Mass Prostate-specific Antigen Research Articles

Mortality reduction and cumulative excess incidence (CEI) in the prostate-specific antigen (PSA) screening era

The extent to which PSA screening is related to prostate cancer mortality reduction in the United States (US) is controversial. US Surveillance, Epidemiology, and End Results Program (SEER) data from 1980 to 2016 were examined to assess the relationship between prostate cancer mortality and cumulative excess incidence (CEI) in the PSA screening era and to clarify the impact of race on this relationship. CEI was considered as a surrogate for the intensity of prostate cancer screening with PSA testing and subsequent biopsy as appropriate. Data from 163,982,733 person-years diagnosed with 544,058 prostate cancers (9 registries, 9% of US population) were examined. Strong inverse linear relationships were noted between CEI and prostate cancer mortality, and 317,356 prostate cancer deaths were avoided. Eight regions of the US demonstrated prostate cancer mortality reduction of 46.0–63.7%. On a per population basis, the lives of more black men than white men were saved in three of four registries with sufficient black populations for comparison. Factor(s) independent of CEI (potential effects of treatment advances) explained 14.6% of the mortality benefit (p-value = 0.3357) while there was a significant main effect of CEI (effect = −0.0064; CI: [−0.0088, −0.0040]; p-value < 0.0001). Therefore, there is a strong relationship between CEI and prostate cancer mortality reduction that was not related to factors independent of screening utilization. Minority populations have experienced large mortality reductions in the context of PSA mass utilization.

Exploration of the diagnostic capacity of PSAMR combined with PI-RADS scoring for clinically significant prostate cancer and establishment and validation of the Nomogram prediction model.

The objective of this investigation was to explore the diagnostic capability of Prostate Specific Antigen Mass Ratio (PSAMR) combined with Prostate Imaging Reporting and Data System (PI-RADS) scoring for clinically significant prostate cancer (CSPC), develop and validate a Nomogram prediction model for the probability of prostate cancer occurrence in patients who have not undergone prostate biopsy. Initially, we retrospectively collected clinical and pathological data of patients who underwent trans-perineal prostate puncture at Yijishan Hospital of Wanan Medical College from July 2021 to January 2023. Through logistic univariate and multivariate regression analysis, independent risk factors for CSPC were determined. Receiver Operating Characteristic (ROC) curves were generated to compare the ability of different factors for diagnosis of CSPC. Then, we split the dataset into a training set and validation set, compared their heterogeneity, and developed a Nomogram prediction model based on the training set. Finally, we validated the Nomogram prediction model in terms of discrimination, calibration, and clinical usefulness. Logistic multivariate regression analysis illustrated that age [64-69 (OR = 2.736, P = 0.029); 69-75 (OR = 4.728, P = 0.001); > 75 (OR = 11.344, P < 0.001)], PSAMR [0.44-0.73 (OR = 4.144, P = 0.028); 0.73-1.64(OR = 13.022, P < 0.001); > 1.64(OR = 50.541, P < 0.001)], and PI-RADS score [4 points (OR = 7.780, P < 0.001); 5 points (OR = 24.533, P < 0.001)] were independent risk factors for CSPC. The Area Under the Curve (AUC) of the ROC curves of PSA, PSAMR, PI-RADS score, and PSAMR combined with PI-RADS score were respectively 0.797, 0.874, 0.889, and 0.928. The performance of PSAMR and PI-RADS score for diagnosis of CSPC was superior to PSA, but inferior to PSAMR combined with PI-RADS. Age, PSAMR, and PI-RADS were included in the Nomogram prediction model. The AUCs of the training set ROC curve and the validation set ROC curve were 0.943 (95% CI 0.917-0.970) and 0.878 (95% CI 0.816-0.940), respectively, in the discrimination validation. The calibration curve showed good consistency, and the decision analysis curve suggested the model had good clinical efficacy. We found that PSAMR combined with PI-RADS scoring had a strong diagnostic capability for CSPC, and provided a Nomogram prediction model to predict the probability of prostate cancer occurrence combined with clinical data.

Machine Learning Algorithms for Predicting High-Risk of Prostate Cancer Using Prostate-Specific Antigen (PSA), Age and Body Mass Index (BMI)

Machine Learning Algorithms for Predicting High-Risk of Prostate Cancer Using Prostate-Specific Antigen (PSA), Age and Body Mass Index (BMI)

Cost-benefit analysis of a population-based prostate-specific antigen mass testing for early detection of prostate cancer in Anambra State, Nigeria: A health provider's perspective

Aims: We conducted a cost-benefit analysis of a population-based prostate-specific antigen (PSA) mass testing for prostate cancer (PCa) from a provider’s perspective to give further insights into the programme’s sustainability at scale-up. Materials and Methods: A cross-sectional study design was adopted. The cost and benefit of the population-based-specific antigen mass testing were estimated using activity-based costing and participants’ willingness to pay (WTP), respectively. The study was conducted in a primary health-care facility in Anambra State, Nigeria. A total of 412 asymptomatic males between 40 and 74 years who had not had a PSA screening within the past five years were recruited for the study. A one-month population-based PSA mass screening for PCa was performed at the primary health-care facility. The cost of population-based PSA mass testing was presented as cost/male screened while benefit was measured as the participants’ minimum WTP analysis amount. Benefit-cost ratio (BCR) served as the primary outcome, with values higher than one signifying a self-sustainable programme. Results: The cost/male screened was USD 13.43 ± 2.26, while the participants’ WTP amount of US$3.99 ± 4.49 to calculate the BCR gave a BCR ratio of 0.3. Conclusion: The estimated BCR showed that the programme would not be sustainable if funding were based solely on participants’ out-of-pocket expenses. Other financing mechanisms, such as donor funds, will be necessary to sustain such public health programmes in Nigeria.

