Low Preoperative Prolactin Levels Predict Non-Organ Confined Prostate Cancer in Clinically Localized Disease.

INTRODUCTION: To evaluate the association between preoperative serum prolactin (PRL) levels and risk of non-organ confined prostate cancer (PCa) in clinically localized disease. MATERIALS AND METHODS: From December 2007 to December 2011, 124 patients with clinically localized PCa were retrospectively evaluated. Non-organ confined disease in the surgical specimen was defined according to extra-capsular extension, seminal vesicle invasion, positive surgical margins, and lymph node invasion. The association between clinical factors and serum levels of pituitary-testis hormones with the risk of non-organ confined disease was evaluated. RESULTS: Perioperative factors associated with non-organ confined disease include prostatic-specific antigen (OR 1.144; p = 0.025), proportion of biopsy positive cores (BPC, OR 36.702; p = 0.007), bioptical Gleason Score > 6 (OR 2.785; p = 0.034), and PRL (OR 0.756, p < 0.0001). The association was strong for BPC (area under the curve [AUC] 0.704; p < 0.0001) and PRL (AUC 0.299; p < 0.0001). When we dichotomized according to median value, PRL ≤7.7 µg/L was an independent predictor of extraprostatic disease (OR 6.571; p < 0.0001) with fair discrimination power (AUC 0.704; p < 0.0001). CONCLUSION: Low preoperative PRL levels predict the risk of non-organ confined PCa in clinically localized disease.

The preoperative serum ratio of total prostate specific antigen (PSA) to free testosterone (FT), PSA/FT index ratio, and prostate cancer. Results in 220 patients undergoing radical prostatectomy.

OBJECTIVES: To evaluate associations of preoperative total prostate specific antigen (PSA) to free testosterone (FT), the PSA/FT index ratio, with features of pathology prostate cancer (PCA) and to investigate its prognostic potential in clustering the PCA population. PATIENTS AND METHODS: After excluding criteria, the records of 220 patients who underwent radical prostatectomy (RP) were retrospectively reviewed. Serum samples of PSA, total testosterone (TT) and FT were collected at 8.00 A.M., one month after biopsies and before RP. The PSA/FT ratio was computed in the population of patients who were clustered in groups according to ranking intervals of the PSA/FT ratio which identified at least 4 clusters which were coded as A, B, C, and D. The independent associations of the PSA/FT index ratio were assessed by statistical methods and a two-sided P < 0.05 was considered to indicate statistical significance. RESULTS: TT correlated to FT which was a significant predictor of PSA in the population of patients who were subsequently clustered, according to increasing interval values of the PSA/FT index ratio, in groups that showed a stronger linear association of FT with PSA. The PSA/FT index ratio significantly associated with pathology features of prostate cancer such as pathology Gleason score (pGS), invasion of the seminal vesicles (pT3b), proportion of positive cores (P+) and proportion of cancer involving the volume of the prostate. In the population of patients, TT, PSA/FT index ratio and P+ independently associated with pGS ≥ 7 and pT3b; moreover, the odds ratio (OR) of the PSA/FT index ratio resulted 9.11 which was stronger than TT (OR = 1.11) and P+ (OR = 8.84). In the PCA population, TT, PSA/FT index ratio and P+ also independently associated with pT3b PCA; interestingly, the OR of PSA/FT index resulted 54.91 which was stronger than TT (OR = 1.31) and P+ (26.43). CONCLUSIONS: Preoperative PSA/FT index ratio is an independent strong factor which directly associates with aggressive features of pathology PCA; moreover, it might express prognostic potential for clustering the patient population in risk classes. Confirmatory studies are required.

Prostate cancer volume associates with preoperative plasma levels of testosterone that independently predicts high grade tumours which show low densities (quotient testosterone/tumour volume).

