No abstract

alpha-Blockers were beneficial in the treatment of benign prostatic hyperplasia. Tolerance to treatment appeared to develop in a large proportion of patients after 6 months of therapy. However, for patients who benefit from long-term use of alpha-blockers effective treatment might be maintained for years.

The effect of Casodex (ICI 176,334), a new, once-daily, selective antiandrogen, given as 50 mg monotherapy, was compared with orchidectomy in a randomised, multicentre, open study in 376 patients with metastatic prostate cancer. At 3 months, PSA was reduced by 86% in the Casodex group and by 96% in the orchidectomy group. Treatment failed in 51 patients in the orchidectomy group and 66 showed a subjective response. Treatment failed in 86 patients treated with Casodex and 40 patients showed a subjective response. Patients treated with Casodex maintained their sexual interest better than those in the orchidectomy group. Median survival was significantly longer in the orchidectomy group. Casodex was well-tolerated. The most likely reason for the differences between the groups regarding time to treatment failure and survival is that the dose of Casodex was too small. Further studies with higher doses of Casodex are in progress.

These data indicate that computerized nuclear texture analysis as well as up regulation of sialyl Lewis(x) molecules may be new important prognostic factors in metastatic prostate cancer. Furthermore the prognostic importance of sedimentation rate, alkaline phosphatase and hemoglobin was confirmed.

A new texture operator, gray‐level entropy matrix (GLEM), was developed, and nine new textural features were extracted from this matrix. These textural features were applied to light microscopy images of nuclei taken from monolayers of advanced prostate cancer cells representing two different prognostic groups: hormone‐sensitive (good prognosis) and hormone‐resistant (poor prognosis) tumors. A comparison between the classification results obtained from GLEM features and those obtained from standard textural estimators is also discussed. Single features that gave correct classification rates better than 65% were included in a discriminant analysis in order to find the optimal set of features to discriminate between the two prognostic groups in the training data set. The best combination of features includes three GLEM features together with ENTROPY extracted from gray‐level cooccurrence matrix, and this combination gave a correct classification rate of 95% using the leaving‐one‐out technique. The influences of image sharpness and number of cells were also investigated. The features based on entropy or degree of scatter of minute structures can be used to discriminate between hormone‐sensitive and hormone‐resistant prostate carcinomas. © 1996 Wiley‐Liss, Inc.

In 224 consecutive patients with hormone-resistant prostatic cancer referred to 2 European Cancer Centres for palliation of painful bone metastases the one year survival for all patients was 24% (2-year survival: 7%). The median survival was 8 months. In univariate analyses the following prognostic factors were identified: performance status, serum creatinine, alkaline phosphatase, duration of response to primary hormone treatment, degree of bone scan involvement and hemoglobin. Multivariate analyses confirmed the four first parameters to be independent factors. A prognostic model was established (no or one risk factors vs 2 risk factors vs 3 or 4 risk factors) based on performance status, creatinine, alkaline phosphatase and hormone response duration. The median survival of these groups was 10 months, 6 months and 3 months, respectively. This model proved to be discriminative in an external data set of 214 patients with hormone-resistant prostatic cancer entered in two prospective trials. The above differences in outcome between readily and simply defined prognostic groups are greater than the differences one can realistically hope to produce using new treatment strategies. These prognostic factors should be taken into account both in the design and interpretation of clinical studies dealing with the treatment of hormone-resistant progressing prostatic cancer and painful bone metastases.

No abstract

This report describes the prognostic value of computerized nuclear texture analysis in metastatic prostate cancer. Seventy‐seven patients with histologically verified prostate carcinomas and skeletal metastases were selected from a Scandinavian multicenter study (SPCG‐2). Thirty‐six therapy‐resistant patients experienced objective progression and cancer‐related death within 2 years after orchiectomy. Thirty patients responded well to orchiectomy, i.e., showed objective disease remission and no signs of progression during 3 years of follow‐up. From this data set, 10 randomly chosen therapy‐resistant and 10 randomly chosen therapy‐sensitive carcinomas were used in our previous study to find the optimal combination of features that can discriminate between the two groups (Yogesan et al.: Cytometry 24:268–276, 1996). In addition to these two groups, 11 patients experienced stable disease or disease remission during the first year and a secondary progression during the second or third year of follow‐up, with subsequent cancer‐related death. Traditional clinical prognostic factors such as histopathological grading and serum markers could not discriminate between these groups of patients. Therefore, image analysis techniques based on texture analysis have been utilized in this study of prognosis of prostate cancer. Feulgen‐stained monolayers of nuclei were prepared from paraffin‐embedded material taken from the primary tumor before endocrine ablation. Four different textural features were selected from the training data set to calculate the discriminating function. This function separated the therapy‐sensitive and the therapy‐resistant patients with 87% accuracy in the independent data set. This study demonstrates that it is possible to predict tumor progression and survival for endocrine‐ablated metastatic prostate carcinomas using computerized nuclear texture analysis on light microscopy images from prostate biopsies taken at the time of diagnosis. © 1996 Wiley‐Liss, Inc.