Patient opinions on controversies: In regard to low-risk prostate cancer, is Gleason 6 the old Gleason 5?
Bibliographic record
Abstract
329 Background: In 2005, the International Society of Urologic Pathology effectively eliminated Gleason patterns 1 and 2, thus removing Gleason grades 2-5 as a cancer diagnosis. Today, patients with low-risk Gleason 6 prostate cancer, prostate cancer clinicians, guideline writers, and policymakers are facing issues about whether Gleason 6 lesions should be reclassified as noncancer. Some of the issues being discussed among urologists, radiation oncologists, and pathologists focus on whether to reclassify low-risk Gleason 6 prostate lesions as a noncancer with the goal of reducing patient anxiety and financial toxicity. We also asked about biopsy methods, which affects both the low-risk and favorable intermediate-risk populations, that have been a major topic in support organizations over the past two years. We conducted this survey of patients on active surveillance to determine where patients stand on these issues to help guide clinicians, policymakers, and guideline writers. Methods: We conducted a survey in October 2022 asking patients their views on these issues. We invited patients on active surveillance or previously on active surveillance for low-risk prostate cancer to respond to a 40-question survey to share their views on a range of topics related to the diagnosis of Gleason grade 6 lesions as cancer, as well as complementary issues related to innovations in biopsy and active surveillance. We had access to email lists containing ~2,500 names from the AnCan Foundation’s Active Surveillance Virtual Support Group, Active Surveillance Patients International, Prostate Cancer Support Canada, and The Active Surveillor newsletter. Other major prostate cancer support groups also distributed links to the questionnaire posted on SurveyMonkey. Results: At the deadline for placeholders for abstracts, the survey is underway. Questions for patients include: Have you experienced distress (anxiety or depression) because of the cancer label from Gleason 6? Have you experienced financial toxicity, including cancellation of insurance policies or an increase in rates, because of the cancer diagnosis? If Gleason 6 was reclassified as a noncancer, would you stop surveillance? What will you prefer as a next biopsy--transperineal to avoid the risk of sepsis and other infections or transrectal which may cause less immediate pain? Conclusions: We intend that the results will inform decision making as to the classification of Gleason 6 diagnoses.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.017 | 0.077 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.008 | 0.007 |
| Insufficient payload (model declined to judge) | 0.011 | 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".