A single serum PSA measurement is commonly used as a screening test to identify men with prostate cancer.
A rise in PSA over time may identify men at increased risk of prostate cancer. Dynamic measures of PSA change (ex: PSA velocity, PSA doubling time) are frequently used to justify prostate biopsy in men. We demonstrate that the current serum PSA is the best predictor of future prostate cancer risk among commonly available clinical variables. We show that dynamic measures of PSA change do not improve upon PSA's ability to predict future prostate cancer. Our study suggests that dynamic measures of PSA change may not be useful in screening for prostate cancer.
OBJECTIVE: To determine whether prostate-specific antigen velocity (PSA-V), PSA doubling time (PSA-DT), or PSA percentage change (PSA-PC) add incremental information to PSA alone for community-based men undergoing prostate cancer (PCa) screening.
ARTICIPANTS AND METHODS:P A population-based cohort of 11 872 men from Olmsted County, MN undergoing PSA screening for PCa from 1993 to 2005 was analysed for PSA, PSA-DT, PSA-PC and PSA-V and subsequent PCa. Receiver-operating characteristics curves and logistic regression were used to calculate the area under the curve (AUC) and Aikaike's information criterion. Reclassification analysis was performed and the net reclassification improvement and integrated discrimination improvement were measured. The method of Begg and Greenes was used to adjust for verification bias.
RESULTS: The single best predictor of future PCa was PSA (AUC = 0.773) with PSA-V (AUC = 0.729) and PSA-DT/PSA-PC (AUC = 0.689) performing worse. After age adjustment, combining PSA with PSA-V (AUC = 0.773) or PSA-DT/PSA-PC (AUC = 0.773) resulted in no better predictions than PSA alone. Reclassification analysis showed that adding PSA-V or PSA-DT/PSA-PC to PSA did not result in a meaningful amount of reclassification.
CONCLUSIONS: PSA is a better predictor of future PCa than PSA-V, PSA-DT, or PSA-PC. Adding PSA-V, PSA-DT, or PSA-PC to PSA does not result in clinically relevant improvements in the ability to predict future PCa.
Written by:
Inman BA, Zhang J, Shah ND, Denton BT. Are you the author?
Division of Urology, Duke University Medical Center, Durham, NC; Philips Research North America, Briarcliff Manor, NY; Division of Health Care Policy and Research, Mayo Clinic College of Medicine, Rochester, MN; Edward P. Fitts Department of Industrial & Systems Engineering, North Carolina State University, Raleigh, NC, USA.
Reference: BJU Int. 2012 Feb 7. Epub ahead of print.
doi: 10.1111/j.1464-410X.2011.10925.x
PubMed Abstract
PMID: 22313933