OBJECTIVE: To investigate potential associations of preoperative total testosterone (TT) with tumor volume (TV) and grade of prostate cancer (PCa). METHODS: Patients who were under medications impacting on the hypothalamic-pituitary-adrenal-testis-prostate axis were excluded. TT was measured preoperatively at least 1 month after biopsies and TV was calculated on the removed prostate specimen. Other continuous variables included total prostate specific antigen (PSA), percentage of positive cores (P+) and weight (W) of the removed prostate. Patients were categorized according to the pathologic Gleason score (pGS) in 3 groups (pGS 6, 7 and > 7). Invasion of the seminal vesicles was coded as seminal vesicle invasion (SVI). RESULTS: The median levels of TT were significantly and increasingly higher from pGS 6 (14.7 nmol/L) to pGS 7 (15.0 nmol/L) and pGS > 7 (18.8 nmol/L). The median values of TV were also detected significantly and increasingly higher from pGS 6 (5.6 mL) to pGS 7 (8.1 mL) and pGS > 7 (14.8 mL). The median preoperative levels of PSA were also increasing from pGS 6 (5.9 µg/L) to pGS 7 (6.2 µg/L) and pGS > 7 (7.7 µg/L). There was a significant and positive correlation of TV to PSA, TT and P+. Multiple linear regression analysis showed that TV was significantly and independently predicted by TT, PSA and P+. High grade PCa (pGS > 7) independently associated with TV, TT, P+ and SVI. The median density values of TT relative to TV (quotient TT/TV) significantly decreased from pGS 6 (2.6 nmol/L/mL) to pGS 7 (1.9 nmol/L/mL) and pGS > 7 (1.4 nmol/L/mL). The median density values of PSA relative to TV (quotient PSA/TV) also significantly decreased from pGS (1.1 µg/L/mL) to pGS 7 (0.7 µg/L/mL) and pGS > 7 (0.6 µg/L/mL). CONCLUSION: The investigation shows that TT relates to volume and grade of PCa; moreover, the density of TT relative to TV inversely associates with rate of increase of cancer that depends on the grade of the tumour.

Chronic inflammation of the prostate type IV with respect to risk of prostate cancer.

BACKGROUND: Chronic inflammatory infiltrate (CII) might be involved in prostate cancer (PCA) and benign hyperplasia (BPH); however, its significance is controversial. Chronic inflammatory prostatitis type IV is the most common non cancer diagnosis in men undergoing biopsy because of suspected PCA. OBJECTIVE: To evaluate potential associations of coexistent CII and PCA in biopsy specimens after prostate assessment. DESIGN, SETTING, AND PARTICIPANTS: Between January 2007 and December 2008, 415 consecutive patients who underwent prostate biopsy were retrospectively evaluated. The investigated variables included Age (years) and PSA (ug/l); moreover, CII+, glandular atrophy (GA+), glandular hyperplasia (GH+), prostate Intraepithelial neoplasm (PIN+), atypical small acinar cell proliferation (ASAP+) and PCA positive cores (P+) were evaluated as categorical and continuous (proportion of positive cores). OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Associations of CII+ and PCA risk were assessed by statistical methods. RESULTS AND LIMITATIONS: In the patient population, a biopsy core positive for PCA was detected in 34.2% of cases and the rate of high grade PCA (HGPCA: bGS ! 8) resulted 4.82%. CII+ significantly and inversely associated with a positive biopsy core P+ (P < 0.0001; OR = 0.26) and HGPCA (P = 0.0005; OR = 0.05). Moreover, the associations indicated that patients with coexistent CII+ on needle biopsy were 74% less likely to have coexistent PCA than men without CII+ as well as 95% less likely to have HGPCA in the biopsy core than men without coexistent CII+. There were limits in our study which was single centre and included only one dedicated pathologist. CONCLUSIONS: There was an inverse association of chronic inflammation of the prostate type IV and risk of PCA; moreover, HGPCA was less likely to be detected in cancers associated with coexistent CII. In prostate microenvironment, prostate chronic inflammation may be protective; however, its role in PCA carcinogenesis remains controversial and needs further research.

Associations of pretreatment serum total testosterone measurements with pathology-detected Gleason score cancer.

