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Record W4390783373 · doi:10.3389/fonc.2023.1322262

The association between graded prognostic assessment and the prognosis of brain metastases after whole brain radiotherapy: a meta-analysis

2024· review· en· W4390783373 on OpenAlexaboutno aff
Xiaohan Geng, Changgui Kou, Jianfeng Wang

Bibliographic record

VenueFrontiers in Oncology · 2024
Typereview
Languageen
FieldMedicine
TopicBrain Metastases and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsMeta-analysisMedicineRadiation therapyOncologyWhole brain radiotherapyInternal medicineBrain cancerBrain metastasisCancerMetastasis

Abstract

fetched live from OpenAlex

Introduction: This meta-analysis aims to provide evidence-based medical evidence for formulating rational treatment strategies and evaluating the prognosis of brain metastasis (BM) patients by assessing the effectiveness of the graded prognostic assessment (GPA) model in predicting the survival prognosis of patients with BM after whole-brain radiotherapy (WBRT). Methods: A comprehensive search was conducted in multiple databases, including the China Biomedical Literature Database (CBM), China National Knowledge Infrastructure (CNKI), PubMed, Wanfang database, Cochrane Library, Web of Science, and Embase. Cohort studies that met the inclusion and exclusion criteria were selected. The quality of the included literature was evaluated using the Newcastle-Ottawa Scale, and all statistical analyses were performed with R version 4.2.2. The effect size (ES) was measured by the hazard ratio (HR) of overall survival (OS). The OS rates at 3, 6, 12, and 24 months of patients with BM were compared between those with GPAs of 1.5-2.5, 3.0, and 3.5-4.0 and those with GPAs of 0-1 after WBRT. Results: A total of 1,797 participants who underwent WBRT were included in this study. The meta-analysis revealed a significant association between GPA and OS rates after WBRT: compared with BM patients with GPA of 0-1, 3-month OS rates after WBRT were significantly higher in BM patients with GPA of 1.5-2.5 (HR = 0.48; 95% CI: 0.40-0.59), GPA of 3 (HR = 0.38; 95% CI: 0.25-0.57), and GPA of 3.5-4 (HR = 0.28; 95% CI: 0.15-0.52); 6-month OS rates after WBRT were significantly higher in BM patients with GPA of 1.5-2.5 (HR = 0.48; 95% CI: 0.41-0.56), GPA of 3 (HR = 0.33; 95% CI: 0.24-0.45), and GPA of 3.5-4 (HR = 0.24; 95% CI: 0.16-0.35); 12-month OS rates after WBRT were significantly higher in BM patients with GPA of 1.5-2.5 (HR = 0.49; 95% CI: 0.41-0.58), GPA of 3 (HR = 0.48; 95% CI: 0.32-0.73), and GPA of 3.5-4 (HR = 0.31; 95% CI: 0.12-0.79); and 24-month OS rates after WBRT were significantly higher in BM patients with GPA of 1.5-2.5 (HR = 0.49; 95% CI: 0.42-0.58), GPA of 3 (HR = 0.49; 95% CI: 0.32-0.74), and GPA of 3.5-4 (HR = 0.38; 95% CI: 0.15-0.94). Conclusion: BM patients with higher GPAs generally exhibited better prognoses and survival outcomes after WBRT compared to those with lower GPAs. Systematic review registration: https://www.crd.york.ac.uk/prospero/, identifier CRD42023422914.

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 imitation

Not 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.

metaresearch head score (Codex)0.017
metaresearch head score (Gemma)0.033
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.017
Threshold uncertainty score0.091

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0170.033
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0120.053
Bibliometrics0.0040.005
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0020.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.060
GPT teacher head0.403
Teacher spread0.343 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
Domainnot available
GenreReview

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".

Quick stats

Citations1
Published2024
Admission routes1
Has abstractyes

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