MP38-05 DEFINING A COHORT OF MEN WHO MAY NOT REQUIRE REPEAT PROSTATE BIOPSY BASED ON PCA3 AND MRI: THE DOUBLE NEGATIVE EFFECT.
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Résumé
You have accessJournal of UrologyProstate Cancer: Detection & Screening IV1 Apr 2017MP38-05 DEFINING A COHORT OF MEN WHO MAY NOT REQUIRE REPEAT PROSTATE BIOPSY BASED ON PCA3 AND MRI: THE DOUBLE NEGATIVE EFFECT. Nathan Perlis, Thamir Al-Kasab, Ardalan Ahmad, Estee Goldberg, Kamel Fadaak, Rashid Sayyid, Antonio Finelli, Girish Kulkarni, Alexandre Zlotta, Rob Hamilton, and Neil Fleshner Nathan PerlisNathan Perlis More articles by this author , Thamir Al-KasabThamir Al-Kasab More articles by this author , Ardalan AhmadArdalan Ahmad More articles by this author , Estee GoldbergEstee Goldberg More articles by this author , Kamel FadaakKamel Fadaak More articles by this author , Rashid SayyidRashid Sayyid More articles by this author , Antonio FinelliAntonio Finelli More articles by this author , Girish KulkarniGirish Kulkarni More articles by this author , Alexandre ZlottaAlexandre Zlotta More articles by this author , Rob HamiltonRob Hamilton More articles by this author , and Neil FleshnerNeil Fleshner More articles by this author View All Author Informationhttps://doi.org/10.1016/j.juro.2017.02.1158AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookTwitterLinked InEmail INTRODUCTION AND OBJECTIVES Prostate Cancer (PC) overdiagnosis and overtreatment is a major concern for clinicians and policy makers. Multiparametric MRI (mpMRI) and the PCA3 urine test aim to limit this by identifying fewer cases of indolent cancer and more clinically significant cases. We explore whether the utility of the tests can be maximized by combining them for a group of patients with previous prostate biopsies. METHODS We collected clinicopathologic data from all patients that underwent a urine PCA3 test from 2011 to June 2016 at the University Health Network at The University of Toronto in accordance with ethics committee approval. This included patients on active surveillance (AS) for low-risk PC and those without PC with previous negative biopsies and suspicion of occult, significant disease primarily based on rising PSA. We explored whether age, PSA, PCA3, mpMRI, DRE, family history and prostate size predicted for clinically significant prostate cancer on repeat biopsy as defined by Epstein criteria. We then stratified patients by mpMRI and PCA3 result to detect whether any particular combination of these test has exemplary negative predictive value (NPV) and considered the optimal sequence of tests. RESULTS 470 patients met inclusion criteria with median (IQR) age and PSA of 62.5 ng/mL (58-68) and 6.3 (4.6-8.8), respectively. PCA3 was abnormal (≥35) in 32.5% of cases. 18.8% of men had a positive family history and 5.6% had suspicious DRE. Epstein criteria or worse PC was identified in 26.3% of cases. In the multivariate model, only age (OR 1.08, 95%CI 1.01-1.16), mpMRI score 4 (OR 16.6, 95%CI 3.9-70.0) or 5 (OR 28.3, 95%CI 5.7-138), and PCA3 (OR 2.9, 95%CI 1.0-8.8) predicted for clinically significant PC on biopsy. No patients with a negative mpMRI and normal PCA3 test were found to have clinically significant PC on biopsy (0 of 26, 100% NPV for double negative test, p<0.0001). Using mpMRI as the initial test diminishes the number of overall tests (11 fewer tests per 100 patients), adds spatial information for targeted biopsy when available, but is more expensive than starting with PCA3 test for all patients. CONCLUSIONS Both PCA3 and mpMRI are useful tests for predicting clinically significant PC on repeat prostate biopsy. In the 1 of 6 patients in our cohort with double negative tests no clinically significant PC was found on biopsy, which raises the question whether biopsy can be avoided in this group altogether. This study is limited by its retrospective design and selection bias. A prospective trial at our centre is currently ongoing examining this question for patients on AS. © 2017FiguresReferencesRelatedDetails Volume 197Issue 4SApril 2017Page: e485-e486 Advertisement Copyright & Permissions© 2017MetricsAuthor Information Nathan Perlis More articles by this author Thamir Al-Kasab More articles by this author Ardalan Ahmad More articles by this author Estee Goldberg More articles by this author Kamel Fadaak More articles by this author Rashid Sayyid More articles by this author Antonio Finelli More articles by this author Girish Kulkarni More articles by this author Alexandre Zlotta More articles by this author Rob Hamilton More articles by this author Neil Fleshner More articles by this author Expand All Advertisement 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 | 0,011 | 0,049 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,002 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,002 | 0,003 |
| Intégrité de la recherche | 0,001 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,010 | 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 ».