Targeted inhibition of mammalian target of rapamycin for the treatment of advanced renal cell carcinoma
Bibliographic record
Abstract
Clinical trials have validated the importance of mammalian target of rapamycin (mTOR) as a targeted mechanism in the treatment of renal cell carcinoma (RCC). Temsirolimus, an mTOR inhibitor that is approved for treatment of advanced RCC, has demonstrated both overall survival benefits and progression-free survival benefits versus interferon-alpha as first-line treatment for patients with poor prognostic features. Exploratory subset analyses indicated that temsirolimus benefits patients with RCC regardless of tumor histology or nephrectomy status. Everolimus, the second mTOR inhibitor to demonstrate activity in RCC, improved progression-free survival versus placebo in patients whose disease progressed after treatment with vascular endothelial growth factor receptor tyrosine kinase inhibitors (sunitinib, sorafenib, or both); benefit was observed for all risk groups. Deforolimus also exhibited antitumor activity against RCC in early clinical studies. There is now compelling clinical evidence for the effectiveness of targeting mTOR in the treatment of 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".