The role of volume-weighted mean nuclear volume in predicting disease outcome in patients with prostate cancer treated with radical prostatectomy

Background. Estimates of volume-weighted mean nuclear volume (MNV) are the only means by which unbiased estimates of three-dimensional parameters can be obtained from single two-dimensional sections without any assumptions. W e have reported that for prostate cancer estimates of MNV are prognosticall y equal or superior to morphological grading of malignancy, such as Gleason score (GS), and in particular, that MNV proved to be a meaningful predicto r of prognosis for patients with clinically localized tumors. However, all previous studies were conducted on patients treated conservatively, and no authors have tested whether estimates of MNV can predict the prognosis of p atients treated with radical prostatectomy. Materials and methods. A retros pective prognostic study of 52 patients with clinically localized prostate cancer diagnosed at three Hospitals in Shizuoka Prefecture, Japan (Shizuoka City Hospital, Shizuoka Prefectural Hospital and Shimada Municipal Hospita l) and treated by radical prostatectomy was performed. Twenty of these pati ents were treated with hormone therapy before radical prostatectomy. Unbias ed estimates of MNV were compared with clinical stage, histological grading according to GS and neo-adjuvant hormone therapy with regard to the progno stic value. Results. MNV was significantly correlated with pathologcial T s tage, but was not significantly correlated with the presence or absence of lymph node metastasis. Univariate analysis revealed that MNV correlated sig nificantly with progression-free survival (p=0.0116). Multivariate analysis revealed that MNV (p=0.0115) and GS (p=0.0275) were two significant indepe ndent predictors of progression-free survival. Conclusions. The results of the present study suggest that MNV and GS are powerful independent predicto rs of prognosis for prostate cancer treated with radical prostatectomy. We recommend estimates of MNV as a supportive method to the histological gradi ng for patients with prostate cancer.