Researchers have developed a model to predict prostate cancer for men who undergo a prostate biopsy. The details of the risk calculator appear in the Journal of the National Cancer Institute.
Fifty percent of men in the United States undergo regular screening for prostate cancer, using a test that measures levels of prostate-specific antigen (PSA), a protein secreted by the prostate gland. However, recent research looking at PSA levels after a prostate biopsy has revealed that PSA level is not a very accurate predictor of prostate cancer risk. Prostate cancer can occur when PSA levels are "normal." Other variables, such as family history, age, race, and digital rectal examination (DRE) results also play a role in assessing prostate cancer risk.
To better assess prostate cancer risk, Ian M. Thompson, M.D., of the University of Texas Health Science Center at San Antonio, and colleagues analyzed information on 5519 men aged 55 or older from the placebo group of the Prostate Cancer Prevention Trial (PCPT). Men in the PCPT were followed for 7 years, receiving regular PSA screening and DREs annually. If tests were abnormal, men underwent a prostate biopsy to check for prostate cancer. Men also underwent biopsies at the end of the study if they had not undergone a biopsy during the study. The researchers used various statistical tests to analyze biopsy results, family history of prostate cancer, race, age, rectal examination results, and previous biopsy history.
The authors used the equations generated by their analysis to develop a risk calculator that can be used to assess an individual's risk of prostate cancer. The risk calculator is available online and can be used to calculate risk of prostate cancer and high-grade disease for men aged 50 years or and older who have no previous history of prostate cancer and who have had recent PSA screening and DRE tests.
The authors write, "This risk calculator model uses variables that go beyond only PSA level to help patients and physicians decide whether a prostate biopsy should be performed. We anticipate that the area of cancer risk modeling - including the incorporation of new risk variables and the understanding of patient decision-making - will have a measurable clinical impact over the next few years."
In an accompanying editorial, H. Ballentine Carter, M.D., of the Johns Hopkins School of Medicine in Baltimore, brings up concerns about over treatment of prostate cancer if the model were to pick up the non-lethal varieties of prostate cancer. He writes, "In the absence of accurate markers of life-threatening disease, I do not believe that physicians should endorse any approach to predicting the risk of prostate cancer that is likely to increase the diagnosis of biologically unimportant cancers. Once we have the ability to assess multiple risk factors (e.g., PSA or other new markers) in populations for which the long-term outcomes are known, approaches like the one described by Thompson, et al. will help identify those men who will benefit from active treatment."