Refining partial gland ablation for localised prostate cancer: the <scp>FALCON</scp> project
Bibliographic record
Abstract
OBJECTIVES: To provide a contemporary statement on focal therapy (FT) for localised prostate cancer (PCa) from an international and diverse group of physicians treating localised PCa, with the aim of overcoming the limitations of previous consensus statements, which were restricted to early adopters, and to offer direction regarding the various aspects of FT application that are currently not well defined. MATERIALS AND METHODS: The FocAL therapy CONsensus (FALCON) project began with a 154-item online survey, developed following a steering committee discussion and literature search. Invitations to participate were extended to a large, diverse group of professionals experienced in PCa management. From 2022 to 2023, a Delphi consensus study consisting of three online rounds was conducted using the Modified Delphi method. A 1-9 Likert scale was used for the survey, which was followed by an in-person expert meeting. The threshold for achieving consensus was set at 70% agreement/disagreement. Six main aspects of FT were covered: (i) patient selection; (ii) energy source selection; (iii) treatment approach; (iv) treatment evaluation and follow-up; (v) treatment cost and accessibility; and (vi) future perspectives. RESULTS: Of 246 initial participants, 148 (60%) completed all three rounds. Based on participant feedback, 27 new statements were added in the second round, and 33 questions related to personal expertise, for which consensus was not necessary, were excluded. After the third and final round, consensus had not been reached for 69 items. These items were discussed at the in-person meeting, resulting in a consensus of 57 additional items. Consensus was finally not reached on 12 items. Given the volume of data, the voting outcomes are summarised in this article, with a detailed breakdown presented in the form of figures and tables. CONCLUSIONS: The FALCON project delivered a significant consensus on the approach to FT for localised PCa. Additionally, it highlighted gaps in our knowledge that may provide guidance for future research.
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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 | 0.021 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".