Brain Metastases in Gynaecologic Cancer: A Retrospective Cohort Study Evaluating Treatment Outcomes, Prognostic Factors, and Overall Survival
Bibliographic record
Abstract
(1) Background: The objectives of this study were to assess survival of patients with a diagnosis of brain metastases secondary to gynaecologic malignancy and the impact of clinicopathological factors on prognosis in this population. (2) Methods: A retrospective cohort of patients with gynaecologic cancers diagnosed with brain metastases treated with radiation at a tertiary care centre from 1 January 2004 until 30 September 2023 was studied. Kaplan-Meier method and log-rank test were used to evaluate survival, and cox regression was used to identify significant predictive factors of survival. (3) Results: In total, 103 patients were included in this study. Median age at diagnosis of brain metastases was 59 (range 30-94). Median survival time following diagnosis of brain metastases was 3.6 months (range 0.4-183.8). Survival was significantly longer for patients treated with surgery combined with radiation compared to radiation alone and with stereotactic radiosurgery (SRS) compared to whole brain radiation therapy (WBRT). Cox regression revealed that primary ovarian malignancy, extracranial disease at diagnosis, and ≥3 brain metastases were associated with poorer prognosis, and complete response to prior treatment was associated with more favourable prognosis. (4) Conclusions: Data from this study will assist in providing evidence-based prognostic information to patients with gynaecologic malignancy diagnosed with brain metastases.
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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 | 0.001 | 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) | 0.001 | 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 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".