Epidemiology of synchronous brain metastases
Bibliographic record
Abstract
Abstract Background The objectives of this study were to characterize (1) epidemiology of brain metastases at the time of primary cancer diagnosis, (2) incidence and trends of synchronous brain metastases from 2010 to 2015, and (3) overall survival (OS) of patients with synchronous brain metastases. Methods A total of 42 047 patients with synchronous brain metastases from 2010 to 2015 were identified from the Surveillance, Epidemiology, and End Results database. Descriptive analysis was utilized to analyze demographics and incidence. The Kaplan–Meier method and a Cox proportional hazards model were utilized to evaluate potential prognostic factors for OS. Results The majority of patients were diagnosed from age older than 50 (91.9%). Common primary sites included lung (80%), melanoma (3.8%), breast (3.7%), and kidney/renal pelvis (3.0%). Among pediatric patients, common primaries included kidney/renal pelvis and melanomas. The incidence was roughly 7.3 persons/100 000. Synchronous brain metastases were associated with significantly poorer OS compared to extracranial metastases alone (hazard ratio [HR] =1.56; 95% CI: 1.54–1.58; P < .001). Among patients with brain metastases, male gender (HR = 1.60 vs 1.52), age older than 65 years (HR = 1.60 vs 1.46), synchronous liver, bone, or lung metastases (HR = 1.61 vs 1.49), and earlier year of diagnosis (HR = 0.98 for each year following 2010) were associated with significantly poorer OS. Conclusions The vast majority of brain metastases are from lung primaries. Synchronous brain metastases are associated with poorer OS compared to extracranial metastases alone.
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".