BACKGROUND: A 17-gene biopsy-based reverse transcription polymerase chain reaction assay, which provides a Genomic Prostate Score (GPS-scale 0-100), has been validated as an independent predictor of adverse pathology and biochemical recurrence after radical prostatectomy (RP) in men with low- and intermediate-risk prostate cancer (PCa). OBJECTIVE: To evaluate GPS as a predictor of PCa metastasis and PCa-specific death (PCD) in a large cohort of men with localized PCa and long-term follow-up. DESIGN, SETTING, AND PARTICIPANTS: A retrospective study using a stratified cohort sampling design was performed in a cohort of men treated with RP within Kaiser Permanente Northern California. RNA from archival diagnostic biopsies was assayed to generate GPS results. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: We assessed the association between GPS and time to metastasis and PCD in prespecified uni- and multivariable statistical analyses, based on Cox proportional hazard models accounting for sampling weights. RESULTS AND LIMITATIONS: The final study population consisted of 279 men with low-, intermediate-, and high-risk PCa between 1995 and 2010 (median follow-up 9.8 yr), and included 64 PCD and 79 metastases. Valid GPS results were obtained for 259 (93%). In univariable analysis, GPS was strongly associated with time to PCD, hazard ratio (HR)/20 GPS units=3.23 (95% confidence interval [CI] 1.84-5.65; p<0.001), and time to metastasis, HR/20 units=2.75 (95% CI 1.63-4.63; p<0.001). The association between GPS and both end points remained significant after adjusting for National Comprehensive Cancer Network, American Urological Association, and Cancer of the Prostate Risk Assessment (CAPRA) risks (p<0.001). No patient with low- or intermediate-risk disease and a GPS of<20 developed metastases or PCD (n=31). In receiver operating characteristic analysis of PCD at 10 yr, GPS improved the c-statistic from 0.78 (CAPRA alone) to 0.84 (GPS+CAPRA; p<0.001). A limitation of the study was that patients were treated during an era when definitive treatment was standard of care with little adoption of active surveillance. CONCLUSIONS: GPS is a strong independent predictor of long-term outcomes in clinically localized PCa in men treated with RP and may improve risk stratification for men with newly diagnosed disease. PATIENT SUMMARY: Many prostate cancers are slow growing and unlikely to spread or threaten a man's life, while others are more aggressive and require treatment. Increasingly, doctors are using new molecular tests, such as the17-gene Genomic Prostate Score (GPS), which can be performed at the time of initial diagnosis to help determine how aggressive a given patient's cancer may be. In this study, performed in a large community-based healthcare network, GPS was shown to be a strong predictor as to whether a man's prostate cancer will spread and threaten his life after surgery, providing information that may help patients and their doctors decide on the best course of management of their disease.
BACKGROUND: A 17-gene biopsy-based reverse transcription polymerase chain reaction assay, which provides a Genomic Prostate Score (GPS-scale 0-100), has been validated as an independent predictor of adverse pathology and biochemical recurrence after radical prostatectomy (RP) in men with low- and intermediate-risk prostate cancer (PCa). OBJECTIVE: To evaluate GPS as a predictor of PCa metastasis and PCa-specific death (PCD) in a large cohort of men with localized PCa and long-term follow-up. DESIGN, SETTING, AND PARTICIPANTS: A retrospective study using a stratified cohort sampling design was performed in a cohort of men treated with RP within Kaiser Permanente Northern California. RNA from archival diagnostic biopsies was assayed to generate GPS results. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: We assessed the association between GPS and time to metastasis and PCD in prespecified uni- and multivariable statistical analyses, based on Cox proportional hazard models accounting for sampling weights. RESULTS AND LIMITATIONS: The final study population consisted of 279 men with low-, intermediate-, and high-risk PCa between 1995 and 2010 (median follow-up 9.8 yr), and included 64 PCD and 79 metastases. Valid GPS results were obtained for 259 (93%). In univariable analysis, GPS was strongly associated with time to PCD, hazard ratio (HR)/20 GPS units=3.23 (95% confidence interval [CI] 1.84-5.65; p<0.001), and time to metastasis, HR/20 units=2.75 (95% CI 1.63-4.63; p<0.001). The association between GPS and both end points remained significant after adjusting for National Comprehensive Cancer Network, American Urological Association, and Cancer of the Prostate Risk Assessment (CAPRA) risks (p<0.001). No patient with low- or intermediate-risk disease and a GPS of<20 developed metastases or PCD (n=31). In receiver operating characteristic analysis of PCD at 10 yr, GPS improved the c-statistic from 0.78 (CAPRA alone) to 0.84 (GPS+CAPRA; p<0.001). A limitation of the study was that patients were treated during an era when definitive treatment was standard of care with little adoption of active surveillance. CONCLUSIONS: GPS is a strong independent predictor of long-term outcomes in clinically localized PCa in men treated with RP and may improve risk stratification for men with newly diagnosed disease. PATIENT SUMMARY: Many prostate cancers are slow growing and unlikely to spread or threaten a man's life, while others are more aggressive and require treatment. Increasingly, doctors are using new molecular tests, such as the17-gene Genomic Prostate Score (GPS), which can be performed at the time of initial diagnosis to help determine how aggressive a given patient's cancer may be. In this study, performed in a large community-based healthcare network, GPS was shown to be a strong predictor as to whether a man's prostate cancer will spread and threaten his life after surgery, providing information that may help patients and their doctors decide on the best course of management of their disease.
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Authors: Daniel W Lin; Yingye Zheng; Jesse K McKenney; Marshall D Brown; Ruixiao Lu; Michael Crager; Hilary Boyer; Maria Tretiakova; James D Brooks; Atreya Dash; Michael D Fabrizio; Martin E Gleave; Suzanne Kolb; Michael Liss; Todd M Morgan; Ian M Thompson; Andrew A Wagner; Athanasios Tsiatis; Andrea Pingitore; Peter S Nelson; Lisa F Newcomb Journal: J Clin Oncol Date: 2020-03-04 Impact factor: 44.544
Authors: Belén Pastor-Navarro; José Rubio-Briones; Ángel Borque-Fernando; Luis M Esteban; Jose Luis Dominguez-Escrig; José Antonio López-Guerrero Journal: Int J Mol Sci Date: 2021-06-10 Impact factor: 5.923