Renal cell carcinoma bone metastases: clinical advances
Bibliographic record
Abstract
Bone is a common site of metastatic spread in patients with advanced renal cell carcinoma (RCC) occurring in around one-third of patients enrolled in clinical trials evaluating modern systemic therapies for this disease. Until recently, limited systemic therapeutic options were available for advanced RCC. Nowadays, a quiver of agents have demonstrated activity, including compounds targeting the vascular endothelial growth factor (VEGF) axis and those targeting the mammalian target of rapamycin (mTOR). Despite a detailed biological understanding of how these drugs work, their effect on bony metastases is less clear. Data suggesting that bisphosphonates (namely zoledronic acid) benefit patients with bone metastases from advanced RCC was gathered prior to the targeted therapy era; therefore, there is some uncertainty about their role in patients on modern RCC therapies. This review summarizes the current targeted therapies registered for use in advanced RCC and postulates how some of them might affect the behavior of bone metastases. It also explores the data available on the role of bisphosphonates for bone metastases from RCC, describes methods of assessing response to therapy for bone metastases and delineates future expectations for the treatment of bone metastases from advanced 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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".