Identification of a Novel MicroRNA Panel Associated with Metastasis Following Radical Prostatectomy for Prostate Cancer
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND/AIM: This is a case control study designed to identify one or more novel microRNA sequences associated with metastasis following radical prostatectomy for clinically localized prostate cancer. MATERIALS AND METHODS: Samples were obtained from patients with clinical evidence of metastatic disease following surgery (cases) and patients who showed no evidence of metastasis or biochemical recurrence at least 5 years following surgery (controls) as identified from a single-center, institutional database. Cases and controls were matched for tumor grade and duration of follow-up. RESULTS: Whole miRNome analysis identified 2,792 expressed miRNAs in 19 patient pairs. The 497 miRNA sequences with reads per million over 10, were used for analysis, bootstrapping with backward selection identified a panel of 5-miRNA (miR-17-3p, miR-27a-3p, miR-200a-3p, miR-375, and miR-376b-3p) with a risk score strongly associated with metastasis (AUC=89.5%, 95%CI=79.5-99.5%). Methodologically, most studies use the magnitude of differential expression with or without clinical judgement for selection of predictors for inclusion in panels. In order to strengthen the predictive model, a selection strategy was employed, bootstrapping with automated backwards selection, which relied on the strength of association for inclusion. CONCLUSION: A genome-wide analysis of microRNA expression identified a panel of 5 miRNAs strongly associated with prostate cancer metastasis following radical prostatectomy.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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