Pazopanib-Induced Regression of Brain Metastasis After Whole Brain Palliative Radiotherapy in Metastatic Renal Cell Cancer Progressing on First-Line Sunitinib: A Case Report
Bibliographic record
Abstract
Pervious randomized studies have demonstrated survival benefit in favor of tyrosine kinase inhibitors (TKIs) compared to cytokines in metastatic clear cell renal cell carcinoma (RCC). However, the role of TKIs for treating brain metastasis from RCC remains unknown. Previous studies have reported possible activity of sunitinib and sorafenib in RCC patients with brain metastasis. We report on patient with metastatic RCC who responded to first-line sunitinib but then progressed with multiple brain metastasis, but with controlled extra-cranial metastatic disease. The patient was treated with whole-brain palliative radiotherapy followed by treatment schedule of pazopanib at standard dose of 800 mg/day which was associated with a response in brain metastasis. Subsequently, she was re-challenged at reduced dose of 600 mg/day and developed further response in metastatic brain lesions. She lived for more than 3 years from initial diagnosis of brain metastasis. This is the first case report of sequential TKI therapy for treating metastatic RCC with brain metastasis and supports the probable use of pazopanib as potent TKI for treating patients with cerebral metastasis.
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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 | 0.002 | 0.000 |
| 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 | 0.000 |
| 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".