Best Current Practice and Research Priorities in Active Surveillance for Prostate Cancer—A Report of a Movember International Consensus Meeting
Bibliographic record
Abstract
BACKGROUND: Active surveillance (AS) is recommended for low-risk and some intermediate-risk prostate cancer. Uptake and practice of AS vary significantly across different settings, as does the experience of surveillance-from which tests are offered, and to the levels of psychological support. OBJECTIVE: To explore the current best practice and determine the most important research priorities in AS for prostate cancer. DESIGN, SETTING, AND PARTICIPANTS: A formal consensus process was followed, with an international expert panel of purposively sampled participants across a range of health care professionals and researchers, and those with lived experience of prostate cancer. Statements regarding the practice of AS and potential research priorities spanning the patient journey from surveillance to initiating treatment were developed. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Panel members scored each statement on a Likert scale. The group median score and measure of consensus were presented to participants prior to discussion and rescoring at panel meetings. Current best practice and future research priorities were identified, agreed upon, and finally ranked by panel members. RESULTS AND LIMITATIONS: There was consensus agreement that best practice includes the use of high-quality magnetic resonance imaging (MRI), which allows digital rectal examination (DRE) to be omitted, that repeat standard biopsy can be omitted when MRI and prostate-specific antigen (PSA) kinetics are stable, and that changes in PSA or DRE should prompt MRI ± biopsy rather than immediate active treatment. The highest ranked research priority was a dynamic, risk-adjusted AS approach, reducing testing for those at the least risk of progression. Improving the tests used in surveillance, ensuring equity of access and experience across different patients and settings, and improving information and communication between and within clinicians and patients were also high priorities. Limitations include the use of a limited number of panel members for practical reasons. CONCLUSIONS: The current best practice in AS includes the use of high-quality MRI to avoid DRE and as the first assessment for changes in PSA, with omission of repeat standard biopsy when PSA and MRI are stable. Development of a robust, dynamic, risk-adapted approach to surveillance is the highest research priority in AS for prostate cancer. PATIENT SUMMARY: A diverse group of experts in active surveillance, including a broad range of health care professionals and researchers and those with lived experience of prostate cancer, agreed that best practice includes the use of high-quality magnetic resonance imaging, which can allow digital rectal examination and some biopsies to be omitted. The highest research priority in active surveillance research was identified as the development of a dynamic, risk-adjusted approach.
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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 | 0.416 | 0.253 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.005 | 0.010 |
| Bibliometrics | 0.010 | 0.009 |
| Science and technology studies | 0.007 | 0.005 |
| Scholarly communication | 0.014 | 0.014 |
| Open science | 0.016 | 0.025 |
| Research integrity | 0.022 | 0.024 |
| 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".