MP28-03 DO ELDERLY MEN (>75) HARBOR MORE AGGRESSIVE PROSTATE CANCER? COMPARISON OF DECIPHER AND PAM50 TESTS AMONG DIFFERENT AGE GROUPS
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Résumé
You have accessJournal of UrologyProstate Cancer: Markers II (MP28)1 Apr 2019MP28-03 DO ELDERLY MEN (>75) HARBOR MORE AGGRESSIVE PROSTATE CANCER? COMPARISON OF DECIPHER AND PAM50 TESTS AMONG DIFFERENT AGE GROUPS Hanan Goldberg*, Jaime Omar Herrera Cáceres, Maria Santiago-Jimenez, Nick Fishbaen, Elai Davicioni, Zachary Klaassen, Thenappan Chandrasekar, Christopher Wallis, Dixon Woon, Robert Hamilton, Girish Kulkarni, Alejandro Berlin, and Neil Fleshner Hanan Goldberg*Hanan Goldberg* More articles by this author , Jaime Omar Herrera CáceresJaime Omar Herrera Cáceres More articles by this author , Maria Santiago-JimenezMaria Santiago-Jimenez More articles by this author , Nick FishbaenNick Fishbaen More articles by this author , Elai DavicioniElai Davicioni More articles by this author , Zachary KlaassenZachary Klaassen More articles by this author , Thenappan ChandrasekarThenappan Chandrasekar More articles by this author , Christopher WallisChristopher Wallis More articles by this author , Dixon WoonDixon Woon More articles by this author , Robert HamiltonRobert Hamilton More articles by this author , Girish KulkarniGirish Kulkarni More articles by this author , Alejandro BerlinAlejandro Berlin More articles by this author , and Neil FleshnerNeil Fleshner More articles by this author View All Author Informationhttps://doi.org/10.1097/01.JU.0000555708.92392.e3AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVES: Age is an important prognostic factor in oncology. Over 20% of men diagnosed with prostate cancer (PC) are > = 75 years old. In the growing elderly population, objective methods for predicting outcomes beyond chronologic age are necessary in order minimize the likelihood of withholding curative treatment when warranted. Herein, we describe and analyze age-related differences in clinico-genomic prognostic indices of aggressiveness in localized PC. METHODS: Clinical and genomic data for 8355 patients from the Decipher Genomic Resource Information Database (GRID; NCT02609269) was obtained. Conventional and genomic prognostic indices including Decipher GC scores, PAM50 molecular subtypes (e.g. luminal A/B or basal) NCCN risk groups and Gleason groups (GG) were stratified by age using multivariable logistic regression analyses (MLRA). RESULTS: With increasing decile of age, we observed a higher proportion of high GG and higher Decipher scores. There was a statistically significant increase in the proportion of patients with high Decipher scores with increasing age among GG1 and GG2 ( < 55 - 10.2%, 30.7%, 55-60 – 15.4%, 25.6%, 60-65 – 15.9%, 29.7%, 65-70 – 16.9%, 28.2%, 70-75 – 17.9%, 30%, and > 75 – 20.3%, 37.3%, respectively). Furthermore, the prevalence of the PAM50 luminal B subtype (associated with worse prognosis) increased with age among GG1 and GG2 ( < 60 – 22.2%, 40%, 60-65 – 29.1%, 41.7%, 65-70 – 28.2%, 39.2%, 70-75 – 30%, 43.4%, 75-80 – 33.5%, 44.3%, > 80 – 34.2%, 52%, respectively). Among higher grade tumors (GG 3-5), no statistically significant differences between the different age groups were observed. MLRA demonstrated that in addition to higher T stage, PSA and GG, each age decile entailed a 20% increased risk for a high Decipher score (OR 1.2, 95% C.I 1.11-1.3, p < 0.001). CONCLUSIONS: Older men with lower grade tumors, as opposed to higher grade tumors, harbored worse disease based on genomic risk models. The accepted paradigm of elderly PC patients being treated conservatively based solely on chronologic age, needs to be changed. We provide evidence suggesting the utility of clinical-genomic characterization for better treatment individualization decisions. Source of Funding: Decipher GenomeDX Toronto, Canada; Vancouver, Canada; Toronto, Canada© 2019 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 201Issue Supplement 4April 2019Page: e403-e404 Advertisement Copyright & Permissions© 2019 by American Urological Association Education and Research, Inc.MetricsAuthor Information Hanan Goldberg* More articles by this author Jaime Omar Herrera Cáceres More articles by this author Maria Santiago-Jimenez More articles by this author Nick Fishbaen More articles by this author Elai Davicioni More articles by this author Zachary Klaassen More articles by this author Thenappan Chandrasekar More articles by this author Christopher Wallis More articles by this author Dixon Woon More articles by this author Robert Hamilton More articles by this author Girish Kulkarni More articles by this author Alejandro Berlin More articles by this author Neil Fleshner 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) | 0,001 | 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) | 0,012 | 0,003 |
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 ».