The adrenal glands produce significant amounts of steroid hormones and their metabolites, with various levels of androgenic activities. Until recently, the androgenic potency of these adrenal-derived compounds were not well known, but some recent studies have shown that the production of 11-oxoand 11β-hydroxy-derived testosterone and dihydrotestosterone evidently have high androgenic activity. This fact has clinical importance, for instance, in various types of congenital adrenal hyperplasia with androgenization or polycystic ovarian syndrome, and laboratory determinations of these substances could help to better evaluate the total androgen pressure in patients with these disorders. Another area of concern is the treatment of prostate cancer with androgen deprivation, which loses effectiveness after a certain time. The concurrent blocking of the secretion of adrenal C19-steroids, whether using corticoids or adrenostatics, could increase the effectiveness of androgen-deprivation therapy., Luboslav Stárka, Michaela Dušková, Jana Vítků., and Obsahuje bibliografii
Serum levels of adiponectin were measured in patients with benign prostatic hyperplasia and prostate cancer of pT2 and pT3 stage. Adiponectin ELISA assay, immunohistochemistry, and selected metabolic and biochemical parameters measurement was performed in 25 patients with benign prostatic hyperplasia and 43 with prostate cancer (17 patients with organ-confined and 26 patients with locally advanced disease). Serum adiponectin levels did not differ between prostate benign hyperplasia and cancer clinical stage T2, but was significantly higher in pT3 relative to pT2 group (14.51± 4.92 vs. 21.41±8. 12, P = 0.003). Tissue immunohistochemistry showed enhanced staining in neoplastic prostate glands and intraepithelial neoplasia relative to benign prostatic hyperplasia without distinction between disease grade and stage. Serum adiponectin levels are higher in locally advanced relative to organ-confined prostate cancer and may thus serve as an auxiliary marker providing further improvement for discrimination between pT2 and pT3 stages., D. Housa, Z. Vernerová, J. Heráček, B. Procházka, P. Čechák, J. Kuncová, M. Haluzík., and Obsahuje bibliografii a bibliografické odkazy
Introduction: The dataset of 826 patients who were suspected of the prostate cancer was examined. The best single marker and the combination of markers which could predict the prostate cancer in very early stage of the disease were looked for. Methods: For combination of markers the logistic regression, the multilayer perceptron neural network and the k-nearest neighbour method were used. 10 models for each method were developed on the training data set and the predictive accuracy verified on the test data set. Results and conclusions: The ROCs for the models were constructed and AUCs were estimated. All three examined methods have given comparable results. The medians of estimates of AUCs were 0.775, which were larger than AUC of the best single marker.