Survival outcomes and clinical characteristics of brain metastases from prostate cancer: A single-center analysis
Bibliographic record
Abstract
Abstract Background Brain metastases (BrM) from prostate cancer (PC) are rare. This study sought to evaluate their prevalence, clinical features, treatment modalities, and survival outcomes. Methods From a database of BrM patients, we analyzed 28 cases of prostate cancer treated at our center between 2008 and 2023. Results BrM from PC comprised 0.7% of cases. The majority of patients had high-risk features at PC diagnosis: median prostate-specific antigen (PSA) at diagnosis was 65.5 ng/ml (range: 3.9–784.7 ng/ml), 82% were Gleason grade group ≥ 4, and 68% had perineural invasion (PNI). At BrM diagnosis, 79% were castrate-resistant. Most patients had concurrent metastases, including bone (94%), lymph nodes (63%), or lung (6%). Fifty percent presented with a single brain lesion, and the median Graded Prognostic Assessment (GPA) score was 1.5 (range: 0.5–2.5). Patients commonly had radiographic brain edema (57%) and neurological symptoms (54%), whereas only 7% had seizures. Median overall survival (OS) was 9.4 months (95% CI: 4.8–14.8 months) after BrM diagnosis. An upward trend in OS was observed with higher GPA (P = .07). Treatment modalities, including surgery with adjuvant radiation, stereotactic radiosurgery, and whole brain radiotherapy, showed no significant difference in median OS (9.4, 10.1, and 11.0 months respectively, P = .79). OS did not significantly differ between patients with a single versus multiple BrM or patients with castrate-sensitive versus castrate-resistant PC. Conclusion BrMs from prostate cancer are rare and predominantly occur in patients with advanced, castrate-resistant disease, often accompanied by other metastases. This analysis enhances our understanding of the disease trajectory and informs treatment discussions.
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 | 0.001 |
| 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) | 0.000 | 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".