Prognostic value of tumor volume for biochemical recurrence of prostate cancer remains controversial. We aimed to determine which tumor volume definition would optimally correlate with established prognostic factors and classify macroscopic tumor configuration. Radical prostatectomy specimens with follow-up to biochemical recurrence in the period between 2009 and 2012 were retrieved. Newly proposed categories of reconstructed three-dimensional macroscopic tumor configuration were nodular, medial prominence, subcapsular spreading, and miliary types. Several algorithms were applied to identify optimal tumor volume including (1) combined volume of all nodules, (2) volume of largest nodule as index tumor, and (3) volume of nodule with strongest evidence of poor prognosis. Macroscopic typing correlated well with radiologic findings, and nodular type was most common (70.7 %). In most multifocal tumors, the largest nodule showed the highest Gleason score (90.8 %) as well as extraprostatic extension or seminal vesicle invasion (93.5 %). Total tumor and index tumor volumes were significant predictors of biochemical recurrence (both, P < 0.0001). Tumor volume, classified in three groups with cutoff values at 2 and 5 cm3, was independently predictive of recurrence-free survival in multivariate analysis (P < 0.05) and surpassed bilaterality even in stage pT2. In pT2 disease, recurrence-free survival was significantly associated with total tumor volume (P = 0.003) and index tumor volume (P = 0.002), but not with pT2 substage (P = 0.278). The proposed macroscopic classification system can be correlated with preoperative imaging findings. Total tumor or index tumor volume significantly predicts biochemical recurrence. Tumor volume classification is easy to apply in practice with high reproducibility and offsets the limitations of pT classification.
Bibliographical noteFunding Information:
This study was supported by the Korean Foundation for Cancer Research and by a grant from the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health & Welfare, Republic of Korea (grant number HI13C0858).
© 2016, Springer-Verlag Berlin Heidelberg.
All Science Journal Classification (ASJC) codes
- Pathology and Forensic Medicine
- Molecular Biology
- Cell Biology