title: Estimation of prostate cancer risk on the basis of total and free prostate-specific antigen, prostate volume and digital rectal examination.
abstract: OBJECTIVE
  Approximately 70% of the men with an elevated serum prostate-specific antigen (PSA) identified in prostate cancer screening do not have prostate cancer. Other available diagnostic variables may be utilized to reduce the number of false positive PSA results, but few algorithms for calculation of the combined impact of multiple variables are available. The objective of this study was to establish nomograms showing the probability of detecting prostate cancer at biopsy on the basis of total PSA, and the percentage of free PSA in serum, prostate volume and digital rectal examination (DRE) findings.
  
  
  METHODS
  In a randomized, population-based prostate cancer screening trial 10284 men aged 55-67 years were screened during 1996 and 1997 in two metropolitan areas in Finland. Results for men (n=758) with a serum PSA of 4-20 microg/l were used to establish the risk nomograms. Of these 200 (26%) had prostate cancer at biopsy.
  
  
  RESULTS
  Prostate cancer probability depended most strongly on the percentage of free PSA. Total PSA, prostate volume, and DRE also contributed to prostate cancer probability, whereas age and family history of prostate cancer did not. More false positive PSA results could be eliminated by using the multivariate risk model rather than the percentage of free PSA (p<0.001) or PSA density (p=0.003) alone.
  
  
  CONCLUSIONS
  Wide variation in probability of detecting prostate cancer among screened men with a serum PSA of 4-20 microg/l was observed. The nomograms established can be used to avoid or defer biopsy in men with a low prostate cancer probability in spite of a serum PSA level exceeding 4 microg/l.
authors.affiliation: Department of Clinical Chemistry, Helsinki University Central Hospital, Biomedicum-Helsinki, A418a, P.O. Box 700 (Haartmaninkatu 8), FIN-00029 HUS, Finland. patrik.finne@hus.fi
authors.forename: Patrik
authors.initials: P
authors.lastname: Finne
authors.forename: Anssi
authors.initials: A
authors.lastname: Auvinen
authors.forename: Jussi
authors.initials: J
authors.lastname: Aro
authors.forename: Harri
authors.initials: H
authors.lastname: Juusela
authors.forename: Liisa
authors.initials: L
authors.lastname: Määttänen
authors.forename: Sakari
authors.initials: S
authors.lastname: Rannikko
authors.forename: Matti
authors.initials: M
authors.lastname: Hakama
authors.forename: Teuvo L J
authors.initials: TL
authors.lastname: Tammela
authors.forename: Ulf-Håkan
authors.initials: UH
authors.lastname: Stenman
mesh_terms: D000368:Aged; D014408:Biomarkers, Tumor / Q000032:analysis*; D001706:Biopsy; D005189:False Positive Reactions; D006801:Humans; D016015:Logistic Models; D008297:Male; D008403:Mass Screening; D008875:Middle Aged; D016571:Neural Networks, Computer; D010173:Palpation; D011336:Probability; D011467:Prostate / Q000473:pathology*; D017430:Prostate-Specific Antigen / Q000032:analysis*; D011471:Prostatic Neoplasms / Q000175:diagnosis*; D012007:Rectum; D012306:Risk
chemical_list: D014408:Biomarkers, Tumor; D017430:Prostate-Specific Antigen