Stereotactic ablative radiotherapy for primary kidney cancer – An international patterns of practice survey
Bibliographic record
Abstract
Purpose: To conduct an international survey of radiation oncologists treating primary renal cell carcinoma (RCC) with SABR to ascertain the general patterns of SABR use, common dose/treatment/follow-up details, and expected outcomes. Materials and methods: A 51-question survey was created containing the following themes: prevalence and clinical scenarios in which RCC SABR is used, dose-fractionation schedules, treatment delivery details, follow-up/outcome assessments, and implementation barriers. The survey was distributed widely across multiple influential radiation oncology societies and social media, and ran from January to April 2023. Results: A total of 255 respondents participated, mostly from academic centers within Europe/North America. Of these, 40 % (n = 102) currently offer SABR (50 % having begun within the last 3 years). Common barriers in non-users included lack of referrals by urologists and lack of supportive practice guidelines. Of respondents who do offer SABR, 77 % treat both small (4 cm or less) and large (>4 cm) renal masses. Dose-fractionation strategies varied from 27-52 Gy (3-5 fractions) for multifraction regimens, and 15-34 Gy for single fractions. Apart from treatment for medically inoperable disease, scenarios in which SABR was likely to be offered were for recurrence post surgery/thermal ablation and for oligometastatic kidney lesions. Uncommon scenarios included RCC with renal vein/inferior vena cava thrombosis, and as cytoreductive therapy in metastatic RCC. Expected local control outcomes were generally above 70 %, higher for small versus large renal masses. Conclusions: SABR is a relatively newer indication for primary RCC, offered by less than 50% of respondents, with both consistent and variable practice patterns observed.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".