PD52-10 CLINICAL SIGNIFICANCE OF THE LACDINAC-GLYCOSYLATED PROSTATE-SPECIFIC ANTIGEN ASSAY FOR PROSTATE CANCER DETECTION
Bibliographic record
Abstract
You have accessJournal of UrologyProstate Cancer: Markers II (PD52)1 Apr 2020PD52-10 CLINICAL SIGNIFICANCE OF THE LACDINAC-GLYCOSYLATED PROSTATE-SPECIFIC ANTIGEN ASSAY FOR PROSTATE CANCER DETECTION Tohru Yoneyama*, Yuki Tobisawa, Tomonori Kaneko, Takatoshi Kaya, Shingo Hatakeyama, Kazuyuki Mori, Mihoko Sutoh Yoneyama, Teppei Okubo, Koji Mitsuzuka, Wilhelmina Duivenvoorden, Jehonathan H. Pinthus, Yasuhiro Hashimoto, Akihiro Ito, Takuya Koie, Robert A. Gardiner, and Chikara Ohyama Tohru Yoneyama*Tohru Yoneyama* More articles by this author , Yuki TobisawaYuki Tobisawa More articles by this author , Tomonori KanekoTomonori Kaneko More articles by this author , Takatoshi KayaTakatoshi Kaya More articles by this author , Shingo HatakeyamaShingo Hatakeyama More articles by this author , Kazuyuki MoriKazuyuki Mori More articles by this author , Mihoko Sutoh YoneyamaMihoko Sutoh Yoneyama More articles by this author , Teppei OkuboTeppei Okubo More articles by this author , Koji MitsuzukaKoji Mitsuzuka More articles by this author , Wilhelmina DuivenvoordenWilhelmina Duivenvoorden More articles by this author , Jehonathan H. PinthusJehonathan H. Pinthus More articles by this author , Yasuhiro HashimotoYasuhiro Hashimoto More articles by this author , Akihiro ItoAkihiro Ito More articles by this author , Takuya KoieTakuya Koie More articles by this author , Robert A. GardinerRobert A. Gardiner More articles by this author , and Chikara OhyamaChikara Ohyama More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000000954.010AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: To reduce unnecessary prostate biopsies (Pbx), better discrimination is needed. To identify significant prostate cancer (sigPC) we determined the performance of LacdiNAc-glycosylated prostate-specific antigen (LDN-PSA) and LDN-PSA normalized by prostate volume (LDN-PSAD). METHODS: We retrospectively measured LDN-PSA, total PSA (tPSA), and free PSA/tPSA (F/T PSA) values in 718 men who underwent a Pbx in three academic urology clinics in Japan and Canada (Pbx cohort) and in 174 PC patients who subsequently underwent radical prostatectomy in Australia (preop-PSA cohort). The assays were evaluated using the area under receiver operating characteristics curve (AUC) and decision curve analyses (DCA) to discriminate sigPC. RESULTS: In the Pbx cohort, LDN-PSAD (AUC 0.825) provided significantly better clinical performance for discriminating overall PC compared with LDN-PSA (AUC 0.801, p <0.0001), PSAD (AUC 0.745, p <0.0001), tPSA (AUC 0.654, p <0.0001) and F/T PSA (AUC 0.668, p <0.0001). DCA analysis showed that using a risk threshold of 30%, adding LDN-PSA and LDN-PSAD to the base model (age, DRE status, tPSA, and F/T PSA) permitted avoidance of even more biopsies without missing PC (5.6% and 9.3% resp. vs. 1.8% (base model)). LDN-PSAD (AUC 0.860) provided significantly better clinical performance for discriminating sigPC compared with LDN-PSA (AUC 0.827, p=0.0024), PSAD (AUC 0.809, p <0.0001), tPSA (AUC 0.712, p <0.0001) and F/T PSA (AUC 0.661, p <0.0001). DCA analysis showed that using a risk threshold of 25%, adding LDN-PSA and LDN-PSAD to the base model permitted avoidance of even more biopsies without missing sigPC (9.9% and 18.1% resp. vs. 2.2% (base model)). In the preop-PSA cohort, LDN-PSA values positively correlated with tumor volume and tPSA, and were significantly higher in pT3, pathological GS ≥7. CONCLUSIONS: The diagnostic performance of LDN-PSA is significantly better than the PSA, FT/ PSA & PSAD test in identifying patients with overall PC and sigPC. Addition of LDN-PSA test to conventional diagnostic model significantly improve avoidable biopsy effect in identifying patients with PC. Source of Funding: none © 2020 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 203Issue Supplement 4April 2020Page: e1093-e1094 Advertisement Copyright & Permissions© 2020 by American Urological Association Education and Research, Inc.MetricsAuthor Information Tohru Yoneyama* More articles by this author Yuki Tobisawa More articles by this author Tomonori Kaneko More articles by this author Takatoshi Kaya More articles by this author Shingo Hatakeyama More articles by this author Kazuyuki Mori More articles by this author Mihoko Sutoh Yoneyama More articles by this author Teppei Okubo More articles by this author Koji Mitsuzuka More articles by this author Wilhelmina Duivenvoorden More articles by this author Jehonathan H. Pinthus More articles by this author Yasuhiro Hashimoto More articles by this author Akihiro Ito More articles by this author Takuya Koie More articles by this author Robert A. Gardiner More articles by this author Chikara Ohyama More articles by this author Expand All 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 | 0.001 | 0.003 |
| 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 | 0.002 |
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".