BACKGROUND AND OBJECTIVE: Prostate cancer is an endocrine-dependent tumor which is still under-investigated for physiopathology factors related to its natural history. The association of pretreatment total testosterone (TT) serum levels with prostate cancer is still a controversial topic. The objective of this study was to investigate potential associations and functional relationships of preoperative TT serum level and pathology-detected Gleason score (pGS). MATERIALS AND METHODS: Pretreatment and pathological variables of 220 patients operated with radical prostatectomy were retrospectively reviewed. Age, prostate-specific antigen (PSA), percentage of positive biopsy cores (P+), biopsy Gleason score (bGS), pGS, TT and free testosterone were the continuous variables, while clinical stage (cT: cT1c, cT2/3), biopsy Gleason pattern (bGP: ≤3+3, 3+4, >3+4), pathology Gleason pattern (pGP: ≤3+3, 3+4, >3+4), pathology stage (pT: pT2, pT3a, pT3b), pathology nodal staging (pN: pN0, pN1, pNx) and surgical margin invasion by cancer (R-, R+) were the categorical variables. Statistical methods were computed for assessing associations of TT and pGS; moreover, simple and multiple linear regression analysis (SLRA and MLRA) were used for assessing functional relationships of TT and pGS. RESULTS: High-grade tumors (pGS ≥8.0) were associated with bGS >6.0 (p < 0.0001), pGP ≥3+4 (p < 0.0001), P+ >0.31% (p = 0.006), cT2/3 (p = 0.01), TT >15.5 nmol/l (p = 0.0004) and, to a lesser extent, PSA >6.27 µg/l (p = 0.06). The odds ratio (OR) ranked as follows: 2.01 (PSA >6.27 µg/l), 2.88 (cT2/3), 3.23 (P+ >0.31%), 5.53 (TT >15.5 nmol/l) and 12.09 (pGP ≥3+4 and pGS ≥8.0). On SLRA, pGS variation was significantly predicted by bGS (p < 0.0001), P+ (p < 0.0001), PSA (p = 0.0005) and TT (p = 0.02); on MLRA, pGS variation was still significantly predicted by bGS (p < 0.0001), P+ (p = 0.04), PSA (p = 0.03) and TT (p = 0.002). When bGS, P+, PSA and TT were dichotomized to their median value, only bGS (p < 0.0001) and TT (p = 0.001) showed independence in predicting pGS variation. The best model for predicting pGS variations was by dichotomizing TT above its median (>15.5 nmol/l) because the predictive coefficient increased to 0.32, which means that patients with TT >15.5 have a significantly higher estimated risk for high-grade pGS than patients with TT ≤15.5 nmol/l (OR = 1.31). CONCLUSION: In a patient population undergoing radical prostatectomy, increased pretreatment serum measurements of TT are associated with and functionally related to high-grade pGS; moreover, baseline TT together with bGS and PSA are important factors for predicting pGS and assessing high-grade tumors. Baseline TT serum levels might have prognostic potential for assessing treatment response for continuous as well as intermittent androgen deprivation therapy.

Serum total testosterone is a significant preoperative variable independently contributing to separating the prostate cancer population into prostatectomy Gleason score groups.

AIM: To investigate the potential of preoperative serum total testosterone (TT) in contributing to the definition of separate prostatectomy Gleason score (pGS) groups of the prostate cancer (PCa) population. MATERIALS AND METHODS: The data of 220 patients operated on for PCa were retrospectively reviewed. No patient had previously received 5α-reductase inhibitor, luteinizing hormone-releasing analogs or testosterone replacement treatment. The patient population was grouped according to the pGS as 6 = 3+3, 7 = 3+4, 7 = 4+3 and 8-10. Eight variables were simultaneously investigated in each group: prostate-specific antigen (PSA), TT, free testosterone, age, percentage of positive prostate biopsy cores (P+), biopsy Gleason score (bGS), overall cancer volume estimated as percentage of prostate volume (V+) and prostate weight (Wi). Univariate analysis of variance (ANOVA), multivariate analysis of variance (MANOVA) and multivariate discriminant analysis (MDA) were the statistical methods used for evaluating the data. RESULTS: There were 89 patients in pGS 6 = 3+3, 84 in pGS 7 = 3+4, 24 in pGS 7 = 4+3 and 23 in pGS 8-10. ANOVA showed that bGS (p < 0.0001), P+ (p < 0.0001), V+ (p < 0.0001), PSA (p = 0.0001), Wi (p = 0.0002) and TT (p = 0.01) were significantly different in the four pGS groups. MANOVA tests showed that only bGS (p < 0.0001), V+ (p = 0.0003), TT (p = 0.001) and, to a lesser extent, PSA (p = 0.06) were the significant variables that individually and independently contributed a significant amount to separation of the four pGS groups of the PCa population. MDA showed that the independent variables ranked as bGS (p < 0.0001), TT (p = 0.001), V+ (p = 0.001) and PSA (p = 0.06). CONCLUSIONS: Serum TT is a significant preoperative variable that independently contributes to separating the PCa population into pGS score groups. Pretreatment baseline serum TT levels should be measured and their inclusion in neural networks predicting PCa natural history be considered in the patient population diagnosed with PCa.

Follicle-stimulating hormone and the pituitary-testicular-prostate axis at the time of initial diagnosis of prostate cancer and subsequent cluster selection of the patient population undergoing standard radical prostatectomy.

