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

Prostate Cancer and Prostatic Diseases (2024)Cite this article

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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 from 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 one researcher with a second overreading. 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 the 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 the 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 the 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, evidence from current management-era data and of the predictive ability of these tests is needed.

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Fig. 1: Hazard ratio forest plot for biochemical recurrence by genomic classifier.
Fig. 2: Hazard ratio forest plot for development of metastases by genomic classifier.
Fig. 3: Hazard ratio forest plot for prostate cancer-specific mortality by genomic classifier.

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Data availability

Study protocol: available at www.crd.york.ac.uk/prospero (PROSPERO: CRD42022347950).

Code availability

Statistical code and data set: available from AMG (adelaide.gordon@va.gov).

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Acknowledgements

The authors thank the following key stakeholders and technical expert panel members for providing advice during the conduct of this review but who do not necessarily endorse the stated conclusions: Drs Maria Kelly, Edward Obedian, Michael G. Chang, Andrew Armstrong, Daniel Spratt, and Jeremy Shelton. In addition, we would like to thank Liz Wing and Stacy Lavin, for editorial assistance, and Julie Snyder for administrative support.

Funding

This project was funded by the Department of Veterans Affairs, Veterans Health Administration, Office of Research and Development, Quality Enhancement Research Initiative (ESP 09- 010). This work was also supported by the Durham Center of Innovation to Accelerate Discovery and Practice Transformation (ADAPT) (CIN 13-410) at the Durham VA Health Care System. Primary Funding Source: U.S. Department of Veterans Affairs (PROSPERO CRD42022347950). The US Department of Veterans Affairs was not involved in the design, conduct, or analysis interpretation.

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Authors and Affiliations

  1. Durham VA Health Care System, Durham, NC, USA

    Matthew J. Boyer, Jeffrey R. Gingrich, Rhonda L. Bitting, Adelaide M. Gordon, Belinda Ear, Jennifer M. Gierisch, Morgan Jacobs & Karen M. Goldstein

  2. Department of Radiation Oncology, Duke University School of Medicine, Durham, NC, USA

    Matthew J. Boyer

  3. Wellstar Radiation Oncology, Hiram, GA, USA

    David J. Carpenter

  4. Department of Urology, Duke University School of Medicine, Durham, NC, USA

    Jeffrey R. Gingrich

  5. Department of Population Health Sciences, Duke University School of Medicine, Durham, NC, USA

    Sudha R. Raman

  6. Department of Pathology, University of Utah School of Medicine, Salt Lake City, UT, USA

    Deepika Sirohi

  7. Department of Health Outcomes and Behavior, Moffitt Cancer Center, Tampa, FL, USA

    Amir Alishahi Tabriz

  8. Division of Urology, McGill University, Montreal, QC, Canada

    Alexis Rompre-Broduer

  9. Division of General Internal Medicine, Department of Medicine, Duke University School of Medicine, Durham, NC, USA

    Joseph Lunyera, Jennifer M. Gierisch & Karen M. Goldstein

  10. Division of Medical Oncology, Department of Medicine, Duke University School of Medicine, Durham, NC, USA

    Fahmin Basher & Rhonda L. Bitting

  11. Department of Biostatistics & Bioinformatics, Duke University School of Medicine, Durham, NC, USA

    Andrzej Kosinski

  12. Duke University Medical Center Library & Archives, Duke University School of Medicine, Durham, NC, USA

    Sarah Cantrell

  13. Department of Population Health, Duke University School of Medicine, Durham, NC, USA

    Jennifer M. Gierisch

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Contributions

Conceptualization: MB, DJC, JRG, SRR, DS, AAT, AR-B, JL, FB, RLB, SC, AMG, BE, JMG, KMG. Data curation: AK, AMG, BE, MJ, KMG. Formal analysis: MB, DJC, AK, AMG, KMG. Investigation: MB, DJC, JRG, SRR, DS, AAT, AR-B, JL, FB, RLB, AMG, JMG, KMG. Methodology: MB, DJC, JRG, SRR, DS, AAT, AR-B, JL, FB, RLB, AK, SC, AMG, BE, JMG, KMG. Project administration: AMG, BE, MJ. Supervision: KMG. Visualization: AK, MJ, KMG. Writing—original draft: MB, DJC, JRG, SRR, DS, AAT, AR-B, JL, FB, RLB, AMG, BE, KMG. Writing—review and editing: MB, DJC, JRG, SRR, DS, AAT, AR-B, JL, FB, RLB, AK, SC, AMG, JMG, KMG.

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Correspondence to Matthew J. Boyer.

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Boyer, M.J., Carpenter, D.J., Gingrich, J.R. et al. Genomic classifiers and prognosis of localized prostate cancer: a systematic review. Prostate Cancer Prostatic Dis (2024). https://doi.org/10.1038/s41391-023-00766-z

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