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Multicenter Study
. 2020 Dec;23(4):646-653.
doi: 10.1038/s41391-020-0226-2. Epub 2020 Mar 30.

Performance of clinicopathologic models in men with high risk localized prostate cancer: impact of a 22-gene genomic classifier

Jeffrey J Tosoian  1 , Samuel R Birer  2 , R Jeffrey Karnes  3 , Jingbin Zhang  4 , Elai Davicioni  4 , Eric E Klein  5 , Stephen J Freedland  6 , Sheila Weinmann  7 , Bruce J Trock  8 , Robert T Dess  2 , Shuang G Zhao  2 , William C Jackson  2 , Kosj Yamoah  9 , Alan Dal Pra  10 , Brandon A Mahal  11 , Todd M Morgan  1 , Rohit Mehra  12 , Samuel Kaffenberger  1 , Simpa S Salami  1 , Christopher Kane  13 , Alan Pollack  10 , Robert B Den  14 , Alejandro Berlin  15 , Edward M Schaeffer  16 , Paul L Nguyen  11 , Felix Y Feng  17 , Daniel E Spratt  18
Affiliations
Multicenter Study

Performance of clinicopathologic models in men with high risk localized prostate cancer: impact of a 22-gene genomic classifier

Jeffrey J Tosoian et al. Prostate Cancer Prostatic Dis. 2020 Dec.

Abstract

Background: Prostate cancer exhibits biological and clinical heterogeneity even within established clinico-pathologic risk groups. The Decipher genomic classifier (GC) is a validated method to further risk-stratify disease in patients with prostate cancer, but its performance solely within National Comprehensive Cancer Network (NCCN) high-risk disease has not been undertaken to date.

Methods: A multi-institutional retrospective study of 405 men with high-risk prostate cancer who underwent primary treatment with radical prostatectomy (RP) or radiation therapy (RT) with androgen-deprivation therapy (ADT) at 11 centers from 1995 to 2005 was performed. Cox proportional hazards models were used to determine the hazard ratios (HR) for the development of metastatic disease based on clinico-pathologic variables, risk groups, and GC score. The area under the receiver operating characteristic curve (AUC) was determined for regression models without and with the GC score.

Results: Over a median follow-up of 82 months, 104 patients (26%) developed metastatic disease. On univariable analysis, increasing GC score was significantly associated with metastatic disease ([HR]: 1.34 per 0.1 unit increase, 95% confidence interval [CI]: 1.19-1.50, p < 0.001), while age, serum PSA, biopsy GG, and clinical T-stage were not (all p > 0.05). On multivariable analysis, GC score (HR: 1.33 per 0.1 unit increase, 95% CI: 1.19-1.48, p < 0.001) and GC high-risk (vs low-risk, HR: 2.95, 95% CI: 1.79-4.87, p < 0.001) were significantly associated with metastasis. The addition of GC score to regression models based on NCCN risk group improved model AUC from 0.46 to 0.67, and CAPRA from 0.59 to 0.71.

Conclusions: Among men with high-risk prostate cancer, conventional clinico-pathologic data had poor discrimination to risk stratify development of metastatic disease. GC score was a significant and independent predictor of metastasis and may help identify men best suited for treatment intensification/de-escalation.

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Conflict of interest statement

Conflicts of Interest

Non-relevant conflicts of interest will be disclosed in the ICMJE forms.

JJT: Leadership role with equity interest: LynxDx, Inc.

SJF: Research funding: Decipher Biosciences.

SGZ: Travel/expenses and patent applications pending with Decipher Biosciences.

TMM: Research funding: Myriad Genetics, GenomeDx.

EMS: Consultant: Abbvie.

DES: Advisory board: Blue Earth and Janssen. Funding: Janssen.

Figures

Fig. 1 -
Fig. 1 -
Prognostic effect of clinical and pathologic variables on the cumulative incidence of metastases in men with high risk prostate cancer. Cumulative incidence curves of metastasis by (a) biopsy Grade Group, (b) clinical T-stage, and (c) National Comprehensive Cancer Network (NCCN) risk group.
Fig. 1 -
Fig. 1 -
Prognostic effect of clinical and pathologic variables on the cumulative incidence of metastases in men with high risk prostate cancer. Cumulative incidence curves of metastasis by (a) biopsy Grade Group, (b) clinical T-stage, and (c) National Comprehensive Cancer Network (NCCN) risk group.
Fig. 1 -
Fig. 1 -
Prognostic effect of clinical and pathologic variables on the cumulative incidence of metastases in men with high risk prostate cancer. Cumulative incidence curves of metastasis by (a) biopsy Grade Group, (b) clinical T-stage, and (c) National Comprehensive Cancer Network (NCCN) risk group.
Fig. 2 -
Fig. 2 -
Prognostic effect of Decipher on the cumulative incidence of metastases for men with high risk prostate cancer. Cumulative incidence curves of metastasis by Decipher low- (<0.45), intermediate- (0.45–0.60), and high-risk (>0.60) groups.
Fig. 3 -
Fig. 3 -
Discriminatory performance of clinicopathologic models and Decipher to predict metastatic outcome. (A) Time-dependent and (B) five-year area under the receiver operating characteristic curve (AUC) for metastasis based on National Comprehensive Cancer Network (NCCN) and Cancer of the Prostate Risk Assessment (CAPRA) risk groups without and with inclusion of Decipher score.
Fig. 3 -
Fig. 3 -
Discriminatory performance of clinicopathologic models and Decipher to predict metastatic outcome. (A) Time-dependent and (B) five-year area under the receiver operating characteristic curve (AUC) for metastasis based on National Comprehensive Cancer Network (NCCN) and Cancer of the Prostate Risk Assessment (CAPRA) risk groups without and with inclusion of Decipher score.
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References

    1. Fitzmaurice C, Akinyemiju TF, Al Lami FH, Alam T, Alizadeh-Navaei R, Allen C et al. Global, Regional, and National Cancer Incidence, Mortality, Years of Life Lost, Years Lived With Disability, and Disability-Adjusted Life-Years for 29 Cancer Groups, 1990 to 2016. JAMA Oncol 2018; 4: 1553. - PMC - PubMed
    1. Patrikidou A, Loriot Y, Eymard JC, Albiges L, Massard C, Ileana E et al. Who dies from prostate cancer? Prostate Cancer Prostatic Dis 2014; 17: 348–352. - PubMed
    1. Reese AC, Pierorazio PM, Han M, Partin AW. Contemporary evaluation of the national comprehensive cancer network prostate cancer risk classification system. Urology 2012; 80: 1075–1079. - PubMed
    1. Sundi D, Tosoian JJ, Nyame YA, Alam R, Achim M, Reichard CA et al. Outcomes of very high-risk prostate cancer after radical prostatectomy: Validation study from 3 centers. Cancer 2019; 125: 391–397. - PubMed
    1. Mahal BA, Butler S, Franco I, Spratt DE, Rebbeck TR, D’Amico AV et al. Use of Active Surveillance or Watchful Waiting for Low-Risk Prostate Cancer and Management Trends Across Risk Groups in the United States, 2010–2015Trends in Use of Active Surveillance and Watchful Waiting for Management of Low-Risk Prostate CancerLetters. JAMA 2019; 321: 704–706. - PMC - PubMed

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