The incidence of brain metastases among patients with metastatic breast cancer: a systematic review and meta-analysis
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Patients with metastatic breast cancer (MBC) are living longer, but the development of brain metastases often limits their survival. We conducted a systematic review and meta-analysis to determine the incidence of brain metastases in this patient population. METHODS: Articles published from January 2000 to January 2020 were compiled from four databases using search terms related to breast cancer, brain metastasis, and incidence. The overall and per patient-year incidence of brain metastases were extracted from studies including patients with human epidermal growth factor receptor-2 positive (HER2+), triple negative, and hormone receptor (HR)+/hormone receptor negative (HER2-) MBC; pooled overall estimates for incidence were calculated using random effects models. RESULTS: 937 articles were compiled, and 25 were included in the meta-analysis. Incidence of brain metastases in patients with HER2+ MBC, triple negative MBC, and HR+/HER2- MBC was reported in 17, 6, and 4 studies, respectively. The pooled cumulative incidence of brain metastases was 31% for the HER2+ subgroup (median follow-up: 30.7 months, IQR: 24.0-34.0), 32% for the triple negative subgroup (median follow-up: 32.8 months, IQR: 18.5-40.6), and 15% among patients with HR+/HER2- MBC (median follow-up: 33.0 months, IQR: 31.9-36.2). The corresponding incidences per patient-year were 0.13 (95% CI: 0.10-0.16) for the HER2+ subgroup, 0.13 (95%CI: 0.09-0.20) for the triple negative subgroup, and only 0.05 (95%CI: 0.03-0.08) for patients with HR+/HER2- MBC. CONCLUSION: There is a high incidence of brain metastases among patients with HER2+ and triple negative MBC. The utility of a brain metastases screening program warrants investigation in these populations.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.016 | 0.002 |
| Bibliometrics | 0.000 | 0.002 |
| 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 it