Prostate-specific antigen kinetics in localized and advanced prostate cancer

The successful management of prostate cancer requires early detection, appropriate risk assessment and optimum treatment. To this end, much research has been conducted over many years with the goal of identifying a reliable and easily measurable tumour marker that could be used on a large scale for the diagnosis, staging and monitoring of the disease. Prostate-specific antigen (PSA) was independently discovered by two groups in the 1960s and 1970s, in semen and prostate tissue, and given different names. It later became evident that these proteins were encoded by the same gene and were the same protein. PSA was then identified as a useful marker for assessing patients with prostate cancer during their follow-up. In 1986, PSA was approved by the United States Food and Drug Administration to monitor prostate cancer, and in 1994 approved as a tool for detecting the disease in men aged >= 50 years. PSA is now the most widely used serum marker for detecting and monitoring prostate cancer, but its use as a diagnostic marker is controversial because it has several limitations, including its low specificity (PSA levels are also increased in benign prostatic hyperplasia, and in general inflammatory responses) and low sensitivity. Furthermore, PSA levels are highly variable over time, and PSA poorly distinguishes indolent from aggressive cancers. As such, the use of PSA level as a diagnostic tool can lead to over-detection of cancers that pose little threat to health and/or life. Moreover, the impact of PSA screening on prostate cancer mortality rates remains controversial, and will do so until the results of currently ongoing randomized controlled studies in Europe and the USA become available. To overcome the limitations of using PSA, research on PSA kinetics has developed considerably in the last decade. We review publications on the added value of PSA kinetics compared with single PSA measurements in the early detection of prostate cancer, and in predicting the outcome of patients with localized and advanced disease.