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Departments of 1 Urology, 2 Pathology, and 3 Cellular and Structural Biology, University of Texas Health Science Center, and 4 Brooke Army Medical Center, San Antonio, Texas; 5 Department of Preventive Medicine and Community Health, University of Texas Medical Branch, Galveston, Texas; 6 Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland; and 7 University of Pittsburgh Cancer Center, Pittsburgh, Pennsylvania
Requests for reprints: Dipen Parekh, Department of Urology, University of Texas Health Sciences Center at San Antonio, 7703 Floyd Curl Drive, San Antonio, TX 78284-7802. Phone: 210-567-5640; Fax: 210-567-6868. E-mail: parekhd{at}uthscsa.edu
Objective: We analyzed the association of 54 biomarkers from seven classes including adipokines, immune response metalloproteinases, adhesion molecules, and growth factors with prostate cancer risk adjusting for the Prostate Cancer Prevention Trial (PCPT) risk score.
Methods: A total of 123 incident prostate cancer cases and 127 age-matched controls were selected from subjects in the San Antonio Center for Biomarkers of Risk of Prostate Cancer cohort study. Prediagnostic serum concentrations were measured in the sample collected at baseline using LabMAP technology. The odds ratios (OR) of prostate cancer risk associated with serum concentrations of 54 markers were estimated using univariate conditional logistic regression before and after adjustment for the PCPT risk score. Two-way hierarchical unsupervised clustering techniques were used to evaluate whether the 54-marker panel distinguished cases from controls.
Results: Vascular endothelial growth factor, resistin, interleukin 1Ra (IL-1Ra), granulocyte colony-stimulating factor, matrix metalloproteinase-3, plasminogen activator inhibitor, and kallikrein-8 were statistically significantly (P < 0.05) underexpressed in prostate cancer cases, and
-fetoprotein was statistically significantly overexpressed in prostate cancer cases, but all had area underneath the receiver-operating characteristic curve <60%; none were statistically significant adjusting for multiple comparisons (P < 0.0008) or after adjustment for the PCPT risk score. Statistical clustering of patients by the marker panel did not distinguish a separate group of cases from controls.
Conclusions: This age-matched case-control study did not support findings of increased diagnostic potential from a 54-marker panel when compared with the conventional risk factors incorporated in the PCPT risk calculator. Future discovery of new biomarkers should always be tested and compared against conventional risk factors before applying them in clinical practice. (Cancer Epidemiol Biomarkers Prev 2007;16(10):1966–72)
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Cancer Epidemiol. Biomarkers Prev., November 1, 2007; 16(11): 2519 - 2519. [Full Text] [PDF] |
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