AIM: A preceding exploratory analysis has shown that follicle-stimulating hormone (FSH) was significantly correlated to and predicted by prostate-specific antigen (PSA) in a prostate cancer population. The aim of the study was to evaluate FSH physiopathology along the pituitary-testicular-prostate (PTP) axis at the time of initial diagnosis of prostate cancer in an operated population clustered according to the FSH/PSA ratio. PATIENTS AND METHODS: The study included 93 patients who underwent standard radical prostatectomy. Age, percentages of positive cores at transrectal ultrasound scan biopsy (TRUSB) (P+), biopsy Gleason score (bGS), pathology Gleason score (pGS), luteinizing hormone (LH), FSH, prolactin hormone (PRL), total testosterone (TT), free testosterone (FT), estradiol (ESR) and PSA were the continuous variables. Category variables were pT and biopsy/pathology Gleason pattern I/II (b/pGPI/II). The population was clustered according to the FSH/PSA ratio which was computed from empirical data and then ranked for clustering the population as groups A (range 0.13 ≤ FSH/PSA ≤ 0.20), B (range 0.20 < FSH/PSA ≤ 0.50), C (range 0.50 < FSH/PSA ≤ 0.75), D (range 0.75 < FSH/PSA ≤ 1.00), E (range 1.00 < FSH/PSA ≤ 1.25), F (range 1.25 < FSH/PSA ≤ 2.00), G (range 2.00 < FSH/PSA ≤ 2.25), H (range 2.25 < FSH/PSA ≤ 6.40) and I (range 6.40 < FSH/ PSA ≤ 19.40). The model was assessed by simple linear regression analysis and differences between the groups were investigated by analysis of variance (ANOVA) for continuous variables and by contingency tables for category variables. RESULTS: FSH was significantly correlated to and predicted by PSA in groups A (p = 0.04), B (p < 0.0001), C (p < 0.0001), D (p < 0.0001), E (p < 0.0001), F (p < 0.0001), G (p < 0.0001), H (p = 0.0001) and I (p = 0.001). Also, clusters (A-I) differed significantly for mean values of FSH (p < 0.0001), LH (p < 0.0001), TT (p = 0.04), PSA (p < 0.0001), bGS (p = 0.005), pGS (p = 0.01) and PSA/FT ratio (p < 0.0001); moreover, the nine groups showed significant different frequency distributions of pGPI (p = 0.02), pGPII (p = 0.0002) and bGPI (p = 0.04). CONCLUSION: The ranking FSH/PSA ratio significantly clustered, along the PTP axis, an operated population diagnosed with prostate cancer. Also, the ranking FSH/PSA ratio selected prostate cancer clusters expressing different levels of hormonal disorder along the PTP axis and prognostic potential with different risks of progression. As a theory, in the current advancing world, the ranking FSH/PSA model might be considered as an interesting and effective tool for prostate cancer study as well as individualized, risk-adapted approaches of the disease. However, confirmatory studies are needed.

Along the pituitary-testis-prostate axis, serum total testosterone is a significant preoperative variable independently contributing to separating the prostate cancer population into prostatectomy Gleason score groups.

AIM: To investigate, along the pituitary- testis- prostate axis, the potential of preoperative serum TT in contributing to defining separate prostatectomy Gleason score (pGS) groups of the prostate cancer (PC) population. MATERIALS AND METHODS: The data of 126 patients operated on for PC were retrospectively reviewed. No patient had previously received 5α-reductase inhibitor, luteinizing hormone (LH)-releasing hormone analogs or testosterone replacement treatment. The patient population was grouped according to the prostatectomy Gleason score (pGS) as 6=3+3, 7=3+4, 7=4+3 and 8-10. Twelve variables were simultaneously investigated in each group: age, prolactin (PRL), follicle stimulating hormone (FSH), LH, total testosterone (TT), free testosterone (FT), estradiol (Er), prostate specific antigen (PSA), percentage of prostate biopsy positive cores (P+), biopsy Gleason score (bGS), overall cancer volume estimated as percentage of prostate volume (V+) and prostate weight (Wi). Univariate analysis of variance (ANOVA), multivariate analysis of variance (MANOVA) and multivariate discriminant analysis were the statistical methods used for evaluating the data. RESULTS: There were 38 patients in pGS 6=3+3, 57 in pGS 7=3+4, 15 in pGS 7=4+3 and 16 in pGS 8-10. ANOVA showed that bGS (p<0.0001), P+ (p<0.0001), V+ (p<0.0001), PSA (p=0.02), Wi (p=0.001) and TT (p=0.04) were significantly different in the four pGS groups. MANOVA tests showed that only bGS (p<0.0001) and TT (p=0.005) were the significant variables that individually and independently contributed a significant amount to separation of the four pGS groups of the PC population. Multivariate discriminant analysis confirmed that TT (p=0.005) and bGS (p<0.0001) were the only variables that independently and significantly contributed to separating the pGS groups. CONCLUSION: along the pituitary- testis- prostate axis, serum TT is a significant preoperative variable that independently contributes to separating the prostate cancer population into pGS score groups. Pretreatment baseline serum TT levels should be measured for their inclusion in nomograms and future neural networks to be considered in the patient population diagnosed with PC.

