Outcomes of Patients with Brain Metastases from Renal Cell Carcinoma Receiving First-line Therapies: Results from the International Metastatic Renal Cell Carcinoma Database Consortium
Bibliographic record
Abstract
Patients with brain metastases (BrM) from renal cell carcinoma and their outcomes are not well characterized owing to frequent exclusion of this population from clinical trials. We analyzed data for patients with or without BrM using the International Metastatic Renal Cell Carcinoma Database Consortium (IMDC). A total of 389/4799 patients (8.1%) had BrM on initiation of systemic therapy. First-line immuno-oncology (IO)-based combination therapy was associated with longer median overall survival (OS; 32.7 mo, 95% confidence interval [CI] 22.3-not reached) versus tyrosine kinase inhibitor monotherapy (20.6 mo, 95% CI 15.7-24.5; p = 0.019), as were intensive focal therapies with stereotactic radiotherapy or neurosurgery (31.4 mo, 95% CI 22.3-37.5) versus whole-brain radiotherapy alone or no focal therapy (16.5 mo, 95% CI 10.2-21.1; p = 0.028). On multivariable analysis, IO-based regimens (HR 0.49, 95% CI 0.25-0.97; p = 0.040) and stereotactic radiotherapy or neurosurgery (HR 0.48, 95% CI 0.29-0.78; p = 0.003) were independently associated with longer OS, as was IMDC favorable or intermediate risk (HR 0.40, 95% CI 0.24-0.66; p < 0.001). Intensive systemic and focal therapies were associated with better prognosis in this population. Further studies should explore the clinical effectiveness of multimodal strategies. PATIENT SUMMARY: In a large group of patients with advanced kidney cancer, we found that 8.1% had brain metastases when starting systemic therapy. Patients with brain metastases had significantly poorer prognosis than those without brain metastases. Receipt of combination immunotherapy, stereotactic radiotherapy, or neurosurgery was associated with longer overall survival.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".