PCA3: A Molecular Urine Assay for Predicting Prostate Biopsy Outcome

Autor: Sheila M.J. Aubin, Leonard S. Marks, Jack Groskopf, Alan W. Partin, Seongjoon Koo, Amy Blase, Harry G. Rittenhouse, John R. Day, Ina L. Deras, William J. Ellis, Yves Fradet
Rok vydání: 2008
Předmět:
Zdroj: Journal of Urology. 179:1587-1592
ISSN: 1527-3792
0022-5347
DOI: 10.1016/j.juro.2007.11.038
Popis: A urinary assay for PCA3, an mRNA that is highly over expressed in prostate cancer cells, has shown usefulness as a diagnostic test for this common malignancy. We further characterized PCA3 performance in different groups of men and determined whether the PCA3 score could synergize with other clinical information to predict biopsy outcome.Prospectively urine was collected following standardized digital rectal examination in 570 men immediately before prostate biopsy. Urinary PCA3 mRNA levels were quantified and then normalized to the amount of prostate derived RNA to generate a PCA3 score.The percent of biopsy positive men identified increased directly with the PCA3 score. PCA3 assay performance was equivalent in the first vs previous negative biopsy groups with an area under the ROC curve of 0.70 and 0.68, respectively. Unlike serum prostate specific antigen the PCA3 score did not increase with prostate volume. PCA3 assay sensitivity and specificity were equivalent at serum prostate specific antigen less than 4, 4 to 10 and more than 10 ng/ml. A logistic regression algorithm using PCA3, serum prostate specific antigen, prostate volume and digital rectal examination result increased the AUC from 0.69 for PCA3 alone to 0.75 (p = 0.0002).PCA3 is independent of prostate volume, serum prostate specific antigen level and the number of prior biopsies. The quantitative PCA3 score correlated with the probability of positive biopsy. Logistic regression results suggest that the PCA3 score could be incorporated into a nomogram for improved prediction of biopsy outcome. The results of this study provide further evidence that PCA3 is a useful adjunct to current methods for prostate cancer diagnosis.
Databáze: OpenAIRE