Investigative clinical study on prostate cancer part IX and X: estradiol and the pituitary-testicular-prostate axis at the time of initial diagnosis and subsequent cluster selection of the patient population after radical prostatectomy.

AIM: To evaluate estradiol (E(2)) physiopathology along the pituitary-testicular-prostate axis at the time of initial diagnosis of prostate cancer (PC) and subsequent cluster selection of the patient population. PATIENTS AND METHODS: Records of the diagnosed (n=105) and operated (n=91) patients were retrospectively reviewed. Age, percentage of positive cores at-biopsy (P+), biopsy Gleason score (bGS), E(2), prolactin (PRL), luteinizing hormone (LH), follicle-stimulating hormone (FSH), total testosterone (TT), free-testosterone (FT), prostate-specific antigen (PSA), pathology Gleason score (pGS), estimated tumor volume in relation to percentage of prostate volume (V+), overall prostate weight (Wi), clinical stage (cT), biopsy Gleason pattern (bGP) and pathology stage (pT), were the investigated variables. None of the patients had previously undergone hormonal manipulations. E(2) correlation and prediction by multiple linear regression analysis (MLRA) was performed. At diagnosis, the log E(2)/log bGS ratio clustered the population into groups A (log E(2)/log bGS ≤ 2.25), B (2.25

Investigative clinical study on prostate cancer part VIII: prolactin hormone and the pituitary-testicular-prostate axis at the time of initial diagnosis and subsequent cluster selection of the patient population after radical prostatectomy.

AIM: To evaluate the prolactin hormone (PRL) physiopathology along the pituitary testicular prostate axis at the time of initial diagnosis of prostate cancer and the subsequent cluster selection of the patient population after radical prostatectomy in relation to clinical and pathological variables. PATIENTS AND METHODS: Ninety-two operated prostate cancer patients were retrospectively reviewed. No patient had previously received hormonal treatment. The investigated variables included PRL, follicle stimulating hormone (FSH), luteinizing hormone (LH), total testosterone (TT), free testosterone (FT), total prostate specific antigen (PSA), percentage of positive cores at transrectal ultrasound scan biopsy (TRUSB) (P+), biopsy Gleason score (bGS), pathology Gleason score (pGS), estimated tumor volume in relation to percentage of prostate volume (V+), overall prostate weight (Wi) and age. Empirical PRL correlations and multiple linear predictions were investigated along the pituitary testis prostate axis in the different groups of the prostate cancer population and clustered according to pT (2a/b, 3a, 3b/4) status. The patient population was classified according to the log(10) PRL/V+ ratio and clustered as follows: group A (log(10) PRL/V+ ≤1.5), B (1.5< log(10)PRL/V+ ≤2.0) and C (log(10) PRL/V+ >2.0). Simple linear regression analysis of V+ predicting PRL was computed for assessing the clustered model and analysis of variance was performed for assessing significant differences between the groups. RESULTS: PRL was independently predicted by FSH (p=0.01), LH (p=0.008) and P+ (p=0.06) in low-stage prostate cancer (pT2a/b). Interestingly, PRL was independently predicted by LH (p=0.03) and FSH, TT, FT, PSA, bGS, pGS, V+, Wi and age (all at p=0.01) in advanced stage-disease (pT3b/4). V+ was also significantly correlated (r=0.47) and predicted by P+ (p<0.0001) in the prostate cancer population. PRL was significantly correlated and predicted by V+ when the patient population was clustered according to the log(10)PRL/V+ ratio in group A (p=0.008), B (p<0.0001) and C (p<0.0001). Moreover, the three groups had significantly different mean values of PRL (p<0.0001), PSA (p=0.007), P+ (p=0.0001), V+ (p<0.0001), Wi (p=0.03), bGS (p=0.008), pGS (p=0.003); also, groups A, B and C had significant different pGS (p=0.03), pT (p=0.0008) and pR (p=0.01) frequency distributions. CONCLUSION: At diagnosis, in an operated prostate cancer population, PRL was significantly correlated and independently predicted along the pituitary testis prostate axis in high-stage disease; V+ was also significantly correlated and predicted by P+. Because of the high correlation and prediction of PRL by both V+ and P+, the prostate cancer population at diagnosis was clustered according to the log(10)PRL/V+ ratio into groups A, B and C that, in theory, might be models with prognostic potential and clinical applications in the prostate cancer population. However, confirmatory studies are needed.

