Recent Trends in Synchronous Brain Metastasis Incidence and Mortality in the United States: Ten-Year Multicenter Experience
Bibliographic record
Abstract
BACKGROUND: Large epidemiological studies describing the trends in incidence rates and mortality of synchronous brain metastases (SBMs) are lacking. The study aimed to provide a comprehensive understanding of the changes in the incidence and mortality of SBMs over the previous ten years. METHODS: Trends in the incidence of solid malignancies outside of the CNS in patients with SBMs and incidence-based mortality rates were assessed using data from the Surveillance, Epidemiology, and End Results database. Joinpoint analyses were used to calculate annual percent changes (APCs) and 95% CIs. RESULTS: Between 2010 and 2019, 66,655 patients, including 34,821 (52.24%) men and 31,834 (47.76%) women, were found to have SBMs, and 57,692 deaths occurred over this period. Lung cancer SBMs, melanoma SBMs, and breast cancer SBMs were ranked in the top three, having the highest age-standardized incidence rates. The incidence of SBMs decreased significantly with an APC of -0.6% from 2010 to 2019, while the APC was 1.2% for lung cancer SBMs, 2.5% for melanoma SBMs, and 0.6% for breast cancer SBMs. The SBM mortality first experienced a rapid increase (APC = 28.6%) from 2010 to 2012 and then showed a significant decline at an APC of -1.8% from 2012 to 2019. Lung cancer SBMs showed similar trends, while melanoma SBM and breast cancer SBM mortality increased continuously. CONCLUSIONS: SBMs incidence (2010-2019) and incidence-based mortality (2012-2019) declined significantly. These findings can advance our understanding of the prevalence of SBMs.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.001 | 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".