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Validation of a genomic classifier for prediction of metastasis and prostate cancer-specific mortality in African-American men following radical prostatectomy in an equal access healthcare setting

Prostate Cancer and Prostatic Diseases volume 23, pages 419–428 (2020)Cite this article

Subjects

Abstract

Background

The Decipher 22-gene genomic classifier (GC) may help in post-radical prostatectomy (RP) decision making given its superior prognostic performance over clinicopathologic variables alone. However, most studies evaluating the GC have had a modest representation of African-American men (AAM). We evaluated the GC within a large Veteran Affairs cohort and compared its performance to CAPRA-S for predicting outcomes in AAM and non-AAM after RP.

Methods

GC scores were generated for 548 prostate cancer (PC) patients, who underwent RP at the Durham Veteran Affairs Medical Center between 1989 and 2016. This was a clinically high-risk cohort and was selected to have either pT3a, positive margins, seminal vesicle invasion, or received post-RP radiotherapy. Multivariable Cox models and survival C-indices were used to compare the performance of GC and CAPRA-S for predicting the risk of metastasis and PC-specific mortality (PCSM).

Results

Median follow-up was 9 years, during which 37 developed metastasis and 20 died from PC. Overall, 55% (n = 301) of patients were AAM. In multivariable analyses, GC (high vs. intermediate and intermediate vs. low) was a significant predictor of metastasis in all men (all p < 0.001). Consistent with prior studies, relative to CAPRA-S, GC had a higher C-index for 5-year metastasis (0.78 vs. 0.72) and 10-year PCSM (0.85 vs. 0.81). There was a suggestion GC was a stronger predictor in AAM than non-AAM. Specifically, the 5-year metastasis risk C-index was 0.86 in AAM vs. 0.69 in non-AAM and the 10-year PCSM risk C-index was 0.91 in AAM vs. 0.78 in non-AAM. However, the test for interaction of race and the performance of the GC in the Cox model was not significant for either metastasis or PCSM (both p ≥ 0.3).

Conclusions

GC was a very strong predictor of poor outcome and performed well in both AAM and non-AAM. Our data support the use of GC for risk stratification in AAM post-RP. While our data suggest that GC may actually work better in AAM, given the limited number of events, further validation is needed.

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Fig. 1: Consort diagram showing the cohort selection.
Fig. 2: Cumulative incidence of metastasis and prostate cancer-specific mortality, stratified by CAPRA-S and the Decipher genomic classifier.
Fig. 3: Receiver operating characteristic (ROC) curve for CAPRA-S and genomic classifier predicting 5-year metastasis and 10-year prostate cancer-specific mortality, stratified by race.
Fig. 4: Cumulative incidence of metastasis and prostate cancer-specific mortality by race, stratified by the Decipher genomic classifier.

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Acknowledgements

This study was funded by Decipher Biosciences.

Author information

Authors and Affiliations

  1. Duke Cancer Institute, Duke University School of Medicine, Durham, NC, USA

    Lauren E. Howard

  2. Department of Surgery, Division of Urology, Veteran Affairs Healthcare System, Durham, NC, USA

    Lauren E. Howard, Amanda M. De Hoedt & Stephen J. Freedland

  3. Decipher Biosciences, Inc, Vancouver, BC, Canada

    Jingbin Zhang, Nick Fishbane & Elai Davicioni

  4. Department of Surgery, Section of Urology, Augusta University - Medical College of Georgia, Augusta, GA, USA

    Zachary Klaassen

  5. Department of Radiation Oncology, University of Michigan, Ann Arbor, MI, USA

    Daniel E. Spratt

  6. Department of Surgery, Division of Urology, Cedars-Sinai Medical Center, Los Angeles, CA, USA

    Adriana C. Vidal, Sungyong You, Michael R. Freeman & Stephen J. Freedland

  7. Department of Medicine, Cedars-Sinai, Los Angeles, CA, USA

    Dechen Lin & Megan P. Hitchins

  8. Center for Bioinformatics and Functional Genomics, Cedars-Sinai, Los Angeles, CA, USA

    Dechen Lin & Megan P. Hitchins

  9. Department of Biomedical Sciences, Cedars-Sinai, Los Angeles, CA, USA

    Sungyong You & Michael R. Freeman

  10. Section of Genitourinary Radiation Oncology, Moffitt Cancer Center and Research Institute, Tampa, FL, USA

    Kosj Yamoah

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Correspondence to Stephen J. Freedland.

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JZ, NF, and ED are employees of Decipher Biosciences.

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Howard, L.E., Zhang, J., Fishbane, N. et al. Validation of a genomic classifier for prediction of metastasis and prostate cancer-specific mortality in African-American men following radical prostatectomy in an equal access healthcare setting. Prostate Cancer Prostatic Dis 23, 419–428 (2020). https://doi.org/10.1038/s41391-019-0197-3

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