Safety and clinical efficacy of everolimus in the treatment of advanced renal cell carcinoma (RCC)
Bibliographic record
Abstract
Renal cell carcinoma (RCC) is one of the most lethal genitourinary malignancies. Recently, there has been a paradigm shift in the management of advanced RCC. New targeted therapies including vascular endothelial growth factor (VEGF) and mammalian target of rapamycin (mTOR) inhibitors have been developed which have shown promising results in a patient population who otherwise had very few options for treatment. The first mTOR inhibitor, temsirolimus, an intravenous prodrug, has shown improved overall survival in poor prognosis patients. More recently, an oral mTOR inhibitor, everolimus (RAD 001), has been developed which has been shown to delay disease progression in patients with metastatic RCC who have progressed on other targeted therapies. Although a survival advantage in phase III trials is seen with everolimus, associated systemic toxicities, while generally well tolerated, are not insignificant. These include mucositis, hyperglycemia, hyperlipidemia, and pneumonitis. Despite the side effects, emerging evidence points to everolimus as the optimal second-line treatment for patients with advanced renal cell carcinoma.
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 | 0.002 | 0.002 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".