A Randomized Trial of Stereotactic Body Radiation Therapy vs Radiofrequency Ablation for the Treatment of Small Renal Masses: A Feasibility Study (RADSTER)
Bibliographic record
Abstract
Objective To evaluate the feasibility of a trial comparing stereotactic beam radiation therapy (SBRT) and radiofrequency ablation (RFA) for small renal masses (SRM). Methods Patients opting for treatment of a SRM at a single center were randomized 1:1 to SBRT or RFA. Crossover if ineligible for treatment after randomization was allowed. Biopsies were completed prior to randomization and 12 months post-treatment. Our primary outcome was feasibility of the trial design. Secondary outcomes included treatment efficacy and safety. Results Over 18 months, 33 patients were screened resulting in the recruitment and randomization of 24 patients (SBRT = 12; RFA = 12). Fourteen received SBRT, 7 RFA, and 3 dropped out. Crossover occurred from RFA to SBRT due to inability to perform RFA. Mean estimated glomerular filtration rate (EGFR) reduction was similar at 1 year (RFA −3 ml/minutes/1.73 m 2 , SBRT −5.3 ml/minutes/1.73 m 2 , P = .7). One-year biopsies were performed in 95.2% (20/21) of patients receiving treatment. Per protocol analysis demonstrated a higher pathologic response (RFA 100% vs SBRT 33.3.%, P = .01) in patients undergoing RFA compared to SBRT but not in the intention to treat analysis. No patients developed local failure, metastasis or death during the study period. Conclusion Recruitment, randomization, and follow-up of patients with SRMs was feasible and our results support performing a larger randomized trial. Multidisciplinary evaluation of patients before randomization is needed to assess RFA feasibility to reduce crossover. Both treatments have excellent short-term safety profiles. While not a surrogate for clinical response, RFA had a non-statistically significant improvement in pathological response. Clinicaltrials.gov: NCT03811665
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.004 |
| 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".