Salvage stereotactic ablative body radiotherapy after thermal ablation of primary kidney cancer
Bibliographic record
Abstract
OBJECTIVE: To evaluate the effectiveness and safety of salvage stereotactic ablative body radiotherapy (SABR) for recurrent renal cell carcinoma (RCC) after thermal ablation (TA). MATERIALS AND METHODS: This study was a multi-institutional retrospective analysis of patients with recurrent RCC following TA who received SABR between 2016 and 2020. The primary study outcome was freedom from local failure, evaluated radiographically based on Response Evaluation Criteria in Solid Tumours (RECIST) v1.1. Distant failure, cancer-specific survival (CSS), overall survival (OS), treatment-related toxicity and renal function changes following SABR were the secondary outcomes. The Kaplan-Meier method was used to estimate freedom from local and distant failure, CSS and OS. RESULTS: Seventeen patients with 18 biopsy-confirmed RCCs were included, with a median (interquartile range [IQR]) age at time of SABR of 75.2 (72.6-68.7) years, a median (IQR) tumour size of 3.5 (1.9-4.1) cm and follow-up (reverse Kaplan-Meier method) of 3.36 (95% confidence interval [CI] 1.6-4.1) years. Six of the 17 patients had a solitary kidney. Five patients had failed repeat TA prior to SABR. The median (IQR) time from TA procedure to SABR was 3.03 (1.5-5.1) years. No patient experienced local progression, with a local control rate of 100%. Four patients, two with baseline metastatic disease, experienced distant progression. The distant progression-free survival, CSS and OS at 3 years were 72.1% (95% CI 51.9%-100%), 92.3% (95% CI 78.9%-100%) and 82.1% (95% CI 62.1%-100%), respectively. The median (IQR) glomerular filtration rate before SABR was 58 (40-71) mL/min, and at last follow-up, it was 48 (33-57) mL/min. No patient experienced grade 3+ toxicity or went on to develop end-stage renal disease. CONCLUSION: The results showed that SABR appears to be an effective and safe salvage strategy in patients with recurrent RCC following TA.
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 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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) | 0.001 | 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".