Stereotactic body radiotherapy for the treatment of medically inoperable primary renal cell carcinoma: Current evidence and future directions
Bibliographic record
Abstract
The incidence of renal cell carcinoma (RCC) is steadily rising due to an aging population and more frequent imaging of the abdomen for other medical conditions. While surgery remains the standard of care treatment for localized disease, many patients are unfit due to their advanced age and medical comorbidities. In these patients, an active surveillance strategy or ablative therapies, including radiofrequency/microwave ablation or cryotherapy, can be offered. Such options have limitations particularly with fast growing, or larger tumors. A promising ablative therapy option to consider is stereo-tactic body radiotherapy (SBRT). SBRT refers to high dose, focally ablative radiation delivered in a short time (3-5 fractions), and is safe and effective in many other cancer sites, including lung, liver and spine. SBRT offers potential advantages in the primary kidney cancer setting due to its ablative dosing (overcoming the notion of "radio-resistance"), short treatment duration (important in an elderly population), low toxicity profile (enabling SBRT to treat larger RCCs than other ablative modalities), and non-invasiveness. To date, there is limited long-term prospective data on the outcomes of SBRT in primary RCC. However, early evidence is intriguing with respect to excellent local control and low toxicity; however, most studies vary in terms of technique and radiation dosing used. Well-designed prospective cohort studies with clearly defined and standardized techniques, dosing, follow-up, and integration of quality of life outcomes will be essential to further establish the role of SBRT in management of inoperable, localized RCC.
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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".