Genomic Classifier Performance in Intermediate-Risk Prostate Cancer: Results From NRG Oncology/RTOG 0126 Randomized Phase 3 Trial
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In newly diagnosed localized disease, tissue-based genomic classifiers are generally used to refine baseline risk and guide decisions between active surveillance and definitive treatment.
“In newly diagnosed localized disease, tissue-based genomic classifiers are generally used to refine baseline risk and guide decisions between active surveillance and definitive treatment [4–7].”
From A decision-oriented framework for genomic testing across the prostate cancer continuum (2026) · cites this paper as [7]
The Introduction (page unavailable) says the Decipher classifier improves risk stratification in intermediate-risk prostate cancer, and the Discussion (page unavailable) describes using its results to inform treatment-intensification decisions. The paper lists active surveillance as a treatment option but does not show that classifiers generally guide the choice between active surveillance and definitive treatment; its trial compared radiation doses in men receiving definitive treatment. (LLM, conf=0.86)
Experimental — accuracy not yet measuredTissue-based genomic classifiers provide prognostic information regarding adverse pathology, biochemical recurrence, and metastatic risk but generally do not identify specific therapeutic targets.
“These assays provide prognostic information regarding adverse pathology, biochemical recurrence, and metastatic risk but generally do not identify specific therapeutic targets.”
From A decision-oriented framework for genomic testing across the prostate cancer continuum (2026) · cites this paper as [7]
The Results and Conclusion report that the biopsy-based Decipher classifier was prognostic for biochemical failure and distant metastasis in men with intermediate-risk prostate cancer. The paper does not establish the broader claim about adverse pathology or say that tissue-based genomic classifiers generally do not identify specific therapeutic targets. (LLM, conf=0.85)
Experimental — accuracy not yet measuredTissue-based genomic classifiers can improve risk refinement in localized disease, but their incremental utility is context dependent and not uniformly transformative.
“Tissue-based genomic classifiers can improve risk refinement in localized disease, but their incremental utility is context dependent and not uniformly transformative [4–7].”
From A decision-oriented framework for genomic testing across the prostate cancer continuum (2026) · cites this paper as [7]
Decipher has broader validation across both biopsy and prostatectomy contexts and has demonstrated associations with metastasis and prostate cancer-specific mortality, including in randomized trial cohorts.
“Decipher has broader validation across both biopsy and prostatectomy contexts and has demonstrated associations with metastasis and prostate cancer–specific mortality, including in randomized trial cohorts [6, 7].”
From A decision-oriented framework for genomic testing across the prostate cancer continuum (2026) · cites this paper as [7]
In localized prostate cancer, tissue-based genomic classifiers primarily serve prognostic functions by refining risk estimates beyond clinicopathologic variables.
“In localized disease, tissue-based genomic classifiers primarily serve prognostic functions by refining risk estimates beyond clinicopathologic variables”
From A decision-oriented framework for genomic testing across the prostate cancer continuum (2026) · cites this paper as [7]
In biochemical recurrence, genomic classifiers may help identify patients at higher risk of metastatic progression or those who may benefit from treatment intensification in conjunction with salvage therapy.
“In biochemical recurrence, genomic classifiers may help identify patients at higher risk of metastatic progression or those who may benefit from treatment intensification in conjunction with salvage therapy [6, 7].”
