title: Integrated predictive model for prostatic cancer using clinical, laboratory and ultrasound data.
abstract: OBJECTIVE
  to develop a predictive model to estimate the probability of prostate cancer prior to biopsy.
  
  
  METHODS
  from September 2009 to January 2014, 445 men underwent prostate biopsy in a radiology service. We excluded from the study patients with diseases that could compromise the data analysis, who had undergone prostatic resection or used 5-alpha-reductase inhibitors. Thus, we selected 412 patients. Variables included in the model were age, prostate specific antigen (PSA), digital rectal examination, prostate volume and abnormal sonographic findings. We constructed Receiver Operating Characteristic (ROC) curves and calculated the areas under the curve, as well as the model's Positive Predictive Value (PPV) .
  
  
  RESULTS
  of the 412 men, 155 (37.62%) had prostate cancer (PC). The mean age was 63.8 years and the median PSA was 7.22ng/ml. In addition, 21.6% and 20.6% of patients had abnormalities on digital rectal examination and image suggestive of cancer by ultrasound, respectively. The median prostate volume and PSA density were 45.15cm3 and 0.15ng/ml/cm3, respectively. Univariate and multivariate analyses showed that only five studied risk factors are predictors of PC in the study (p<0.05). The PSA density was excluded from the model (p=0.314). The area under the ROC curve for PC prediction was 0.86. The PPV was 48.08% for 95%sensitivity and 52.37% for 90% sensitivity.
  
  
  CONCLUSIONS
  the results indicate that clinical, laboratory and ultrasound data, besides easily obtained, can better stratify the risk of patients undergoing prostate biopsy.
authors.affiliation: Department of Surgery, Federal University of Santa Catarina, Florianópolis, Santa Catarina, Brazil.
authors.forename: Gustavo David
authors.initials: GD
authors.lastname: Ludwig
authors.affiliation: Department of Surgery, Federal University of Santa Catarina, Florianópolis, Santa Catarina, Brazil.
authors.forename: Henrique Peres
authors.initials: HP
authors.lastname: Rocha
authors.affiliation: Department of Public Health, Federal University of Santa Catarina, Florianópolis, Santa Catarina, Brazil.
authors.forename: Lúcio José
authors.initials: LJ
authors.lastname: Botelho
authors.affiliation: Department of Public Health, Federal University of Santa Catarina, Florianópolis, Santa Catarina, Brazil.
authors.forename: Maiara Brusco
authors.initials: MB
authors.lastname: Freitas
mesh_terms: D001706:Biopsy; D005544:Forecasting; D006801:Humans; D008297:Male; D008875:Middle Aged; D008962:Models, Theoretical; D011237:Predictive Value of Tests; D017430:Prostate-Specific Antigen; D011471:Prostatic Neoplasms / Q000175:diagnosis*; D014463:Ultrasonography
chemical_list: D017430:Prostate-Specific Antigen