Comparative analysis of whole mount processing and systematic sampling of radical prostatectomy specimens: pathological outcomes and risk of biochemical recurrence

Abstract

Purpose: Whole mount processing is more resource intensive than routine systematic sampling of radical retropubic prostatectomy specimens. We compared whole mount and systematic sampling for detecting pathological outcomes, and compared the prognostic value of pathological findings across pathological methods.

Materials and methods: We included men (608 whole mount and 525 systematic sampling samples) with no prior treatment who underwent radical retropubic prostatectomy at Vanderbilt University Medical Center between January 2000 and June 2008. We used univariate and multivariate analysis to compare the pathological outcome detection rate between pathological methods. Kaplan-Meier curves and the log rank test were used to compare the prognostic value of pathological findings across pathological methods.

Results: There were no significant differences between the whole mount and the systematic sampling groups in detecting extraprostatic extension (25% vs 30%), positive surgical margins (31% vs 31%), pathological Gleason score less than 7 (49% vs 43%), 7 (39% vs 43%) or greater than 7 (12% vs 13%), seminal vesicle invasion (8% vs 10%) or lymph node involvement (3% vs 5%). Tumor volume was higher in the systematic sampling group and whole mount detected more multiple surgical margins (each p <0.01). There were no significant differences in the likelihood of biochemical recurrence between the pathological methods when patients were stratified by pathological outcome.

Conclusions: Except for estimated tumor volume and multiple margins whole mount and systematic sampling yield similar pathological information. Each method stratifies patients into comparable risk groups for biochemical recurrence. Thus, while whole mount is more resource intensive, it does not appear to result in improved detection of clinically important pathological outcomes or prognostication.