Defining subgroups of patients with intermediate risk prostate cancer for whom active surveillance is safe.
Bibliographic record
Abstract
393 Background: A number of guideline groups recommend active surveillance (AS) for patients with low risk prostate cancer as well as selected patients with intermediate-risk prostate cancer (IRPC) – these groups are not well defined. Our group has previously shown that some patients with IRPC have high rates of progression to advanced disease. The goal of this study was to determine a subset of patients with IRPC where AS is safe. Methods: This single-institution, phase II study enrolled men with low-risk and selected IRPC patients since 1995. Patients were followed with PSA every 3-6 months, DRE every 6 months with repeat systematic biopsies at 1 year and every 3 years. Since 2013, MRI staging was done every 2 years with targeted and systematic biopsies done for new or growing lesions. Patients were followed until death or withdrawn consent. Time to treatment, metastasis-free survival (MFS), cause-specific survival (CSS) and overall survival were calculated from date of registration biopsy. Results: 1409 men were analyzed with a median follow-up of 11.0 years (range 1.2 – 26.4 years). Median age and PSA at registration biopsy were 67 years and 5.03 ng/ml. 86.4%, 11.8% and 1.7% had GG1, GG2 and GG3 disease. 72.9%, 5.8%, 7.3% and 13.6% had low, GG1 favourable IRPC (FIR), GG2 FIR and unfavourable risk ds (UIR). 996 men had at least one repeat biopsy, 768 reclassified, 604 underwent treatment, 166 had biochemical failure, 64 developed metastases and 41 died of prostate cancer. 10 year MFS was 97.4%. Absolute percentage pattern 4/5 (APP4) at baseline had a sensitivity of 36%, specificity of 86% and AUC of 64% with an optimal cutpoint of >0.30 for predicting MFS. Multivariable analysis (MVA) revealed APP4 (HR 2.86) at baseline and at repeat biopsy (vs baseline) of high risk vs UIR (HR 5.61) and high risk vs GG2 FIR (HR 10.4) were independent predictors of MFS. 10 year CSS was 98.5%. MVA revealed APP4 (>0.7, AUC 67%; HR 3.13) and high risk vs UIR (HR 34.4) were independent predictors of CSS. Conclusions: Patients with GG1 prostate cancer and those with GG2 FIR and APP4 < 0.30 appear to have very low risk of metastases and prostate cancer death and are suitable for active surveillance.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".