Consensus statement on circulating biomarkers for advanced prostate cancer.
Bibliographic record
Abstract
299 Background: The need for validated circulating biomarkers is well recognised in advanced prostate cancer (PCa). Circulating biomarkers evaluating plasma cell-free nucleic acids and circulating tumour cells are being investigated for their clinical utility. There has been a lack of consensus with regards to analyses, reporting and clinical effectiveness of these biomarkers. A consensus meeting was held to address these issues. Methods: A multi-disciplinary panel comprising 18 international prostate cancer experts (including surgeons, medical and radiation oncologists) were consulted prior to the consensus meeting. Four key areas relating to the field of circulating biomarkers were deemed important for discussion: 1) The current utility of circulating biomarkers in 2017; 2) The clinical needs for circulating biomarkers in PCa; 3) The most pressing blood-based molecular assays required; and 4) The steps necessary for developing circulating biomarkers. Using a modified Delphi process, 50 consensus questions were pre-defined for the panel to answer by voting anonymously but publicly at the consensus meeting. Results: A consensus was declared (i.e. ≥ 75% of panellists who did not vote ‘unqualified’ or ‘abstain’ chose the same opinion) in 12/50 (24%) questions. A further 8/50 (16%) of replies were close to reaching consensus (≥ 60% of panellists choosing the same answer). The panel agreed that there is a very high and urgent unmet need for predictive biomarkers, with consensus that DNA repair biomarkers in particular are needed urgently. Metastatic PCa was identified as having the highest clinical need for development of biomarkers to measure response and as surrogate endpoints. Panellists unanimously voted that reproducibility validation studies are of paramount importance. The consensus panel also predicted that cfDNA will impact practice by 2020. Conclusions: This expert consensus identified the need for clinical trials of validated circulating biomarkers to develop predictive, response and surrogacy assays. These could have major clinical and healthcare economic implications, minimizing over-treatment and allowing the delivery of more precise 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 | 0.093 | 0.116 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.007 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.007 | 0.011 |
| Research integrity | 0.022 | 0.017 |
| Insufficient payload (model declined to judge) | 0.016 | 0.016 |
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".