Investigative clinical study on prostate cancer part VI: Follicle-stimulating hormone and the pituitary-testicular-prostate axis at the time of initial diagnosis and subsequent cluster selection of the patient population.

AIM: To evaluate the physiopathology of follicle-stimulating hormone (FSH) along the pituitary-testicular-prostate axis at the time of initial diagnosis of prostate cancer in relation to the available clinical variables and to the subsequent cluster selection of the patient population. PATIENTS AND METHODS: The study included 98 patients who were diagnosed with prostate cancer. Age, percentages of positive cores (P+) at transrectal ultrasound scan biopsy, biopsy Gleason score (bGS), luteinizing hormone (LH), FSH, total testosterone, free testosterone (FT) and prostate-specific antigen (PSA) were the continuous clinical variables. All patients had not previously received hormonal manipulations. FSH correlation and multiple linear analyses were computed in the population. The FSH/PSA ratio was computed and then ranked for clustering the population as groups A (0.13≤FSH/PSA≤0.57), B (0.57

Investigative clinical study on prostate cancer part VII: prolactin and the pituitary-testis-prostate axis at the time of initial diagnosis and subsequent cluster selection of the patient population.

AIM: To evaluate prolactin (PRL) physiopathology along the pituitary-testis-prostate axis at the time of initial diagnosis of prostate cancer in relation to the available clinical variables and to the subsequent cluster selection of the patient population. PATIENTS AND METHODS: The study involved 100 individuals diagnosed with prostate cancer. Age, percentage of positive cores at transrectal ultrasound scan biopsy (P+), biopsy Gleason score (BGS), PRL, luteinizing hormone (LH), follicle stimulating hormone (FSH), total testosterone (TT), free testosterone (FT) and prostate-specific antigen (PSA) were the continuous clinical variables. All patients had histologically proven carcinoma of the prostate and had not previously received hormonal manipulations. Correlation and multiple linear regression analysis of the the variables along the pituitary-testis-prostate cancer axis was performed. The prostate cancer population was clustered according to the PRL/P+ ratio into group A (4.20≤PRL/P+ ≤20), B (20

Investigative clinical study on prostate cancer part IV: exploring functional relationships of total testosterone predicting free testosterone and total prostate-specific antigen in operated prostate cancer patients.

OBJECTIVES: To explore, in operated prostate cancer patients, functional relationships of total testosterone (tt) predicting free testosterone (ft) and total PSA. PATIENTS AND METHODS: 128 operated prostate cancer patients were simultaneously investigated for tt, ft and PSA before surgery. Patients were not receiving 5α-reductase inhibitors, LH-releasing hormone analogues and testosterone replacement treatment. Scatter plots including ft and PSA versus tt were computed in order to assess the functional relationship of the variables. Linear regression analysis of tt predicting ft and PSA was computed. RESULTS: tt was a significant predictor of the response variable (ft) and different subsets of the patient population were assessed according to the ft to tt ratio. PSA was related to tt according to a nonlinear law. tt was a significant predictor of PSA according to an inversely nonlinear law and different significant clusters of the patient population were assessed according to the different constant of proportionality computed from experimental data. CONCLUSIONS: In our prostate cancer population, ft was significantly predicted by tt according to a linear law, and the ft/tt ratio was a significant parameter for assessing the different clusters. Also, tt was a significant variable predicting PSA by a nonlinear law and different clusters of the patient population were assessed by the different constants of proportionality. As a theory, we explain the nonlinear relation of tt in predicting PSA as follows: (a) the number of androgen-independent prostate cancer cells increases as tumor volume and PSA serum levels rise, (b) the prevalence of androgen-independent cells producing a substance which inhibits serum LH, and (c) as a result lower levels of serum tt are detected.

