Clinical-genomic Characterization Unveils More Aggressive Disease Features in Elderly Prostate Cancer Patients with Low-grade Disease.

Aged Cross-Sectional Studies Humans Immunoglobulin G Male Prostatectomy / adverse effects Prostatic Neoplasms / pathology Retrospective Studies
Age Decipher Genomic classifier Gleason group grade Prostate cancer

Journal

European urology focus
ISSN: 2405-4569
Titre abrégé: Eur Urol Focus
Pays: Netherlands
ID NLM: 101665661

Informations de publication

Date de publication:
Jul 2021
Historique:
received: 15 12 2019
revised: 19 01 2020
accepted: 19 02 2020
pubmed: 12 3 2020
medline: 14 4 2022
entrez: 12 3 2020
Statut: ppublish

Résumé

Over 20% of men diagnosed with prostate cancer (PC) are ≥75 yr old. More objective disease-specific indices for predicting outcomes beyond chronological age are necessary. To analyze age-related differences in clinical-genomic prognostic features of aggressiveness in localized PC. A retrospective multicenter cross-sectional study reported the use of the Reporting Recommendations for Tumor Marker Prognostic Studies (REMARK) guidelines. Clinical-genomic data of patients who underwent a prostate biopsy or radical prostatectomy (RP) were obtained from the Decipher Genomic Resource Information Database (NCT02609269). Our analyses focused on the 22-gene Decipher genomic classifier (GC) and 50-gene (PAM50) models in the biopsy and RP cohorts stratified by age. The primary endpoint was the impact of age on GC scores and PAM50 molecular subtypes. Prognostic indices including Decipher GC scores, PAM50 molecular subtypes, National Comprehensive Cancer Network risk categories, and ISUP grade groups (IGGs) were stratified by age using multivariable logistic regression analyses. Within histological low-risk IGGs, there were a higher proportion of patients with high-risk Decipher biopsy scores with age (age <60 yr: 10.1% IGG 1 and 29.9% IGG 2 vs age ≥80 yr: 22% IGG 1 and 37.7% IGG 2). The prevalence of the adverse phenotype luminal B (PAM50-defined) increased with age (age <60 yr: 22.7% and 40.2% vs age ≥80 yr: 29.7% and 49.1%, in patients with IGG 1 and IGG 2, respectively). In IGGs 3-5, no age differences were observed. Multivariable models demonstrated that each age decile entailed a 19% (odds ratio [OR] 1.19, 95% confidence interval [CI] 1.10-1.29, p < 0.001) and a 10% (OR 1.1, 95% CI 1.05-1.16) increased probability for a high-risk Decipher biopsy and RP score, respectively. Aside from an obvious selection bias, data on race, family history, prostate volume, and long-term follow-up outcomes were unavailable. These data demonstrated that elderly men with favorable pathology (IGG 1-2), might harbor more aggressive disease than younger patients based on validated GC scores. The presented clinical-genomic data demonstrate that elderly patients with low-risk prostate cancer might harbor more aggressive disease than their younger counterparts. This suggests that standard well-accepted paradigm of elderly prostate cancer patients not being aggressively treated, based solely on their chronological age, might need to be reconsidered.

Sections du résumé

BACKGROUND BACKGROUND
Over 20% of men diagnosed with prostate cancer (PC) are ≥75 yr old. More objective disease-specific indices for predicting outcomes beyond chronological age are necessary.
OBJECTIVE OBJECTIVE
To analyze age-related differences in clinical-genomic prognostic features of aggressiveness in localized PC.
DESIGN, SETTING, AND PARTICIPANTS METHODS
A retrospective multicenter cross-sectional study reported the use of the Reporting Recommendations for Tumor Marker Prognostic Studies (REMARK) guidelines. Clinical-genomic data of patients who underwent a prostate biopsy or radical prostatectomy (RP) were obtained from the Decipher Genomic Resource Information Database (NCT02609269).
INTERVENTION METHODS
Our analyses focused on the 22-gene Decipher genomic classifier (GC) and 50-gene (PAM50) models in the biopsy and RP cohorts stratified by age.
OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS METHODS
The primary endpoint was the impact of age on GC scores and PAM50 molecular subtypes. Prognostic indices including Decipher GC scores, PAM50 molecular subtypes, National Comprehensive Cancer Network risk categories, and ISUP grade groups (IGGs) were stratified by age using multivariable logistic regression analyses.
RESULTS AND LIMITATIONS CONCLUSIONS
Within histological low-risk IGGs, there were a higher proportion of patients with high-risk Decipher biopsy scores with age (age <60 yr: 10.1% IGG 1 and 29.9% IGG 2 vs age ≥80 yr: 22% IGG 1 and 37.7% IGG 2). The prevalence of the adverse phenotype luminal B (PAM50-defined) increased with age (age <60 yr: 22.7% and 40.2% vs age ≥80 yr: 29.7% and 49.1%, in patients with IGG 1 and IGG 2, respectively). In IGGs 3-5, no age differences were observed. Multivariable models demonstrated that each age decile entailed a 19% (odds ratio [OR] 1.19, 95% confidence interval [CI] 1.10-1.29, p < 0.001) and a 10% (OR 1.1, 95% CI 1.05-1.16) increased probability for a high-risk Decipher biopsy and RP score, respectively. Aside from an obvious selection bias, data on race, family history, prostate volume, and long-term follow-up outcomes were unavailable.
CONCLUSIONS CONCLUSIONS
These data demonstrated that elderly men with favorable pathology (IGG 1-2), might harbor more aggressive disease than younger patients based on validated GC scores.
PATIENT SUMMARY RESULTS
The presented clinical-genomic data demonstrate that elderly patients with low-risk prostate cancer might harbor more aggressive disease than their younger counterparts. This suggests that standard well-accepted paradigm of elderly prostate cancer patients not being aggressively treated, based solely on their chronological age, might need to be reconsidered.

