Literature DB >> 19902378

Investigative clinical study on prostate cancer: on the role of the pretreatment total PSA to free testosterone ratio in selecting different biology groups of prostate cancer patients.

Antonio B Porcaro1, Filippo Migliorini, Mario Romano, Aldo Petrozziello, Stefano Zecchini Antoniolli, Emanuele Rubilotta, Vincenzo Lacola, Teodoro Sava, Claudio Ghimenton, Beatrice Caruso, Carmelo Monaco, Luigi Comunale.   

Abstract

OBJECTIVES: To show that prostate cancer biology is related to serum levels of both free testosterone (FT) and prostate-specific antigen (PSA), that PSA level is linearly related to FT and that the PSA to FT ratio may be considered as the growth rate parameter expressing cancer phenotype biology.
MATERIALS AND METHODS: The study includes 135 consecutive patients diagnosed with prostate cancer. Pretreatment simultaneous serum samples for analyzing total testosterone (TT), FT and total PSA levels were obtained. The study was assessed according to a multidimensional approach of the five continuous variables including TT, FT, PSA, AGE and percentage of positive biopsies (=P+). The all sets of data were considered as one--sample with no groupings among the observations. Multivariate analysis included factor analysis (FA) and principal component analysis (PCA). Multivariate inferential statistics for comparing different groups of patients according to the PSA to free testosterone ratio (PSA/FT) included Hotteling's multivariate two-sample T²-Test for comparing two mean vectors as well as Box's M-Test with the chi-square approximation for comparing multiple covariance matrices when patients were sampled in more than two groups.
RESULTS: Factor analysis showed the two natural grouping of variables, FT-TT and PSA-P+. PCA assessed FT and PSA as the two variables with large variances having a notable influence on the first two principal components. Multiple linear regression analysis showed that all the income variables, except age, significantly predicted the PSA/FT ratio. Patients were first sampled according to the PSA/FT ratio in group 1 (PSA/FT ≤ 0.20) and group 2 (PSA/FT > 0.20), and Hotteling's multivariate two sample T²-Test was significant (P < 0.01). Patients were then sampled according to the PSA/FT ratio in group 1 (PSA/FT ≤ 0.20), group 2 (PSA/FT > 0.20 and ≤ 0.40), and group 3 (PSA/FT > 0.40), and Box's M-Test comparing the covariance matrices of the 3 groups differed significantly (P < 0.001). Finally, patients were sampled according to the PSA/FT ratio in 6 groups, and Box's M-Test was again significant (P < 0.001).
CONCLUSIONS: The PSA to FT ratio is the growing rate parameter expressing different biology patterns and assessing different groups of prostate cancer patients. In our opinion, the results of the present study might have wide applications in understanding, assessing and planning prostate cancer studies including basic science, screening, assessing risk of the disease, predicting disease stage as well natural history after a planned treatment involving biochemical recurrence, progression, hormone refractory prostate cancer and disease-specific survival.

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Year:  2009        PMID: 19902378     DOI: 10.1007/s11255-009-9669-z

Source DB:  PubMed          Journal:  Int Urol Nephrol        ISSN: 0301-1623            Impact factor:   2.370


  33 in total

1.  Pretreatment serum testosterone level as a predictive factor of pathological stage in localized prostate cancer patients treated with radical prostatectomy.

Authors:  Takashi Imamoto; Hiroyoshi Suzuki; Satoshi Fukasawa; Masaki Shimbo; Masahiko Inahara; Akira Komiya; Takeshi Ueda; Taizo Shiraishi; Tomohiko Ichikawa
Journal:  Eur Urol       Date:  2004-12-29       Impact factor: 20.096

2.  The endocrine profiles in men with localized and locally advanced prostate cancer treated with radical prostatectomy.

Authors:  Jiri Heracek; Michael Urban; Jana Sachova; Jitka Kuncova; Vaclav Eis; Vaclav Mandys; Richard Hampl; Luboslav Starka
Journal:  Neuro Endocrinol Lett       Date:  2007-02       Impact factor: 0.765

3.  Prostate-specific antigen as a serum marker for adenocarcinoma of the prostate.

Authors:  T A Stamey; N Yang; A R Hay; J E McNeal; F S Freiha; E Redwine
Journal:  N Engl J Med       Date:  1987-10-08       Impact factor: 91.245

4.  Predictive criteria for prostate cancer detection in men with serum PSA concentration of 2.0 to 4.0 ng/mL.

Authors:  Sergey Kravchick; Ronit Peled; Dov Dorfman; Leonid Agulansky; David Ben-Dor; Shmuel Cytron
Journal:  Urology       Date:  2005-09       Impact factor: 2.649

5.  Occult prostate cancer in men with low serum testosterone levels.

Authors:  A Morgentaler; C O Bruning; W C DeWolf
Journal:  JAMA       Date:  1996-12-18       Impact factor: 56.272

6.  Low serum testosterone and a younger age predict for a poor outcome in metastatic prostate cancer.

Authors:  M Ribeiro; P Ruff; G Falkson
Journal:  Am J Clin Oncol       Date:  1997-12       Impact factor: 2.339

7.  The correlation between pretreatment serum hormone levels and treatment outcome for patients with prostatic cancer and bony metastasis.

Authors:  S S Chen; K-K Chen; A T L Lin; Y-H Chang; H H Wu; L S Chang
Journal:  BJU Int       Date:  2002-05       Impact factor: 5.588

8.  Serum testosterone--a significant determinant of metastatic relapse for irradiated localized prostate cancer.

Authors:  G K Zagars; A Pollack; A C von Eschenbach
Journal:  Urology       Date:  1997-03       Impact factor: 2.649

9.  The correlation between serum prostate-specific antigen and prostate cancer is not influenced by the serum testosterone concentration.

Authors:  J M Monda; R P Myers; D G Bostwick; J E Oesterling
Journal:  Urology       Date:  1995-07       Impact factor: 2.649

10.  Low testosterone and risk of biochemical recurrence and poorly differentiated prostate cancer at radical prostatectomy.

Authors:  Brian R Lane; Andrew J Stephenson; Cristina Magi-Galluzzi; Milton M Lakin; Eric A Klein
Journal:  Urology       Date:  2008-08-09       Impact factor: 2.649

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  2 in total

1.  Predicting prostate biopsy outcome: artificial neural networks and polychotomous regression are equivalent models.

Authors:  Nathan Lawrentschuk; Gina Lockwood; Peter Davies; Andy Evans; Joan Sweet; Ants Toi; Neil E Fleshner
Journal:  Int Urol Nephrol       Date:  2010-05-13       Impact factor: 2.370

2.  Plasma cell-free DNA and its DNA integrity as biomarker to distinguish prostate cancer from benign prostatic hyperplasia in patients with increased serum prostate-specific antigen.

Authors:  Jiang Feng; Feng Gang; Xiao Li; Tang Jin; Huang Houbao; Cao Yu; Li Guorong
Journal:  Int Urol Nephrol       Date:  2013-06-19       Impact factor: 2.370

  2 in total

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