Neoadjuvant Hormone Therapy Before Radical Prostatectomy: Update on the Memorial Sloan-Kettering Cancer Center Trials.

We report here the latest follow-up of the Phase II and III trials evaluating pathologic results and relapse-free survival, as judged by serum prostate specific antigen (PSA), in patients with localized prostate cancer who had radical prostatectomy performed at the Memorial Sloan-Kettering Center (MSKCC) either with or without neoadjuvant hormone therapy (NHT). Pelvic lymphadenectomy (PLND), radical prostatectomy, or both with or without NHT was performed in 141 patients enrolled in a Phase II trial comparing patients receiving NHT with concurrent controls and 140 patients in a randomized Phase III trial. In the Phase II study, there was a significant difference in the pathologic results, with only 35 (49%) of the 72 patients in the control group having organ-confined margin-negative disease compared with 48 (70%) of the 69 patients in the NHT arm (P = 0.0057; chi(2) test). With a median follow-up of 57 months, there was no significant difference in the PSA relapse rates in the two arms (P = 0.92; log-rank test). In the Phase III study, 39 (59%) of the 66 patients in the control arm had organ-confined margin-negative disease compared with 52 (70%) of the 74 patients in the NHT arm (P = 0.17; chi(2) test). However, the positive-margin rate was significantly lower in the NHT arm (19%) than in the control arm (37%) (P = 0.023; chi(2) test). With a median follow-up of 35 months, there was no significant difference in the PSA relapse rates in the two arms (P = 0.73; log-rank test). Thus, although NHT improves the pathologic results, further follow-up is necessary to determine if this marked reduction in the positive-margin rate will translate into improved disease-free survival.

Progress in Two-Dimensional and Three-Dimensional Ultrasonic Tissue-Type Imaging of the Prostate Based on Spectrum Analysis and Nonlinear Classifiers.

Spectrum analysis of radiofrequency (RF) ultrasonic echo signals often can sense tissue differences that are not visible on conventional ultrasonic images. Spectrum-analysis parameter values combined with other variables, such as serum prostate specific antigen (PSA) concentration, can be classified by neural networks to distinguish effectively between cancerous and noncancerous prostate tissues. Images based on neural network classification of spectral parameters and clinical variables can be advantageous for biopsy guidance, staging, and treatment planning and monitoring. A study based on 644 biopsies from 137 patients showed that these methods are significantly superior to B-mode image interpretation for differentiating cancerous from noncancerous prostate tissues. Using the histologic determination of tissue types as the gold standard, the area under the receiver-operator characteristic (ROC) curve for neural network classification based on spectrum analysis and PSA value for the 644 biopsies was 0.87 +/- 0.04, and the ROC curve are for a level-of-suspicion (LOS) assignment based on B-mode imaging was 0.64 +/- 0.04. Color-encoded and gray-scale images derived from neural network assignment of suspicion for cancer at each pixel location showed remarkable detail and suggested potential clinical value for biopsy guidance using real-time two-dimensional (2D) images and staging, treatment planning, and monitoring using three-dimensional (3D) images.