PD55-06 COMPARISON OF MRI/FUSION VERSUS TRUS CONFIRMATORY BIOPSY IN ACTIVE SURVEILLANCE PATIENTS
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Résumé
You have accessJournal of UrologyProstate Cancer: Localized: Active Surveillance III (PD55)1 Apr 2019PD55-06 COMPARISON OF MRI/FUSION VERSUS TRUS CONFIRMATORY BIOPSY IN ACTIVE SURVEILLANCE PATIENTS David Feng, Jeremiah R Dallmer, Svetlana Avulova*, Amy N Luckenbaugh, Aaron A Laviana, Sam S Chang, David F Penson, Matthew J Resnick, Kristen R Scarpato, and Daniel A Barocas David FengDavid Feng More articles by this author , Jeremiah R DallmerJeremiah R Dallmer More articles by this author , Svetlana Avulova*Svetlana Avulova* More articles by this author , Amy N LuckenbaughAmy N Luckenbaugh More articles by this author , Aaron A LavianaAaron A Laviana More articles by this author , Sam S ChangSam S Chang More articles by this author , David F PensonDavid F Penson More articles by this author , Matthew J ResnickMatthew J Resnick More articles by this author , Kristen R ScarpatoKristen R Scarpato More articles by this author , and Daniel A BarocasDaniel A Barocas More articles by this author View All Author Informationhttps://doi.org/10.1097/01.JU.0000557073.87014.7fAboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVES: Selection of appropriate patients for active surveillance (AS) is a key safety issue for conservative management of low-risk localized prostate cancer. Confirmatory biopsy is often performed within a year of diagnosis in order to identify occult high-grade or high-volume cancer, and magnetic resonance imaging (MRI) has been increasingly used to guide confirmatory biopsies. Its overall utility versus conventional transrectal ultrasound (TRUS) biopsy, however, remains unknown. Therefore, we sought to determine the degree to which each technique identified pathologic features that rendered patients ineligible for AS on confirmatory biopsy. METHODS: Cohort consisted of 645 men who chose AS and underwent confirmatory biopsy between 2010 and 2018 with either a repeat TRUS biopsy (575 men) or MRI fusion biopsy (70 men) (which included 12 standard cores in addition to targeted cores). Our primary outcome of interest was AS ineligibility on confirmatory biopsy as defined using the previously published eligibility definitions from 4 major AS cohorts (John Hopkins University [JHU], University of Toronto, Canary Prostate Active Surveillance Study [PASS], and University of California San Francisco [UCSF]). RESULTS: Patients who underwent MRI had a higher average number of cores taken (16.62 versus 14.48, p=0.0001) and larger maximum percent core involvement (22.19% versus 15.34%, p=0.015). In the TRUS protocol, 8-17% of men were no longer eligible for AS after a confirmatory biopsy, whereas, in the MRI protocol, 10-32% were ineligible (Table). JHU AS criteria are the most strict, and in our cohort resulted in the highest rate of ineligibility for AS. Amongst the 4 AS cohorts, MRI confirmatory biopsy was significantly more likely to rule a patient ineligible for AS according to the JHU eligibility criteria (32% versus 17%, respectively, p=0.040), with no significant difference in the other cohorts. CONCLUSIONS: When adhering to strict inclusion criteria for AS, use of MRI-TRUS fusion for confirmatory biopsy results in an increased rate of ineligibility. When applying more inclusive criteria, MRI use increases the number of cores taken and maximum percent tumor involvement per core, without altering eligibility. Thus, MRI-TRUS fusion biopsy may have utility if the intent is to remain on AS only if still meeting JHU criteria after confirmatory biopsy. Source of Funding: None Nashville , TN; Nashville, TN© 2019 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 201Issue Supplement 4April 2019Page: e1013-e1014 Advertisement Copyright & Permissions© 2019 by American Urological Association Education and Research, Inc.MetricsAuthor Information David Feng More articles by this author Jeremiah R Dallmer More articles by this author Svetlana Avulova* More articles by this author Amy N Luckenbaugh More articles by this author Aaron A Laviana More articles by this author Sam S Chang More articles by this author David F Penson More articles by this author Matthew J Resnick More articles by this author Kristen R Scarpato More articles by this author Daniel A Barocas 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 | 0,002 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,002 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,011 | 0,001 |
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 ».