title: Combination of prostate-specific antigen, clinical stage, and Gleason score to predict pathological stage of localized prostate cancer. A multi-institutional update.
abstract: OBJECTIVE
  To combine the clinical data from 3 academic institutions that serve as centers of excellence for the surgical treatment of clinically localized prostate cancer and develop a multi-institutional model combining serum prostate-specific antigen (PSA) level, clinical stage, and Gleason score to predict pathological stage for men with clinically localized prostate cancer.
  
  
  METHODS
  In this update, we have combined clinical and pathological data for a group of 4133 men treated by several surgeons from 3 major academic urologic centers within the United States. Multinomial log-linear regression was performed for the simultaneous prediction of organ-confined disease, isolated capsular penetration, seminal vesicle involvement, or pelvic lymph node involvement. Bootstrap estimates of the predicted probabilities were used to develop nomograms to predict pathological stage. Additional bootstrap analyses were then obtained to validate the performance of the nomograms.
  
  
  METHODS
  A total of 4133 men who had undergone radical retropubic prostatectomy for clinically localized prostate cancer at The Johns Hopkins Hospital (n=3116), Baylor College of Medicine (n=782), and the University of Michigan School of Medicine (n=235) were enrolled into this study. None of the patients had received preoperative hormonal or radiation therapy.
  
  
  METHODS
  Simultaneous prediction of organ-confined disease, isolated capsular penetration, seminal vesicle involvement, or pelvic lymph node involvement using updated nomograms.
  
  
  RESULTS
  Prostate-specific antigen level, TNM clinical stage, and Gleason score contributed significantly to the prediction of pathological stage (P<.001). Bootstrap estimates of the median and 95% confidence interval of the predicted probabilities are presented in the nomograms. For most cells in the nomograms, there is a greater than 25% probability of qualifying for more than one of the pathological stages. In the validation analyses, 72.4% of the time the nomograms correctly predicted the probability of a pathological stage to within 10% (organ-confined disease, 67.3%; isolated capsular penetration, 59.6%; seminal vesicle involvement, 79.6%; pelvic lymph node involvement, 82.9%).
  
  
  CONCLUSIONS
  The data represent a multi-institutional modeling and validation of the clinical utility of combining PSA level measurement, clinical stage, and Gleason score to predict pathological stage for a group of men with localized prostate cancer. Clinicians can use these nomograms when counseling individual patients regarding the probability of their tumor being a specific pathological stage; this will enable patients and physicians to make more informed treatment decisions based on the probability of a pathological stage, as well as risk tolerance and the values they place on various potential outcomes.
authors.affiliation: Department of Urology, Johns Hopkins Hospital, Baltimore, Md, 21287-2101, USA.
authors.forename: A W
authors.initials: AW
authors.lastname: Partin
authors.forename: M W
authors.initials: MW
authors.lastname: Kattan
authors.forename: E N
authors.initials: EN
authors.lastname: Subong
authors.forename: P C
authors.initials: PC
authors.lastname: Walsh
authors.forename: K J
authors.initials: KJ
authors.lastname: Wojno
authors.forename: J E
authors.initials: JE
authors.lastname: Oesterling
authors.forename: P T
authors.initials: PT
authors.lastname: Scardino
authors.forename: J D
authors.initials: JD
authors.lastname: Pearson
mesh_terms: D003661:Decision Support Techniques; D006801:Humans; D008207:Lymphatic Metastasis; D008297:Male; D015999:Multivariate Analysis; D009361:Neoplasm Invasiveness; D009367:Neoplasm Staging / Q000379:methods; D011336:Probability; D017430:Prostate-Specific Antigen / Q000032:analysis*; D011468:Prostatectomy; D011471:Prostatic Neoplasms / Q000276:immunology / Q000473:pathology*; D012044:Regression Analysis; D012680:Sensitivity and Specificity
chemical_list: D017430:Prostate-Specific Antigen