1743 RELATIONSHIP BETWEEN INITIAL PSA DENSITY WITH FUTURE PSA KINETICS AND REPEAT BIOPSIES IN MEN WITH PROSTATE CANCER ON ACTIVE SURVEILLANCE
Bibliographic record
Abstract
You have accessJournal of UrologyProstate Cancer: Localized VII1 Apr 20101743 RELATIONSHIP BETWEEN INITIAL PSA DENSITY WITH FUTURE PSA KINETICS AND REPEAT BIOPSIES IN MEN WITH PROSTATE CANCER ON ACTIVE SURVEILLANCE Ahmed Kotb, Simon Tanguay, Murilo Luz, Wassim Kassouf, and Armen Aprikian Ahmed KotbAhmed Kotb More articles by this author , Simon TanguaySimon Tanguay More articles by this author , Murilo LuzMurilo Luz More articles by this author , Wassim KassoufWassim Kassouf More articles by this author , and Armen AprikianArmen Aprikian More articles by this author View All Author Informationhttps://doi.org/10.1016/j.juro.2010.02.1592AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookTwitterLinked InEmail INTRODUCTION AND OBJECTIVES Prostate cancer is a common health problem affecting older men; active surveillance with deferred treatment is an established management option for localized prostate cancer. PSA velocity (PSAV) is a measure of PSA kinetics with an established correlation with disease progression and disease specific mortality, in men receiving treatment for prostate cancer. PSA density (PSAd) has been used as a measure of disease volume as it takes into account, total prostate volume. The objective of our study is to examine the correlation between PSA density (PSAd) at time of diagnosis and serum testosterone, with PSAV, PSA doubling time (PSADT) and tumour progression, on repeat biopsy, in men with prostate cancer on active surveillance. METHODS Data from 102 patients with clinically localized prostate cancer on active surveillance, in the period between 1992 and 2007, who had the necessary parameters available, were collected. PSAd was calculated and correlated with serum testosterone, PSAV, PSADT, Gleason score at diagnosis, and local progression on repeated biopsies. RESULTS PSAV was 0.64 and 1.31 ng/ml/year (P= 0.02), PSADT of 192 and 113 months (P= 0.4) and serum free testosterone 34.2 and 19.5 pg/ml (P= 0.0005) for PSAd below and above 0.15 respectively. The rate of detecting high Gleason score (>=7) at diagnosis was 6% and 23% for PSAD below and above 0.15 respectively. 101 patients underwent at least a second biopsy and the incidence of upgrading was 10% and 31% for PSAD below and above 0.15 respectively (P= 0.001). CONCLUSIONS Although low PSAd is an accepted measure for suggesting insignificant prostate cancer, our study expands its role to suggest that PSAd <0.15 may be an additional clinical parameter that may suggest indolent disease, as measured by PSAV and repeat biopsy over time. Montreal, Canada© 2010 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 183Issue 4SApril 2010Page: e673-e674 Advertisement Copyright & Permissions© 2010 by American Urological Association Education and Research, Inc.Metrics Author Information Ahmed Kotb More articles by this author Simon Tanguay More articles by this author Murilo Luz More articles by this author Wassim Kassouf More articles by this author Armen Aprikian More articles by this author Expand All Advertisement Advertisement PDF downloadLoading ...
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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 | 0.000 | 0.004 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".