Computationally Derived Image Signature of Stromal Morphology Is Prognostic of Prostate Cancer Recurrence Following Prostatectomy in African American Patients.
Black or African American
/ statistics & numerical data
Biomarkers, Tumor
/ analysis
Disease Progression
Humans
Image Processing, Computer-Assisted
/ methods
Machine Learning
Male
Middle Aged
Neoplasm Recurrence, Local
/ metabolism
Nomograms
Predictive Value of Tests
Prognosis
Prostate-Specific Antigen
/ blood
Prostatectomy
/ methods
Prostatic Neoplasms
/ metabolism
ROC Curve
Risk Assessment
/ methods
Stromal Cells
/ pathology
Survival Rate
Journal
Clinical cancer research : an official journal of the American Association for Cancer Research
ISSN: 1557-3265
Titre abrégé: Clin Cancer Res
Pays: United States
ID NLM: 9502500
Informations de publication
Date de publication:
15 04 2020
15 04 2020
Historique:
received:
13
08
2019
revised:
17
12
2019
accepted:
30
01
2020
pubmed:
7
3
2020
medline:
28
1
2021
entrez:
7
3
2020
Statut:
ppublish
Résumé
Between 30%-40% of patients with prostate cancer experience disease recurrence following radical prostatectomy. Existing clinical models for recurrence risk prediction do not account for population-based variation in the tumor phenotype, despite recent evidence suggesting the presence of a unique, more aggressive prostate cancer phenotype in African American (AA) patients. We investigated the capacity of digitally measured, population-specific phenotypes of the intratumoral stroma to create improved models for prediction of recurrence following radical prostatectomy. This study included 334 radical prostatectomy patients subdivided into training (V An AA-specific, automated stromal signature, AAstro, was prognostic of recurrence risk in both independent validation datasets [V Our results suggest that considering population-specific information and stromal morphology has the potential to substantially improve accuracy of prognosis and risk stratification in AA patients with prostate cancer.
Identifiants
pubmed: 32139401
pii: 1078-0432.CCR-19-2659
doi: 10.1158/1078-0432.CCR-19-2659
pmc: PMC7165025
mid: NIHMS1558042
doi:
Substances chimiques
Biomarkers, Tumor
0
Prostate-Specific Antigen
EC 3.4.21.77
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Research Support, U.S. Gov't, Non-P.H.S.
Langues
eng
Sous-ensembles de citation
IM
Pagination
1915-1923Subventions
Organisme : NCI NIH HHS
ID : P20 CA233255
Pays : United States
Organisme : NCI NIH HHS
ID : R01 CA216579
Pays : United States
Organisme : NCI NIH HHS
ID : U24 CA199374
Pays : United States
Organisme : BLRD VA
ID : I01 BX004121
Pays : United States
Organisme : NIBIB NIH HHS
ID : R43 EB028736
Pays : United States
Organisme : NCI NIH HHS
ID : U01 CA239055
Pays : United States
Organisme : NCI NIH HHS
ID : R01 CA220581
Pays : United States
Organisme : NCI NIH HHS
ID : R01 CA202752
Pays : United States
Organisme : NCI NIH HHS
ID : R01 CA208236
Pays : United States
Informations de copyright
©2020 American Association for Cancer Research.
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