Lauren M Hurwitz1, Ilir Agalliu2, Demetrius Albanes1, Kathryn Hughes Barry3,4, Sonja I Berndt1, Qiuyin Cai5, Chu Chen6, Iona Cheng7, Jeanine M Genkinger8, Graham G Giles9,10,11, Jiaqi Huang1, Corinne E Joshu12, Tim J Key13, Synnove Knutsen14, Stella Koutros1, Hilde Langseth15,16, Sherly X Li9,10,17, Robert J MacInnis9,10, Sarah C Markt18, Kathryn L Penney19,20, Aurora Perez-Cornago13, Thomas E Rohan2, Stephanie A Smith-Warner20,21, Meir J Stampfer20, Konrad H Stopsack22, Catherine M Tangen23, Ruth C Travis13, Stephanie J Weinstein1, Wu Lang PhD24, Eric J Jacobs25, Lorelei A Mucci20, Elizabeth A Platz12, Michael B Cook1. 1. Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA. 2. Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA. 3. Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, MD, USA. 4. Program in Oncology, University of Maryland Marlene and Stewart Greenebaum Comprehensive Cancer Center, Baltimore, MD, USA. 5. Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, TN, USA. 6. Program in Epidemiology, Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA. 7. Department of Epidemiology and Biostatistics, Helen Diller Family Comprehensive Cancer Center, University of California San Francisco, San Francisco, CA, USA. 8. Department of Epidemiology, Columbia University Mailman School of Public Health, New York, NY, USA. 9. Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, VIC, Australia. 10. Centre for Epidemiology and Biostatistics, University of Melbourne, Parkville, VIC, Australia. 11. Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, VIC, Australia. 12. Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA. 13. Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK. 14. School of Public Health, Loma Linda University, Loma Linda, CA, USA. 15. Department of Research, Cancer Registry of Norway, Oslo, Norway. 16. Department of Epidemiology and Biostatistics, Imperial College London, London, UK. 17. Medical Research Council Epidemiology Unit, University of Cambridge, Cambridge, UK. 18. Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH, USA. 19. Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital/Harvard Medical School, Boston, MA, USA. 20. Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA. 21. Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA. 22. Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA. 23. SWOG Statistics and Data Management Center, Fred Hutchinson Cancer Research Center, Seattle, WA, USA. 24. Cancer Epidemiology Division, Population Sciences in the Pacific Program, University of Hawaii Cancer Center, University of Hawaii at Manoa, Honolulu, HI, USA. 25. Behavioral and Epidemiology Research Group, American Cancer Society, Atlanta, GA, USA.
Abstract
BACKGROUND: In the era of widespread prostate-specific antigen testing, it is important to focus etiologic research on the outcome of aggressive prostate cancer, but studies have defined this outcome differently. We aimed to develop an evidence-based consensus definition of aggressive prostate cancer using clinical features at diagnosis for etiologic epidemiologic research. METHODS: Among prostate cancer cases diagnosed in 2007 in the National Cancer Institute's Surveillance, Epidemiology, and End Results-18 database with follow-up through 2017, we compared the performance of categorizations of aggressive prostate cancer in discriminating fatal prostate cancer within 10 years of diagnosis, placing the most emphasis on sensitivity and positive predictive value (PPV). RESULTS: In our case population (n = 55 900), 3073 men died of prostate cancer within 10 years. Among 12 definitions that included TNM staging and Gleason score, sensitivities ranged from 0.64 to 0.89 and PPVs ranged from 0.09 to 0.23. We propose defining aggressive prostate cancer as diagnosis of category T4 or N1 or M1 or Gleason score of 8 or greater prostate cancer, because this definition had one of the higher PPVs (0.23, 95% confidence interval = 0.22 to 0.24) and reasonable sensitivity (0.66, 95% confidence interval = 0.64 to 0.67) for prostate cancer death within 10 years. Results were similar across sensitivity analyses. CONCLUSIONS: We recommend that etiologic epidemiologic studies of prostate cancer report results for this definition of aggressive prostate cancer. We also recommend that studies separately report results for advanced category (T4 or N1 or M1), high-grade (Gleason score ≥8), and fatal prostate cancer. Use of this comprehensive set of endpoints will facilitate comparison of results from different studies and help elucidate prostate cancer etiology. Published by Oxford University Press 2020.
BACKGROUND: In the era of widespread prostate-specific antigen testing, it is important to focus etiologic research on the outcome of aggressive prostate cancer, but studies have defined this outcome differently. We aimed to develop an evidence-based consensus definition of aggressive prostate cancer using clinical features at diagnosis for etiologic epidemiologic research. METHODS: Among prostate cancer cases diagnosed in 2007 in the National Cancer Institute's Surveillance, Epidemiology, and End Results-18 database with follow-up through 2017, we compared the performance of categorizations of aggressive prostate cancer in discriminating fatal prostate cancer within 10 years of diagnosis, placing the most emphasis on sensitivity and positive predictive value (PPV). RESULTS: In our case population (n = 55 900), 3073 men died of prostate cancer within 10 years. Among 12 definitions that included TNM staging and Gleason score, sensitivities ranged from 0.64 to 0.89 and PPVs ranged from 0.09 to 0.23. We propose defining aggressive prostate cancer as diagnosis of category T4 or N1 or M1 or Gleason score of 8 or greater prostate cancer, because this definition had one of the higher PPVs (0.23, 95% confidence interval = 0.22 to 0.24) and reasonable sensitivity (0.66, 95% confidence interval = 0.64 to 0.67) for prostate cancer death within 10 years. Results were similar across sensitivity analyses. CONCLUSIONS: We recommend that etiologic epidemiologic studies of prostate cancer report results for this definition of aggressive prostate cancer. We also recommend that studies separately report results for advanced category (T4 or N1 or M1), high-grade (Gleason score ≥8), and fatal prostate cancer. Use of this comprehensive set of endpoints will facilitate comparison of results from different studies and help elucidate prostate cancer etiology. Published by Oxford University Press 2020.
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