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Genomic classifiers and prognosis of localized prostate cancer: a systematic review

Open access
Boyer, Matthew J., Carpenter, David J., Gingrich, Jeffrey R., Raman, Sudha R., Sirohi, Deepika, Tabriz, Amir Alishahi, Rompre-Broduer, Alexis, Lunyera, Joseph, Basher, Fahmin, Bitting, Rhonda L., Kosinski, Andrzej, Cantrell, Sarah, Gordon, Adelaide M., Ear, Belinda, Gierisch, Jennifer M., Jacobs, Morgan, Goldstein, Karen M.·2025·Prostate Cancer and Prostatic Diseases
DOI 10.1038/s41391-023-00766-z

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Abstract

Abstract Background Refinement of the risk classification for localized prostate cancer is warranted to aid in clinical decision making. A systematic analysis was undertaken to evaluate the prognostic ability of three genomic classifiers, Decipher, GPS, and Prolaris, for biochemical recurrence, development of metastases and prostate cancer specific mortality in patients with localized prostate cancer. Methods Data Sources: MEDLINE, Embase, and Web of Science were queried for reports published January 2010 to April 2022. Study Selection: Prospective or retrospective studies reporting prognosis for patients with localized prostate cancer. Data Extraction: Relevant data were extracted into a customized database by 1 researcher with a second over reading. Risk of bias was assessed using a validated tool for prognostic studies, Quality in Prognosis Studies (QUIPS). Disagreements were resolved by consensus or by input from a third reviewer. We assessed certainty of evidence by GRADE incorporating adaptation for prognostic studies. Results Data Synthesis: A total of 39 studies (37 retrospective) involving over 10 000 patients were identified. Twenty-two assessed Decipher, 5 GPS, and 14 Prolaris. Thirty-four studies included patients who underwent prostatectomy. Based on very low to low certainty of evidence, each of three genomic classifiers modestly improved upon the prognostic ability for biochemical recurrence, development of metastases, and prostate cancer specific mortality compared to standard clinical risk classification schemes Limitations: Downgrading of confidence in the evidence stemmed largely from bias due to the retrospective nature of the studies, heterogeneity in treatment received, and era in which patients were treated (i.e., prior to 2000s). Conclusions: Genomic classifiers provide a small but consistent improvement upon the prognostic ability of clinical classification schemes which may be helpful when treatment decisions are uncertain. However, definitive evidence from current management-era data is needed.

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  • A central limitation in current clinical practice is the misalignment between biomarker function and clinical decision context.

    “A central limitation in current clinical practice is the misalignment between biomarker function and clinical decision context.”

    From A decision-oriented framework for genomic testing across the prostate cancer continuum (2026) · cites this paper as [5]

    The Discussion (page unavailable) identifies a mismatch between some genomic-classifier studies and clinical use: 16 of 39 used comparators not typically employed in practice, and some measured biochemical recurrence rather than a more clinically meaningful outcome. Its conclusion calls for evidence more directly relevant to current prostate cancer care. The paper frames this as a limitation of evidence for genomic classifiers in localized prostate cancer, not as a general limitation of current clinical practice or of biomarker function. (LLM, conf=0.82)

    Experimental — accuracy not yet measured

  • 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 [5]

    The Introduction (page unavailable) says tissue-based genomic classifiers were developed to refine clinical risk classifications and inform personalized treatment recommendations for localized prostate cancer. It does not establish that they are generally used in newly diagnosed patients specifically to choose between active surveillance and definitive treatment; the Results (page unavailable) say most included studies involved patients who initially underwent prostatectomy. (LLM, conf=0.83)

    Experimental — accuracy not yet measured

  • Prognostic classifiers are sometimes overinterpreted as treatment-directing tools, while predictive biomarkers with clear therapeutic implications remain underutilized.

    “Prognostic classifiers are sometimes overinterpreted as treatment-directing tools, while predictive biomarkers with clear therapeutic implications remain underutilized [4, 5].”

    From A decision-oriented framework for genomic testing across the prostate cancer continuum (2026) · cites this paper as [5]

    The Introduction (page unavailable) describes the classifiers as tools for estimating prognosis and says large studies of their predictive ability are still underway. The Discussion (page unavailable) questions the clinical meaning of their modest prognostic improvement. This supports caution about treating prognostic results as treatment-directing evidence, but the paper does not say that clinicians sometimes overinterpret them or that predictive biomarkers with clear therapeutic implications are underutilized. (LLM, conf=0.77)

    Experimental — accuracy not yet measured

  • Tissue-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 [5]

    The Discussion (page unavailable) reports that genomic classifiers modestly improve prognostic assessment for biochemical recurrence and metastases. The Introduction describes them as tissue-based tests that estimate prognosis. The review does not establish the claimed limitation concerning specific therapeutic targets; adverse pathology appears in cited study titles, but is not established as a reviewed outcome in the passages found. (LLM, conf=0.86)

    Experimental — accuracy not yet measured

  • 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 [5]

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Metadata

Authors
Boyer, M. J., Carpenter, D. J., Gingrich, J. R., Raman, S. R., Sirohi, D., Tabriz, A. A., Rompre-Broduer, A., Lunyera, J., Basher, F., Bitting, R. L., Kosinski, A., Cantrell, S., Gordon, A. M., Ear, B., Gierisch, J. M., Jacobs, M., & Goldstein, K. M.
Affiliations
  • Duke University (US)
  • WellStar Health System (US)
  • University of Utah (US)
  • Moffitt Cancer Center (US)
  • Duke Medical Center (US)
  • Durham VA Health Care System (US)
Corresponding author
Boyer, Matthew J.
ORCID
Venue
Prostate Cancer and Prostatic Diseases
Publisher
Springer Science and Business Media LLC
Published
2024-01-10
Volume
28
Issue
1
Pages
103-111
ISSN
  • 1365-7852 (ISSN-L)
  • 1476-5608
DOI
10.1038/s41391-023-00766-z
OpenAlex
W4390698406
Cited by
22
References
2
Citations by year
2026: 11 · 2025: 8 · 2024: 3
FWCI
2.00
Type
journal article
Language
en
Open access
Licence
Locations
  • Prostate Cancer and Prostatic Diseases (publishedVersion)
  • Research Square (acceptedVersion, cc-by)
  • PubMed (publishedVersion)
Funders
  • U.S. Department of Veterans Affairs (ESP-09-010)
  • Quality Enhancement Research Initiative
Topics
  • Health Sciences › Medicine › Urology › Prostate Cancer Diagnosis and Treatment
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Prostate Cancer Treatment and Research
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Breast Cancer Treatment Studies
Keywords
localized prostate cancer, genomic classifier, DECIPHER, GPS, Prolaris, prognostic factors, biochemical recurrence, metastasis, prostate cancer-specific mortality, risk classification, prostatectomy, clinical decision-making
MeSH terms
Humans, Male, Neoplasm Recurrence, Local, Prognosis, Prostatic Neoplasms, Biomarkers, Tumor, Genomics

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