Prostate cancer risk biomarkers from large cohort and prospective metabolomics studies: A systematic review
Why this work is in the frame
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Bibliographic record
Abstract
• To the best of our knowledge, this is the first systematic review exclusively focused on plasma/serum risk assessment biomarkers for prostate cancer (PCa), selected through a careful examination of large prospective studies. By focusing only in homogeneous studies and similar inclusion criteria and methodologies, we can provide more conclusive results. • We propose a preliminary set of 42 metabolites potentially involved in PCa development and progression. Those metabolites were coincident across at least two large cohort studies included in the present work, where sample collection was done years before PCa diagnosis. Some of these metabolites, such as citrate, may be considered for translational clinical applications. • Correlations between metabolites and dietary sources are evident for few of the detected metabolites, although further investigation is needed to establish the associations between both dietary and environmental exposures, and PCa risk and prognosis. Prostate cancer (PCa) is one of the leading causes of cancer-related deaths among men. The heterogeneous nature of this disease presents challenges in its diagnosis, prognosis, and treatment. Numerous potential predictive, diagnostic, prognostic, and risk assessment biomarkers have been proposed through various population studies. However, to date, no metabolite biomarker has been approved or validated for the diagnosis, prognosis, or risk assessment of PCa. Recognizing that systematic reviews of case reports or heterogenous studies cannot reliably establish causality, this review analyzed 29 large prospective metabolomics studies that utilized harmonized criteria for patient selection, consistent methodologies for blood sample collection and storage, data analysis, and that are available in public repositories. By focusing on these large prospective studies, we identified 42 metabolites that were consistently replicated by different authors and across cohort studies. These metabolites have the potential to serve as PCa risk-assessment or predictive biomarkers. A discussion on their associations with dietary sources or dietary patterns is also provided. Further detailed exploration of the relationship with diet, supplement intake, nutrition patterns, contaminants, lifestyle factors, and pre-existing comorbidities that may predispose individuals to PCa is warranted for future research and validation.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| 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