Active Surveillance in Young Patients With Prostate Cancer: The Unanswered Question
Bibliographic record
Abstract
In their long-term follow-up study on a cohort of 450 patients with low-risk prostate cancer managed with active surveillance, Klotz et al 1 reclassified 30% of patients as higher risk, thus requiring definitive therapy (radical prostatectomy or radiotherapy). The critical decision to offer deferred treatment is based on prostate-specific antigen kinetics and histology at rebiopsy. Notwithstanding no difference noted in overall survival between patients who remained on surveillance and those who underwent radical treatment, at a median follow-up of 6.8 years, some doubts remain for long-term outcomes in men reclassified as progressed who were referred to delayed treatment as noted by the authors. An uncertainty immediately arises, considering the median patient age was 70.3 years, and ongoing studies on prostate cancer, such as the European Prostate Cancer Research International: Active Surveillance (PRIAS) project, 2 offer active surveillance that include all patients. The Canadian study reported that patients received an initial biopsy according to the Vienna nomogram scheme of eight to 14 core biopsies, depending on patient age and gland volume. However, the study began in November 1995 and the Vienna nomogram 3 was published in 2005. Before 1998, no studies reported an extended prostate biopsy scheme, which is at least eight cores (sextant plus two lateral biopsies). 4 Thus, it is likely that the cohort was not homogeneous in its accuracy of cancer risk definition among patients recruited at the beginning of the study and afterward. We think a more accurate initial biopsy schedule (the Vienna nomogram should be optimal) may enhance detection accuracy of patients at higher cancer risk in terms of the number of positive cores and reliability of the Gleason score, and, most importantly, identify the true low-risk patients suitable for surveillance.
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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 | 0.019 | 0.057 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.008 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.008 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".