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Urology. 1999 Aug;54(2):220-4.

Use of percentage of free prostate-specific antigen to identify men at high risk of prostate cancer when PSA levels are 2.51 to 4 ng/mL and digital rectal examination is not suspicious for prostate cancer: an alternative model.

Author information

1
Division of Urologic Surgery, Washington University School of Medicine, St. Louis, Missouri, USA.

Abstract

OBJECTIVES:

Currently, many clinicians do not recommend prostate biopsy for men with digital rectal examination (DRE) results that are not suspicious for cancer and prostate-specific antigen (PSA) values between 2.51 and 4 ng/mL. We propose a new model for the detection of prostate cancer using the percentage of free PSA (%FPSA) in the limited range of PSA values between 2.51 and 4 ng/mL that maximizes clinical specificity (ie, minimizes false-positive results). This model identifies higher risk patients in this relatively low-risk population.

METHODS:

Three hundred sixty-eight archived serum samples from men evaluated and treated at two academic institutions were reviewed. All men had a histologic diagnosis, findings not suspicious for cancer on DRE, and PSA levels between 2.51 and 4 ng/mL. Samples were tested in Hybritech's Tandem-R PSA and Tandem-R free PSA (FPSA) assays in the same laboratory at each institution.

RESULTS:

Various models for cancer detection using %FPSA when PSA is 2.51 to 4 ng/mL and DRE is not suspicious for cancer are proposed. These models recommend biopsy for only 10% to 36% of the men in this population and would identify as many as 30% to 54% of the detectable cancers. There is evidence that the cancers that would be detected are the most aggressive cancers in this population.

CONCLUSIONS:

Our models identified men with a higher risk of prostate cancer in a relatively low-risk population that currently does not routinely undergo biopsy. This may allow for a more cost-effective way to increase cancer detection when PSA values are between 2.51 and 4 ng/mL and DRE is not suspicious for cancer. This model has the potential to detect a greater number of clinically important and potentially curable cancers than would be detected with current practice.

PMID:
10443714
DOI:
10.1016/s0090-4295(99)00185-5
[Indexed for MEDLINE]

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