Identifiants

DOI: 10.1016/j.euf.2020.02.008 PMID: 32156491
pubmed: 32156491
pii: S2405-4569(20)30065-1
doi: 10.1016/j.euf.2020.02.008
pii:
doi:

Substances chimiques

Immunoglobulin G 0

Banques de données

ClinicalTrials.gov
['NCT02609269']

Types de publication

Journal Article Multicenter Study

Langues

eng

Sous-ensembles de citation

IM

Pagination

797-806

Commentaires et corrections

Type : CommentIn

Informations de copyright

Copyright © 2020 European Association of Urology. Published by Elsevier B.V. All rights reserved.

Auteurs

Hanan Goldberg (H)

Division of Urology, Department of Surgical Oncology, Princess Margaret Cancer Centre, University Health Network and the University of Toronto, Toronto, ON, Canada; Department of Urology, SUNY Upstate Medical University, Syracuse, NY, USA. Electronic address: gohanan@gmail.com.

Daniel Spratt (D)

Department of Radiation Oncology, University of Michigan, Ann Arbor, MI, USA.

Thenappan Chandrasekar (T)

Department of Urology, Sidney Kimmel Cancer Center, Thomas Jefferson University, Philadelphia, PA, USA.

Zachary Klaassen (Z)

Division of Urology, Department of Surgery, Medical College of Georgia, Augusta University, Augusta, GA, USA; Georgia Cancer Center, Augusta, GA, USA.

Christopher J D Wallis (CJD)

Division of Urology, Department of Surgical Oncology, Princess Margaret Cancer Centre, University Health Network and the University of Toronto, Toronto, ON, Canada.

Maria Santiago-Jimenez (M)

Decipher Biosciences, Vancouver, BC, Canada.

Nick Fishbane (N)

Decipher Biosciences, Vancouver, BC, Canada.

Elai Davicioni (E)

Decipher Biosciences, Vancouver, BC, Canada.

Rodrigo Noorani (R)

Division of Urology, Department of Surgical Oncology, Princess Margaret Cancer Centre, University Health Network and the University of Toronto, Toronto, ON, Canada.

Ardalan E Ahmad (AE)

Division of Urology, Department of Surgical Oncology, Princess Margaret Cancer Centre, University Health Network and the University of Toronto, Toronto, ON, Canada.

Jaime Omar Herrera Cáceres (JO)

Division of Urology, Department of Surgical Oncology, Princess Margaret Cancer Centre, University Health Network and the University of Toronto, Toronto, ON, Canada.

Shabbir Alibhai (S)

Department of Medicine, University Health Network, Toronto, ON, Canada; Department of Medicine, University of Toronto, Toronto, ON, Canada.

Alejandro Berlin (A)

Radiation Medicine Program, Princess Margaret Cancer Centre, University Health Network, Department of Radiation Oncology, University of Toronto, Toronto, ON, Canada; Techna Institute, University Health Network, Toronto, ON, Canada.

Neil Eric Fleshner (NE)

Division of Urology, Department of Surgical Oncology, Princess Margaret Cancer Centre, University Health Network and the University of Toronto, Toronto, ON, Canada.

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Classifications MeSH

questionsmedicales.fr › Personnes › Tranches d'âge › Adulte › Sujet âgé › Clinical-genomic Characterization Unveils More...
questionsmedicales.fr › Environnement et santé publique › Santé publique › Méthodes épidémiologiques › Caractéristiques des études épidémiologiques › Études épidémiologiques › Études transversales › Clinical-genomic Characterization Unveils More...
questionsmedicales.fr › Eucaryotes › Animaux › Chordés › Vertébrés › Mammifères › Eutheria › Primates › Haplorhini › Catarrhini › Hominidae › Humains › Clinical-genomic Characterization Unveils More...
questionsmedicales.fr › Acides aminés, peptides et protéines › Protéines › Globulines › Sérum-globulines › Immunoglobulines › Anticorps › Isotypes des immunoglobulines › Immunoglobuline G › Clinical-genomic Characterization Unveils More...
questionsmedicales.fr › Procédures de chirurgie opératoire › Procédures de chirurgie urogénitale › Procédures de chirurgie urologique › Procédures de chirurgie urologique masculine › Prostatectomie › Clinical-genomic Characterization Unveils More...
questionsmedicales.fr › Maladies urogénitales › Tumeurs de l'appareil urogénital › Tumeurs de l'appareil génital mâle › Tumeurs de la prostate › Clinical-genomic Characterization Unveils More...
questionsmedicales.fr › Environnement et santé publique › Santé publique › Méthodes épidémiologiques › Caractéristiques des études épidémiologiques › Études épidémiologiques › Études de cohortes › Études rétrospectives › Clinical-genomic Characterization Unveils More...