Ablative Techniques for Lung Metastases: Patient Selection and Outcomes Following Treatment with Stereotactic Radiotherapy or Radiofrequency Ablation
Bibliographic record
Abstract
Stereotactic radiotherapy (SBRT) and radiofrequency ablation (RFA) are common ablative techniques for lung metastases. A retrospective review of all patients treated with either modality at a single institution between 2011 and 2019 was conducted. Baseline characteristics and outcomes were compared. Local and distant progression, and overall survival were estimated using the Kaplan–Meier method. Univariable analysis was carried out using Cox regression; this was followed by multivariable modelling. In total, 106 patients treated with RFA and 70 treated with SBRT were identified. Tumours treated with SBRT were larger (median size 18 mm vs. 11 mm) and primarily oligometastatic (91.4% vs. 20%). Median progression-free survival (PFS) was 12.5 months for SBRT and 7.9 months for RFA (p = 0.009). Median OS was similar (p = 0.66). In multivariable analysis, lesion size > 20 mm was predictive of adverse local PFS (p = 0.001), PFS (p = 0.0034) and OS (p = 0.001). A statistically significant interaction effect suggested that RFA was associated with better local PFS within colorectal primary patients (p = 0.035). This study highlights differences in patient selection and outcomes for RFA or SBRT in the treatment of lung metastases at our institution. Future studies for SBRT should focus on the optimum dose schedules required for different histologies. For less-radiosensitive tumours, RFA may offer a superior alternative where dose-escalated SBRT is not possible.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
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 | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".