Independent diagnostic and post-treatment prognostic models for prostate cancer demonstrate significant correlation with disease progression end points

• Published in: Journal of endourology Vol. 26; no. 5; p. 451
• Main Authors: Graversen, Joseph A, Suh, Lara K, Mues, Adam C, Korets, Ruslan, Donovan, Michael J, Khan, Faisal M, Liu, Qiuhua, Landman, Jaime, Gupta, Mantu, McKiernan, James M, Badani, Ketan K
• Format: Journal Article
• Language: English
• Published: United States 01-05-2012
• Subjects: Adult; Aged; Aged, 80 and over; Biopsy; Cohort Studies; Disease Progression; Endpoint Determination; Humans; Male; Middle Aged; Models, Biological; Postoperative Care; Preoperative Care; Prognosis; Prostate - pathology; Prostatectomy; Prostatic Neoplasms - diagnosis; Prostatic Neoplasms - pathology; Prostatic Neoplasms - surgery; Prostatic Neoplasms - therapy
• ISSN: 1557-900X
• DOI: 10.1089/end.2011.0192

A major advance in the standard practice of tissue-based pathology is the new discipline of systems pathology (SP) that uses computational modeling to combine clinical, pathologic, and molecular measurements to predict biologic activity. Recently, a SP-based prostate cancer (PCa) predictive model for both preoperative (Px+) and postoperative (Px) prostatectomy has been developed. The purpose of this study is to calculate the percent agreement and the concordance between the Px+ and Px end points.
Fifty-three patients underwent robot-assisted prostatectomy for PCa, and had Px+ and Px testing performed. Data were collected on Px+ end points and Px end points along with pathologic specimen results. The percent agreement and the degree of correlation between the Px+ and Px end points were then calculated.
The percent agreement (PA) between Px+ end points and Px end points ranged from 77% to 87%. The PA between a high Px+ favorable pathology (FP) classification and dominant Gleason score ≤ 3 and Gleason sum ≤ 6 was 71.7% and 37.4%, respectively. On univariate analysis, Px+ disease progression (DP) score significantly correlated with Px prostate-specific antigen recurrence (PSAR) score (P<0.001), while Px+ DP probability significantly correlated with PxPSAR probability (P<0.001). Px+ FP probability significantly correlated with postprostatectomy dominant Gleason grade ≤ 3 (P<0.001) and Gleason sum (P<0.001).
The PA between Px+ and Px testing end points for radical prostatectomy patients was very good. Furthermore, there was a direct correlation between most Px+ and Px end points. While the Px+FP classification and Gleason sum demonstrated a poor PA, Px+FP score still maintained a direct correlation to prostatectomy Gleason sum.