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    In: Journal of Clinical Oncology, American Society of Clinical Oncology (ASCO), Vol. 27, No. 26 ( 2009-09-10), p. 4300-4305
    Abstract: The long-term risk of prostate cancer–specific mortality (PCSM) after radical prostatectomy is poorly defined for patients treated in the era of widespread prostate-specific antigen (PSA) screening. Models that predict the risk of PCSM are needed for patient counseling and clinical trial design. Methods A multi-institutional cohort of 12,677 patients treated with radical prostatectomy between 1987 and 2005 was analyzed for the risk of PCSM. Patient clinical information and treatment outcome was modeled using Fine and Gray competing risk regression analysis to predict PCSM. Results Fifteen-year PCSM and all-cause mortality were 12% and 38%, respectively. The estimated PCSM ranged from 5% to 38% for patients in the lowest and highest quartiles of predicted risk of PSA-defined recurrence, based on a popular nomogram. Biopsy Gleason grade, PSA, and year of surgery were associated with PCSM. A nomogram predicting the 15-year risk of PCSM was developed, and the externally validated concordance index was 0.82. Neither preoperative PSA velocity nor body mass index improved the model's accuracy. Only 4% of contemporary patients had a predicted 15-year PCSM of greater than 5%. Conclusion Few patients will die from prostate cancer within 15 years of radical prostatectomy, despite the presence of adverse clinical features. This favorable prognosis may be related to the effectiveness of radical prostatectomy (with or without secondary therapy) or the low lethality of screen-detected cancers. Given the limited ability to identify contemporary patients at substantially elevated risk of PCSM on the basis of clinical features alone, the need for novel markers specifically associated with the biology of lethal prostate cancer is evident.
    Type of Medium: Online Resource
    ISSN: 0732-183X , 1527-7755
    RVK:
    RVK:
    Language: English
    Publisher: American Society of Clinical Oncology (ASCO)
    Publication Date: 2009
    detail.hit.zdb_id: 2005181-5
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