Investigative clinical study on prostate cancer Part V: Luteinizing hormone and the pituitary-testicular-prostate axis at the time of initial diagnosis and subsequent cluster selection of the patient population.

AIM: To evaluate Luteinizing hormone (LH) physiopathology along the pituitary testicular prostate axis at the time of initial diagnosis of prostate cancer in relation to the available clinical variables and to the subsequent cluster selection of the patient population. PATIENTS AND METHODS: Age, percentages of positive cores at Trans Rectal Ultrasound Scan Biopsy (TRUSB) (P+), biopsy Gleason score (bGS), LH, Total Testosterone (TT), Free Testosterone (FT) and Prostate Specific Antigen (PSA) were the continuous clinical variables. All patients had histologically proven carcinoma of the prostate and had not previously received 5α-reductase inhibitors, LH-releasing hormone analogues or testosterone replacement treatment. Correlation analysis was performed for the patient population. Correlation analysis, linear regression and analysis of variance was computed in groups and subgroups of the prostate cancer population. RESULTS: Correlation analysis of the patient population showed that LH was significantly correlated to age (p=0.02) and FT (p=0.01). The population was clustered in LH I (LH≤7.5 IU/l) and LH II (LH>7.5 IU/l). Correlation analysis showed significant LH correlations for TT (p<0.0001) and FT (p=0.0004) for LH I; significant LH correlation to FT (p=0.0001) for LH II. Simple linear regression showed that LH was significantly predicted by both TT (p-Value<0.0001) and FT (p-Value=0.0004) in LH I; but only FT (p-Value<0.0001) in LH II. Multiple linear regression showed that LH was significantly predicted by both TT (p-Value=0.0004) and PSA (p-Value=0.03) in LH I; but only by FT (p-Value=0.003) in LH II. Analysis of variance showed that: a) LH and age were significantly lower in LH I than II; b) LH I expressed higher mean FT levels (p=0.08) and lower mean P+ (p=0.07) than LH II. The LH versus PSA plot was computed for LH group I and 3 sub clusters were created: LH I group A (LH/PSA≤0.25), B (0.250.75). Correlation analysis showed that LH was significantly correlated to age (p=0.01), TT (p=0.03) and PSA (p=0.0004) in LH IA; LH was significantly correlated to PSA (p<0.0001) in LH IB; and LH significantly correlated to TT (p=0.005), FT (p=0.01), and PSA (p=0.008) in LH 1C. Multiple linear regression showed that LH was significantly correlated to age (p=0.02) and PSA (p=0.01) in LH IA, to TT (p=0.01) and PSA (p<0.0001) in LH IB, and to PSA (p=0.003) and weakly to TT (p=0.09) in LH IC. The groups differed significantly for mean levels of LH (p=0.0004), TT (p=0.005), FT (p=0.01), PSA (p<0.0001), bGS (p=0.003). Analysis of variance between the subgroups of the patient population (LH IA, LH IB, LH IC, LH II) showed significant differences in mean levels for LH (p<0.0001), age (p=0.004), TT (p=0.009), FT (p=0.02), PSA (p<0.0001), PSA/FT (p<0.0001), bGS (p=0.01), but not for P+ (p=0.10). CONCLUSION: According to LH physiopathology, the prostate cancer population could be clustered into hypo-gonadic and non-hypo-gonadic group at diagnosis. The hypo-gonadic group expresses an aggressive tumor phenotype and might be divided into two more different significant subsets including primary and secondary hypo-gonadic patients: the former (LH II) including older patients with high LH levels, the latter (LH IA) including younger patients with low LH and LH/PSA levels (subgroup LH IA). The non-hypo-gonadic group showed a less aggressive tumor phenotype and according to the LH/PSA ratio might beclustered into LH IB (0.250.75), the former showing a more aggressive tumor phenotype than the latter. Confirmatory studies are necessary.

Investigative clinical study on prostate cancer part III: exploring total PSA and free testosterone distributions and linear correlations in groups and subgroups of operated prostate cancer patients according to the total PSA/FT ratio.

