Grade and volume progression and its association with the Decipher genomic classifier using patients enrolled in a prospective active surveillance protocol.

262 Background: The progression of prostate cancer through serial biopsies in patients on active surveillance is a multifaceted process, with grade and volume progression offering unique perspectives on disease advancement. The Decipher genomic classifier has been recognized as a valuable tool for predicting disease progression. This study examines the relationship between the Decipher score, and other GRID signatures and pathways, and grade and volume progression in prostate cancer patients, utilizing data collected prospectively from the Miami Active Surveillance Trial (MAST). Methods: We scrutinized 224 baseline samples from 124 unique patients participating in the MAST database. Progression was categorized into grade progression, volume progression, and no progression. For patients with multiple samples, the sample with the highest Decipher score was selected. We also evaluate the association between 11 prognostic signatures, including the Decipher score and an average genomic risk score combining the 11 signatures and 20 pathways available from the Decipher GRID. Results: Out of the baseline samples, 60 demonstrated grade progression, 51 volume progression, and 113 showed no progression. We found that the Decipher was not associated to our trial definition of progression, that combined grade and volume progression however we did find a statistically significant difference in Decipher scores from patients who experience grade progression (p=0.0005) as compared to volume progression (p=0.92) when comparing them with patients with no progression. A heat map evaluating prognostic signatures and pathways available on the Decipher grid found that the majority of prognostic signatures including the Decipher score and the average risk model were more associated with grade progression compared to volume or no progression. Conclusions: Our findings suggest that the Decipher score has a stronger correlation with grade progression than volume progression in prostate cancer patients. This highlights the potential of genomic classifiers like Decipher in enhancing our understanding of disease progression and in tailoring personalized treatment strategies. Further prospective studies are required to validate these findings. Clinical trial information: NCT02242773 .

Authors

Institutions

Publication Details

Journal
Journal of Clinical Oncology
Published
2025-02-10
DOI
https://doi.org/10.1200/jco.2025.43.5_suppl.262
Primary Topic
Medical Coding and Health Information
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Grade and volume progression and its association with the Decipher genomic classifier using patients enrolled in a prospective active surveillance protocol.

Yuval Avda, Sanoj Punnen, David Jungpa Lee, Tarek Ajami et al.
Journal of Clinical Oncology
Medical Coding and Health Information
article

Grade and volume progression and its association with the Decipher genomic classifier using patients enrolled in a prospective active surveillance protocol.

Yuval Avda, Sanoj Punnen, David Jungpa Lee, Tarek Ajami, Sandra M. Gaston, Dinno F. Mendiola, Joao G. Porto, Nachiketh Soodana‐Prakash, Archan Khandekar, Ankur Malpani, Hui Yu, Pedro F S Freitas, Brandon A. Mahal, Sanjaya Swain
article en

Abstract

262 Background: The progression of prostate cancer through serial biopsies in patients on active surveillance is a multifaceted process, with grade and volume progression offering unique perspectives on disease advancement. The Decipher genomic classifier has been recognized as a valuable tool for predicting disease progression. This study examines the relationship between the Decipher score, and other GRID signatures and pathways, and grade and volume progression in prostate cancer patients, utilizing data collected prospectively from the Miami Active Surveillance Trial (MAST). Methods: We scrutinized 224 baseline samples from 124 unique patients participating in the MAST database. Progression was categorized into grade progression, volume progression, and no progression. For patients with multiple samples, the sample with the highest Decipher score was selected. We also evaluate the association between 11 prognostic signatures, including the Decipher score and an average genomic risk score combining the 11 signatures and 20 pathways available from the Decipher GRID. Results: Out of the baseline samples, 60 demonstrated grade progression, 51 volume progression, and 113 showed no progression. We found that the Decipher was not associated to our trial definition of progression, that combined grade and volume progression however we did find a statistically significant difference in Decipher scores from patients who experience grade progression (p=0.0005) as compared to volume progression (p=0.92) when comparing them with patients with no progression. A heat map evaluating prognostic signatures and pathways available on the Decipher grid found that the majority of prognostic signatures including the Decipher score and the average risk model were more associated with grade progression compared to volume or no progression. Conclusions: Our findings suggest that the Decipher score has a stronger correlation with grade progression than volume progression in prostate cancer patients. This highlights the potential of genomic classifiers like Decipher in enhancing our understanding of disease progression and in tailoring personalized treatment strategies. Further prospective studies are required to validate these findings. Clinical trial information: NCT02242773 .

Journal of Clinical OncologyVol. 43(5_suppl)
University of Miami (US), University of Miami Hospital (US), Sylvester Comprehensive Cancer Center (US)
Openalex Percentile: Top 97%
Medical Coding and Health Information
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.