Management of Patients with Advanced Prostate Cancer: Report from the Advanced Prostate Cancer Consensus Conference 2021
Bibliographic record
Abstract
BACKGROUND: Innovations in treatments, imaging, and molecular characterisation in advanced prostate cancer have improved outcomes, but various areas of management still lack high-level evidence to inform clinical practice. The 2021 Advanced Prostate Cancer Consensus Conference (APCCC) addressed some of these questions to supplement guidelines that are based on level 1 evidence. OBJECTIVE: To present the voting results from APCCC 2021. DESIGN, SETTING, AND PARTICIPANTS: The experts identified three major areas of controversy related to management of advanced prostate cancer: newly diagnosed metastatic hormone-sensitive prostate cancer (mHSPC), the use of prostate-specific membrane antigen ligands in diagnostics and therapy, and molecular characterisation of tissue and blood. A panel of 86 international prostate cancer experts developed the programme and the consensus questions. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: The panel voted publicly but anonymously on 107 pre-defined questions, which were developed by both voting and non-voting panel members prior to the conference following a modified Delphi process. RESULTS AND LIMITATIONS: The voting reflected the opinions of panellists and did not incorporate a standard literature review or formal meta-analysis. The answer options for the consensus questions received varying degrees of support from panellists, as reflected in this article and the detailed voting results reported in the Supplementary material. CONCLUSIONS: These voting results from a panel of experts in advanced prostate cancer can help clinicians and patients to navigate controversial areas of management for which high-level evidence is scant. However, diagnostic and treatment decisions should always be individualised according to patient characteristics, such as the extent and location of disease, prior treatment(s), comorbidities, patient preferences, and treatment recommendations, and should also incorporate current and emerging clinical evidence and logistic and economic constraints. Enrolment in clinical trials should be strongly encouraged. Importantly, APCCC 2021 once again identified salient questions that merit evaluation in specifically designed trials. PATIENT SUMMARY: The Advanced Prostate Cancer Consensus Conference is a forum for discussing current diagnosis and treatment options for patients with advanced prostate cancer. An expert panel votes on predefined questions focused on the most clinically relevant areas for treatment of advanced prostate cancer for which there are gaps in knowledge. The voting results provide a practical guide to help clinicians in discussing treatment options with patients as part of shared 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 | 0.091 | 0.110 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.006 | 0.006 |
| 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".