PD52-10 CLINICAL SIGNIFICANCE OF THE LACDINAC-GLYCOSYLATED PROSTATE-SPECIFIC ANTIGEN ASSAY FOR PROSTATE CANCER DETECTION
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Résumé
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 ...
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 0,002 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».