PD40-04 A GENOMIC CLASSIFIER SHOWS IMPROVED PREDICTION OF ONCOLOGIC OUTCOMES IN AFRICAN-AMERICAN MEN TREATED WITH RADICAL PROSTATECTOMY
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Résumé
You have accessJournal of UrologyProstate Cancer: Localized: Surgical Therapy I (PD40)1 Apr 2019PD40-04 A GENOMIC CLASSIFIER SHOWS IMPROVED PREDICTION OF ONCOLOGIC OUTCOMES IN AFRICAN-AMERICAN MEN TREATED WITH RADICAL PROSTATECTOMY Stephen Freedland*, Marguerite du Plessis, Jingbin Zhang, Lauren Howard, Amanda De Hoedt, and Elai Davicioni Stephen Freedland*Stephen Freedland* More articles by this author , Marguerite du PlessisMarguerite du Plessis More articles by this author , Jingbin ZhangJingbin Zhang More articles by this author , Lauren HowardLauren Howard More articles by this author , Amanda De HoedtAmanda De Hoedt More articles by this author , and Elai DavicioniElai Davicioni More articles by this author View All Author Informationhttps://doi.org/10.1097/01.JU.0000556415.00894.25AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVES: Accurate risk stratification after radical prostatectomy (RP) is important to help select men at risk of recurrence who will benefit most postoperative radiation or multi-modal therapy. Increasingly genomic testing is being used in the clinic for this purpose. However, little is known about how these tests predict outcomes in African-American men (AAM), an underserved at risk population. Here we evaluate Decipher within a large Veteran Affairs cohort and compare its performance to the CAPRA-S clinical model for predicting outcomes in AAM and non-AAM RP patients. METHODS: Decipher genomic classifier (GC) scores were generated for 557 PCa patients, who underwent RP at the Veteran Affairs Medical Center Durham between 1989 and 2016. This was a clinically high-risk cohort which all underwent RP and were selected to have either T3a, positive margins, seminal vesicle invasion, or received post-op radiation. Cox univariable and multivariable proportional hazards models and survival c-index were used to compare the performance of Decipher and CAPRA-S for predicting risk of metastasis and PCa specific mortality (PCSM). RESULTS: Overall, 55% (n=306) of patients in the cohort were AAM. CAPRA-S classified 10.4% as low risk for recurrence while for GC it was 50.4%. With a median follow-up of 9 years, only 40 patients developed metastases and 18 patients died of PCa. In multivariable analyses, both GC (p=0.044 HR:1.30 95% CI:1.01-1.69) and CAPRA-S (p=0.037 HR:1.27 95% CI:1.01-1.58) were significant predictors for metastasis within non-AAM; however, only GC (p<0.001 HR:1.70 95% CI:1.31-2.20), was significant within AAM. GC but not CAPRA-S was a significant predictor of PCSM for both EAM (p=0.044 HR:1.54 95% CI:1.01-2.53) and AAM (p=0.002 HR:1.65 95% CI:1.19-2.42). The survival c-index of GC for predicting metastasis 8 years post RP was 0.84 (95% CI: 0.76-0.90) in AAM and 0.70 (95% CI:0.63-0.80) in non-AAM. For PCSM endpoint, it was 0.82 (0.61-0.93) in AAM and 0.73 (95% CI:0.63-0.84) in non-AAM. CONCLUSIONS: Our results among non-AAM confirm many prior studies showing that GC is a powerful predictor of metastasis and PCSM. Among AAM, not only was GC a very strong predictor of poor outcome, there was actually a suggestion that GC may perform better among AAM than EAM, though this requires further validation. Source of Funding: GenomeDx Biosciences Los Angeles, CA; Vancouver, Canada; Durham, NC; Durham, NC; San Diego, CA© 2019 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 201Issue Supplement 4April 2019Page: e739-e739 Advertisement Copyright & Permissions© 2019 by American Urological Association Education and Research, Inc.MetricsAuthor Information Stephen Freedland* More articles by this author Marguerite du Plessis More articles by this author Jingbin Zhang More articles by this author Lauren Howard More articles by this author Amanda De Hoedt More articles by this author Elai Davicioni 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 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,006 | 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 ».