A meta‐analysis evaluating stereotactic radiosurgery, whole‐brain radiotherapy, or both for patients presenting with a limited number of brain metastases
Bibliographic record
Abstract
BACKGROUND: To perform a meta-analysis on newly diagnosed brain metastases patients treated with whole-brain radiotherapy (WBRT) and stereotactic radiosurgery (SRS) boost versus WBRT alone, or in patients treated with SRS alone versus WBRT and SRS boost. METHODS: The meta-analysis primary outcomes were overall survival (OS), local control (LC), and distant brain control (DBC). Secondary outcomes were neurocognition, quality of life (QOL), and toxicity. Using published Kaplan-Meier curves, results were pooled using hazard ratios (HR). RESULTS: Two RCTs reported on WBRT and SRS boost versus WBRT alone. For multiple brain metastases (2-4 tumors) we conclude no difference in OS, and LC significantly favored WBRT plus SRS boost. Three RCTs reported on SRS alone versus WBRT plus SRS boost (1-4 tumors). There was no difference in OS despite both LC and DBC significantly favoring WBRT plus SRS boost. Although secondary endpoints could not be pooled for meta-analysis, those RCTs evaluating SRS alone conclude better neurocognition using the validated Hopkins Verbal Learning Test, no adverse risk in deteriorating Mini-Mental Status Exam scores or in maintaining performance status, and fewer late toxicities. We conclude insufficient data for QOL outcomes. CONCLUSIONS: For selected patients, we conclude no OS benefit for WBRT plus SRS boost compared with SRS alone. Although additional WBRT improves DBC and LC, SRS alone should be considered a routine treatment option due to favorable neurocognitive outcomes, less risk of late side effects, and does not adversely affect the patients performance status.
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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 | 0.014 | 0.023 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.019 | 0.070 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".