Semantics in active surveillance for men with localized prostate cancer — results of a modified Delphi consensus procedure
Bibliographic record
Abstract
Semantic heterogeneity exists regarding terminology for active surveillance (AS) for prostate cancer. A panel of leading specialists in prostate cancer and AS involved in the Movember Foundation's Global Action Plan Prostate Cancer Active Surveillance (GAP3) consortium participated in a consensus-forming project to reach international consensus on definitions of terms related to this management option. This standard terminology could support multidisciplinary communication, reduce the extent of variations in clinical practice and optimize clinical decision making. Active surveillance (AS) is broadly described as a management option for men with low-risk prostate cancer, but semantic heterogeneity exists in both the literature and in guidelines. To address this issue, a panel of leading prostate cancer specialists in the field of AS participated in a consensus-forming project using a modified Delphi method to reach international consensus on definitions of terms related to this management option. An iterative three-round sequence of online questionnaires designed to address 61 individual items was completed by each panel member. Consensus was considered to be reached if ≥70% of the experts agreed on a definition. To facilitate a common understanding among all experts involved and resolve potential ambiguities, a face-to-face consensus meeting was held between Delphi survey rounds two and three. Convenience sampling was used to construct the panel of experts. In total, 12 experts from Australia, France, Finland, Italy, the Netherlands, Japan, the UK, Canada and the USA participated. By the end of the Delphi process, formal consensus was achieved for 100% (n = 61) of the terms and a glossary was then developed. Agreement between international experts has been reached on relevant terms and subsequent definitions regarding AS for patients with localized prostate cancer. This standard terminology could support multidisciplinary communication, reduce the extent of variations in clinical practice and optimize clinical decision making.
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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 | 0.212 | 0.270 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".