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Selective detection of histologically aggressive prostate cancer

dc.contributor.authorWilliams, Stephen B.en_US
dc.contributor.authorSalami, Simpaen_US
dc.contributor.authorRegan, Meredith M.en_US
dc.contributor.authorAnkerst, Donna P.en_US
dc.contributor.authorWei, John T.en_US
dc.contributor.authorRubin, Mark A.en_US
dc.contributor.authorThompson, Ian M.en_US
dc.contributor.authorSanda, Martin G.en_US
dc.date.accessioned2012-05-21T15:47:22Z
dc.date.available2013-07-01T14:33:05Zen_US
dc.date.issued2012-05-15en_US
dc.identifier.citationWilliams, Stephen B.; Salami, Simpa; Regan, Meredith M.; Ankerst, Donna P.; Wei, John T.; Rubin, Mark A.; Thompson, Ian M.; Sanda, Martin G. (2012). "Selective detection of histologically aggressive prostate cancer ." Cancer 118(10): 2651-2658. <http://hdl.handle.net/2027.42/91121>en_US
dc.identifier.issn0008-543Xen_US
dc.identifier.issn1097-0142en_US
dc.identifier.urihttps://hdl.handle.net/2027.42/91121
dc.description.abstractBACKGROUND: Limited survival benefit and excess treatment because of prostate‐specific antigen (PSA) screening in randomized trials suggests a need for more restricted selection of prostate biopsy candidates by discerning risk of histologically aggressive versus indolent cancer before biopsy. METHODS: Subjects undergoing first prostate biopsy enrolled in a multicenter, prospective cohort of the National Cancer Institute Early Detection Research Network (N = 635) were analyzed to develop a model for predicting histologically aggressive prostate cancers. The control arm of the Prostate Cancer Prevention Trial (N = 3833) was used to validate the generalization of the predictive model. RESULTS: The Early Detection Research Network cohort was comprised of men among whom 57% had no cancer, 14% had indolent cancer, and 29% had aggressive cancer. Age, body mass index, family history of prostate cancer, abnormal digital rectal examination (DRE), and PSA density (PSAD) were associated with aggressive cancer (all P < .001). The Early Detection Research Network model outperformed PSA alone in predicting aggressive cancer (area under the curve [AUC] = 0.81 vs 0.71, P < .01). Model validation in the Prostate Cancer Prevention Trial cohort accurately identified men at low (<10%) risk of aggressive cancer for whom biopsy could be averted (AUC = 0.78; 95% confidence interval, 0.75‐0.80). Under criteria from the Early Detection Research Network model, prostate biopsy can be restricted to men with PSAD >0.1 ng/mL/cc or abnormal DRE. When PSAD is <0.1 ng/mL/cc, family history or obesity can identify biopsy candidates. CONCLUSIONS: A predictive model incorporating age, family history, obesity, PSAD, and DRE elucidates criteria whereby ¼ of prostate biopsies can be averted while retaining high sensitivity in detecting aggressive prostate cancer. Cancer 2011. © 2011 American Cancer Society. A predictive model incorporating age, family history, obesity, prostate‐specific antigen density, and digital rectal examination has been proposed in detecting aggressive prostate cancer. Using these criteria, ¼ of prostate biopsies can be avoided.en_US
dc.publisherWiley Subscription Services, Inc., A Wiley Companyen_US
dc.subject.otherIndolenten_US
dc.subject.otherProstate Canceren_US
dc.subject.otherBiopsyen_US
dc.subject.otherClinically Significanten_US
dc.titleSelective detection of histologically aggressive prostate canceren_US
dc.typeArticleen_US
dc.rights.robotsIndexNoFollowen_US
dc.subject.hlbsecondlevelOncology and Hematologyen_US
dc.subject.hlbsecondlevelPublic Healthen_US
dc.subject.hlbtoplevelHealth Sciencesen_US
dc.description.peerreviewedPeer Revieweden_US
dc.contributor.affiliationumDepartment of Urology, University of Michigan, Ann Arbor, Michiganen_US
dc.contributor.affiliationother330 Brookline Ave, Rabb 440, Division of Urology, BIDMC, Boston, MA 20115en_US
dc.contributor.affiliationotherDivision of Urology, Beth Israel Deaconess Medical Center, Boston, Massachusettsen_US
dc.contributor.affiliationotherDivision of Urology, Brigham and Women's Hospital, Boston, Massachusettsen_US
dc.contributor.affiliationotherHarvard Medical School, Boston, Massachusettsen_US
dc.contributor.affiliationotherDepartment of Biostatistics and Computational Biology, Dana‐Farber Cancer Institute, Boston, Massachusettsen_US
dc.contributor.affiliationotherUniversity of Texas Health Science Center at San Antonio, San Antonio, Texasen_US
dc.contributor.affiliationotherDepartment of Pathology and Laboratory Medicine, Weill Cornell Medical College, New York, New Yorken_US
dc.identifier.pmid22006057en_US
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/91121/1/26396_ftp.pdf
dc.identifier.doi10.1002/cncr.26396en_US
dc.identifier.sourceCanceren_US
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dc.owningcollnameInterdisciplinary and Peer-Reviewed


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