Consensus Statement on Circulating Biomarkers for Advanced Prostate Cancer
Bibliographic record
Abstract
CONTEXT: In advanced prostate cancer (PC), there is increasing investigation of circulating biomarkers, including quantitation and characterization of circulating tumour cells and cell-free nucleic acids, for therapeutic monitoring and as prognostic and predictive biomarkers. However, there is a lack of consensus and standardisation regarding analyses, reporting, and integration of results into specific clinical contexts. A consensus meeting on circulating biomarkers was held to address these topics. OBJECTIVE: To present a report of the consensus statement on circulating biomarkers in advanced PC. EVIDENCE ACQUISITION: Four important areas of controversy in the field of circulating biomarkers in PC management were identified: known clinical utility of circulating biomarkers; unmet clinical needs for circulating biomarkers in PC care; most pressing blood-based molecular assays required; and essential steps for developing circulating biomarker assays. A panel of 18 international PC experts in the field of circulating biomarkers developed the programme and consensus questions. The panel voted publicly but anonymously on 50 predefined questions developed following a modified Delphi process. EVIDENCE SYNTHESIS: Voting was based solely on panellist opinions of the predefined topics and therefore not on a standard literature review or meta-analysis. The outcomes of the voting had varying degrees of support, as reflected in the wording of this article and in the detailed voting results provided in the Supplementary material. CONCLUSIONS: The expert voting results presented can guide the future development of circulating biomarkers for PC care. Notably, the consensus meeting highlighted the importance of reproducibility and variability studies, among other significant areas in need of trials specifically designed to address them. PATIENT SUMMARY: A panel of international experts met to discuss and vote on the use of different blood-based prostate cancer tests, and how they can be used to guide treatment and disease monitoring to deliver more precise and better patient care.
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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 | 0.147 | 0.205 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.011 |
| Bibliometrics | 0.007 | 0.004 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.010 | 0.012 |
| Research integrity | 0.027 | 0.024 |
| Insufficient payload (model declined to judge) | 0.011 | 0.010 |
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".