities included 3 patients with idiopathic pulmonary fibrosis who developed grade 5 pneumonitis and 2 patients with grade 3 pneumonitis. We therefore report excellent local control and disease-specific survival following patient-adapted Cyberknife lung stereotactic body radiotherapy. Although toxicities were in general minimal, patients with pulmonary fibrosis might be at greater risk of severe complications. Small size, peripheral location, dose ≥ 132 Gy10 and a low Charlson co-morbidity score seem to be associated with better outcomes.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it