Genitourinary microbiomes and prostate cancer: a systematic review and meta-analysis of tumorigeneses and cancer characteristics
Why this work is in the frame
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Bibliographic record
Abstract
Introduction: We assessed the association of genitourinary microbiomes with prostate cancer (PCa) tumorigeneses and cancer characteristics. Material and methods: A systematic search and meta-analysis was performed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement. The primary endpoints were the association between relative abundance of genitourinary microbiomes and PCa compared to non-cancerous men/prostate specimen, high grade disease, and disease progression. The odds ratio (OR) was used as the summary statistic, and results were reported with 95% confidence intervals (CI). Results: Seventeen studies, comprising 2,195 patients were eligible for review and meta-analysis. The specific microbiomes in urine, prostate tissue, and prostate (or seminal) secretions were significantly more abundant in patients with PCa compared to men in the control groups in individual studies. Certain bacterial phyla, genuses, and species were significantly associated with PCa aggressiveness and disease progression in individual studies. The relative abundance meta-analysis of five urine microbiomes revealed no statistically significant differences between PCa patients and control groups (pooled OR, 1.35; 95% CI: 0.70-2.59). Conclusions: Our systematic review indicates that specific genitourinary microbiomes are more abundant in PCa and have a potential to predict/prognosticate disease aggressiveness and clinical outcomes. Nevertheless, these findings should be interpreted with caution owing to the significant heterogeneity among studies in terms of microbiome analysis method, assessed sample's characteristics, and individual biological behavior of microbiomes for analysis. Further studies are needed to validate these observations and shed more light on the role of the microbiome across the development and natural history of PCa.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.000 |
| 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