Current systemic management of metastatic renal cell carcinoma – first line and second line therapy
Bibliographic record
Abstract
PURPOSE OF REVIEW: The improved understanding of the complex biochemical and genetic pathways associated with renal-cell carcinoma (RCC) has led to rapid development of novel targeted therapies over the last decade. The aim of this review is to present and discuss the most recent clinical trial data that support the currently approved first and second line agents in the treatment of metastatic renal cell carcinoma (mRCC). New directions in treatment will also be explored. RECENT FINDINGS: The currently approved first and second line agents for the treatment of mRCC include sunitinib, pazopanib, sorafenib, bevacizumab, temsirolimus, and everolimus. Each of these new agents has shown meaningful clinical benefit in phase III trials and as a group they have replaced cytokines as the frontline therapy for advanced and mRCC. Several new agents are currently being evaluated in phase II and III studies that may provide further benefit in the future. SUMMARY: The treatment paradigm for mRCC had drastically changed over the last decade bringing new hope for improved outcomes and ongoing advances. In spite of recent headway, mRCC remains a disease with no curative therapy and more effective treatment options are needed.
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 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) | 0.000 | 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".