OBJECTIVES: Prostate cancer is an interesting tumor for endocrine investigation. The prostate-specific antigen/free testosterone (PSA/FT) ratio has been shown to be effective in clustering patients in prognostic groups as follows: low risk (PSA/FT ≤0.20), intermediate risk (PSA/FT >0.20 and ≤0.40) and high risk (PSA/FT >0.40 and ≤1.5). In the present study we explored the total PSA and FT distributions, and linear regression of FT predicting PSA in the different groups (PSA/FT, pT and pG) and subgroups (pT and pG) of patients according to the prognostic PSA/FT ratio. PATIENTS AND METHODS: The study included 128 operated prostate cancer patients. Pretreatment simultaneous serum samples were obtained for measuring free testosterone (FT) and total PSA levels. Patients were grouped according to the total PSA/FT ratio prognostic clusters (≤0.20, >0.20 and ≤0.40, >0.40), pT (2, 3a and 3b+4) and pathological Gleason score (pG) (≤6, = 7 >3 + 4, ≥7 >4 + 3). The pT and pG sets were subgrouped according to the prognostic PSA/FT ratio. Linear regression analysis of FT predicting total PSA was computed according to the different PSA/FT prognostic clusters for the: (1) total sample population, (2) pT and pG groups, (3) intraprostatic (pT2) and extraprostatic disease (pT3a/3b/4), and (4) low-intermediate grade (pG ≤6) and high-grade (pG ≥7) prostate cancer. RESULTS: Analysis of variance always showed highly significant different PSA distributions for (1) the different PSA/FT, pT and pG groups; and (2) the pT and pG prognostic subgroups. Significant FT distributions were detected for the (1) PSA/FT and pT groups; and (2) the pT2, pT3a and pG ≤6 prognostic PSA/FT subgroups. Correlation, variance and linear regression analysis of FT predicting total PSA was significant for (1) the PSA/FT prognostic clusters, (2) all the pT2 and pT3a subgroups, and (3) the pT3b/4 subgroup with PSA/FT >0.20 and ≤0.40, and (4) all the pG subsets. Linear regression analysis showed that the slopes of the predicting variable (FT) were always highly significant for patients with (1) intraprostate and extraprostate disease, and (2) low-grade and high-grade prostate cancer. CONCLUSIONS: According to the prognostic PSA/FT ratio, significantly lower levels of FT are detected in prostate cancer patients with extensive and high-grade disease. Also, significant linear correlations of FT predicting PSA are assessed in the different groups and subgroups of patients clustered according to the prognostic PSA/FT ratio. Confirmatory studies are needed.

Investigative clinical study on prostate cancer part II: on the role of the pretreatment total PSA to free testosterone ratio as a marker assessing prostate cancer prognostic groups after radical retropubic prostatectomy.

OBJECTIVES: To explore the significance of the pretreatment total prostate-specific antigen (PSA) to free testosterone (FT) ratio (PSA/FT) as a marker for assessing the pathologic Gleason sum (pGS) and levels of tumor extension (pT) in prostatectomy specimens. PATIENTS AND METHODS: 128 of 135 consecutive patients diagnosed with prostate cancer underwent radical prostatectomy. Simultaneous pretreatment serum samples were obtained to measure serum total testosterone, FT and total PSA levels. The statistical design of the study included 2 sections: the first part trying to explore the role of the PSA/FT ratio in clustering patients with different pathologic prognostic factors, and the second to investigate the PSA/FT ratio distribution in different groups of patients according to the pathologic stage and pGS of the specimen after radical prostatectomy. RESULTS: The average age was 65.80 (range 51.21-77.26) years, mean PSA was 8.88 (range 1.22-44.27) µg/l, mean FT was 35.32 (range 13.70-69.30) pmol/l, and the mean PSA/FT ratio was 0.27 (range 0.04-1.48). The PSA/FT ratio significantly clustered both the pT and pGS groups. Analysis of variance for the distribution of the PSA/FT ratio was significant for the pT model groups. The mean PSA/FT ratio increased as the tumor extended and grew through the prostate gland (high-stage disease). Analysis of variance for the different distributions of the PSA/FT ratio was significant for all model pGS groups. In our investigation we also found (data not shown) that a PSA/FT ratio of ≥0.40 was strongly correlated with large extensive (pT3b+pT4) and high-grade cancers (pGS8+pGS9). CONCLUSIONS: Prostate cancer patients may be classified into 3 different pathologic prognostic groups according to the PSA/FT ratio: low risk (PSA/FT ≤0.20), intermediate risk (PSA/FT >0.20 and ≤0.40), and high risk (PSA/FT >0.40 and ≤1.5). The PSA/FT ratio may be considered as the marker expressing different biology groups of prostate cancer patients, and it is strongly associated with pT and pGS.

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.

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.