From A decision-oriented framework for genomic testing across the prostate cancer continuum (2026) · cites this paper as [7]
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Research works printed but not linked: 14
- Spratt DE, Zhang J, Santiago-Jiménez M, et al. Development and validation of a novel integrated clinical-genomic risk group classification for localized prostate cancer. J Clin Oncol 2018;36:581- 590. [PubMed: 29185869]
- Berlin A, Murgic J, Hosni A, et al. Genomic classifier for guiding treatment of intermediate-risk prostate cancers to dose-escalated image guided radiation therapy without hormone therapy. Int J Radiat Oncol Biol Phys 2019;103:84-91. [PubMed: 30170099]
- Jairath NK, Dal Pra A, Vince R Jr., et al. A Systematic Review of the Evidence for the Decipher Genomic Classifier in Prostate Cancer. Eur Urol 2021;79:374-383. [PubMed: 33293078]
- Feng FY, Huang HC, Spratt DE, et al. Validation of a 22-gene genomic classifier in patients with recurrent prostate cancer: an ancillary study of the NRG/RTOG 9601 randomized clinical trial [published correction appears in JAMA Oncol. 2021 Apr 1;7(4):639]. JAMA Oncol 2021; 7: 544- 552. [PubMed: 33570548]
- Nguyen PL, Martin NE, Choeurng V, et al. Utilization of biopsy-based genomic classifier to predict distant metastasis after definitive radiation and short-course ADT for intermediate and high-risk prostate cancer. Prostate Cancer Prostatic Dis 2017;20:186-192. [PubMed: 28117383]
- Ross AE, Johnson MH, Yousefi K, et al. Tissue-based genomics augments post-prostatectomy risk stratification in a natural history cohort of intermediate-and high-risk men. Eur Urol 2016;69:157- 165. [PubMed: 26058959]
- Abdueva D, Wing M, Schaub B, Triche T, Davicioni E. Quantitative expression profiling in formalin-fixed paraffin-embedded samples by affymetrix microarrays. J Mol Diagn 2010;12:409- 417. [PubMed: 20522636]
- Muralidhar V, Zhang J, Wang Q, et al. Genomic validation of 3-tiered clinical subclassification of high-risk prostate cancer. Int J Radiat Oncol Biol Phys 2019;105:621-627. [PubMed: 31271825]
- Nguyen PL, Huang HR, Spratt DE, et al. Analysis of a biopsy-based genomic classifier in high-risk prostate cancer: meta-analysis of the NRG oncology/radiation therapy oncology group 9202, 9413, and 9902 phase 3 randomized trials. IntJ Radiat Oncol Biol Phys 2023;116:521-529. [PubMed: 36596347]
- Jones CU, Hunt D, McGowan DG, et al. Radiotherapy and short-term androgen deprivation for localized prostate cancer. New Engl J Med 2011;365:107-118. [PubMed: 21751904]
- Kishan AU, Sun Y, Hartman H, et al. Androgen deprivation therapy use and duration with definitive radiotherapy for localised prostate cancer: An individual patient data meta-analysis [published correction appears in Lancet Oncol. 2022;23:e319]. Lancet Oncol. 2022;23:304-316. [PubMed: 35051385]
- Spratt DE, Tward JD. Absolute versus Relative Benefit of Androgen Deprivation Therapy for Prostate Cancer: Moving Beyond the Hazard Ratio to Personalize Therapy. Int J Radiat Oncol Biol Phys 2020;108:899-902. [PubMed: 32928598]
- Tward J, Lenz L, Flake II DD, et al. The Clinical Cell-Cycle Risk (CCR) score is associated with metastasis after radiation therapy and provides guidance on when to forgo combined androgen deprivation therapy with dose-escalated radiation. Int J Radiat Oncol Biol Phys 2022;113:66-76. [PubMed: 34610388]
- Dal Pra A, Ghadjar P, Hayoz S, et al. Validation of the Decipher genomic classifier in patients receiving salvage radiotherapy without hormone therapy after radical prostatectomy -an ancillary study of the SAKK 09/10 randomized clinical trial. Ann Oncol 2022;33:950-958. [PubMed: 35636621]
Cited by
Sorted by citations
A decision-oriented framework for genomic testing across the prostate cancer continuum
Cobran, E. K., Samadder, N. J., Schaid, D. J., Conti, D. V., Haiman, C., Vargas, L., Gionfriddo, M. R., & Tilburt, J. C. (2026) · Cancer Genetics · doi:10.1016/j.cancergen.2026.06.002 · Cited by 1 · see citing works
- Authors
- Spratt, D. E., Liu, V. Y. T., Michalski, J., Davicioni, E., Berlin, A., Simko, J. P., Efstathiou, J. A., Tran, P. T., Sandler, H. M., Hall, W. A., Thompson, D. J. S., Parliament, M. B., Dayes, I. S., Correa, R. J. M., Robertson, J. M., Gore, E. M., Doncals, D. E., Vigneault, E., Souhami, L., Karrison, T. G., & Feng, F. Y.
- ORCID
- Spratt, Daniel E.
- Venue
- International Journal of Radiation Oncology*Biology*Physics
- Publisher
- Elsevier BV
- Published
- 2023-10
- Volume
- 117
- Issue
- 2
- Pages
- 370-377
- ISSN
- 0360-3016
- Cited by
- 44
- References
- 0
- Language
- en
- Update notices
- erratum (2024-12-01)
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