Risk stratification after radical prostatectomy in men with pathologically organ-confined prostate cancer using volume-weighted mean nuclear volume.

Objective: We examined the impact of volume-weighted mean nuclear volume (MNV) on biochemical failure after radical prostatectomy (RP) in pathologically organ-confined prostate cancer (PC) and developed a prognostic factor-based stratification model for these patients.

Patients And Methods: We analyzed 141 patients with pathologically organ-confined PC treated solely with RP. Unbiased estimates of MNV were calculated from biopsy specimens based on a stereological method, and compared with other clinical and pathologic findings including patient age, pre-treatment PSA, biopsy and RP specimen Gleason score, pathologic stage, total cancer volume, index cancer volume, tumor differentiation, number of tumor foci, main tumor location, and surgical margin status, with regard to prediction of disease outcome after RP using Cox proportional hazard models.

Risk factors for subsequent development of bladder cancer after primary transitional cell carcinoma of the upper urinary tract.

Objectives: To determine the independent risk factors for intravesical tumor recurrence in patients with primary transitional cell carcinoma of the upper urinary tract, and to develop a risk-stratification model to allow more accurate prediction of recurrence risk.

Methods: Of 141 patients who underwent total nephroureterectomy for clinically localized transitional cell carcinoma of the upper urinary tract, the data from 89 patients were retrospectively reviewed. Patients with a previous history or concomitance of bladder cancer and/or a follow-up period of less than 1 year were excluded from this study.

Spontaneous rupture of varicocele testis associated with advanced pancreatic cancer.

We report a rare case of strain-induced spontaneous rupture of varicocele associated with renal vein involvement by advanced pancreatic cancer. Computed tomography and color Doppler sonography yielded the correct diagnosis and the patient could maintain quality of life without surgery for acute scrotum.

The use of artificial neural network analysis to improve the predictive accuracy of prostate biopsy in the Japanese population.

Objective: We examined the efficacy of an artificial neural network analysis (ANNA) based on parameters available from previously existing examinations for improving the predictive accuracy of prostate cancer screening in the Japanese population.

Methods: Two hundred and twenty-eight patients with prostate-specific antigen (PSA) of 2-10 ng/ml were enrolled in this study. Two artificial neural network analysis (ANNA) models were constructed: ANNA1 with patient age, total PSA, free to total PSA ratio, prostate volume, transition zone volume (TZ), PSA density (PSAD) and PSA-TZ density (PSATZ) as input variables, and ANNA2 with presumed circle area ratio (PCAR), digital rectal examination (DRE) findings and chief complaint added as variables.