Active Surveillance for Prostate Cancer: For Whom?
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Prostate-specific antigen (PSA) -based prostate cancer screening results in the diagnosis of prostate cancer in many men who are not destined to have clinical progression during their lifetime. Good-risk prostate cancer, defined as a Gleason score of 6 or less, PSA < 10, and T1c to T2a, now constitutes 50% of newly diagnosed prostate cancer. In most of these patients, the disease is indolent and slow growing. The challenge is to identify those patients who are unlikely to experience significant progression while offering radical therapy to those who are at risk. The approach to favorable-risk prostate cancer described in this article uses estimation of PSA doubling time (PSA DT) to stratify patients according to the risk of progression. Patients who select this approach are managed initially with active surveillance. Those who have a PSA DT of 3 years or less (based on a minimum of three determinations over 6 months) are offered radical intervention. The remainder are closely monitored with serial PSA and periodic prostate rebiopsies (at 2, 5, and 10 years). In this series of 299 patients, the median DT was 7 years. Forty-two percent had a PSA DT > 10 years, and 20% had a PSA DT > 100 years. The majority of patients on this study remain under surveillance. The approach of active surveillance with selective delayed intervention based on PSA DT represents a practical compromise between radical therapy for all (which results in overtreatment for patients with indolent disease) and watchful waiting with palliative therapy only (which results in undertreatment for those with aggressive disease).
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.008 | 0.003 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it