The use of prostate-specific antigen mass ratio in prostate cancer

The use of prostate-specific antigen mass ratio in prostate cancer

Body mass index in relation to prostate-specific antigen-related parameters

BackgroundOnly a few previous studies conducted to assess the association between body mass index (BMI) and prostate-specific antigen (PSA) related parameters have taken prostate volume (PV) and blood volume (BV) into consideration. The objective of this study was to assess the relationship between BMI and parameters of PSA concentrations in Chinese adult men.MethodsA total of 86,912 men who have received annual physical examination at the First Affiliated Hospital of Army Medical University from 1 January 2011 to 31 December 2018 were included in this study. Linear regression models were performed to assess the relationship between BMI, PV, BV and PSA, and analyze the correlation between BMI and PSA, PSA density and PSA mass.ResultsThe univariable linear regression showed that PV, BV, systolic pressure (SBP), pulse, fasting blood glucose (FBG) and age were significantly associated with PSA level (P < 0.05). The multivariate linear regression demonstrated that PV, BV, FBG and age were significantly associated with PSA level (P < 0.05). WHR and BMI is negatively associated with PSA and PSA density (P < 0.05), and no statistically significant association was found between PSA mass and WHR and (P = 0.268) or BMI (P = 0.608).ConclusionsThe findings of this large-sample, hospital-based study in China indicate that PV was positively associated with serum PSA concentrations, while BMI and BV were inversely related with PSA levels. PSA mass can be used to estimate the PSA concentration without being affected by obesity in Chinese men.

Prostate-specific antigen (PSA) related to the anthropometric profile among patients admitted at the Hospital II Huamanga Carlos Tuppia García-Godos, EsSalud. Ayacucho

Objective: To determine the association between plasma and mass prostate-specific antigen (PSA) levels and theanthropometric profile, taking into account the risk of prostate pathologies. Materials and methods: A correlational, quantitative, cross-sectional and retrospective study conducted with a sampleof 156 medical records of male patients with PSA tests and anthropometric data. Spearman's Rho with a 95 % confidencelevel was used to analyze the relationship between the variables. Results: The average age of the patients was 67.85 ± 10.83 years and their mean PSA value was 3.57 ± 7.30 ng/mL. Fifteen (15)patients (9.60 %) had a low risk (PSA = 4.1 – 9.90 ng/mL), eight (5.10 %) a medium risk (PSA = 10 – 19.90 ng/mL) and six (3.80 %)a high risk (PSA ≥ 20 ng/mL) of developing prostate pathologies. The mean body mass index (BMI) was 26.37 ± 3.81 kg/m2: 85patients (54.50 %) were overweight and 18 (11.50 %) were obese. The mean mass PSA was 14.89 ± 30.50 μg, the body surfacearea (BSA) was 3.93 ± 2.72 m2 and the plasma volume was 4.18 ± 0.21 L. A very low positive correlation was evidencedbetween plasma PSA and age (rho = 0.184; p = 0.022) and between mass PSA and age (rho = 0.176; p = 0.028). There was amoderate positive association between plasma PSA and BSA (rho = 0.456; p = 0.000) and between mass PSA and BSA(rho = 0.463; p = 0.000). No relationship was found between BMI and PSA. Conclusions: The association between plasma and mass PSA levels and the anthropometric profile was demonstrated,taking into account the risk of prostate pathologies, which increased with BSA and age.

Does prostate-specific antigen (PSA) mass or free PSA mass improve the accuracy of predicting total prostate volume in relation to obesity in men with biopsy-proven benign prostatic hyperplasia?

We evaluated whether the prostate-specific antigen (PSA) mass or free PSA (fPSA) mass (i.e., absolute amount of total circulating PSA or fPSA protein, respectively), versus serum PSA or fPSA concentration, improves the accuracy of predicting the total prostate volume (TPV) in relation to obesity. Among men whose multicore (≥12) transrectal prostate biopsy was negative, 586 who had a PSA of ≤10 ng ml−1 and underwent the fPSA test prior to biopsy were enrolled. The PSA mass or fPSA mass (μ g) was calculated by multiplying the serum level by plasma volume. At each TPV cut-off point (30 ml, 40 ml, and 50 ml), the areas under the receiver operating characteristics curve (AUCs) of each variable were compared in obesity-based subgroups. AUCs of fPSA and fPSA mass for predicting TPV were significantly larger than those for PSA and PSA mass by 8.7%–12.1% at all cut-off points. Subgroup analyses based on obesity showed that, although PSA mass and fPSA mass enhanced accuracy by 4% (P = 0.031) and 1.8% (P = 0.003), respectively, for determining TPVs of ≥30 ml and ≥50 ml in obese and overweight men, they did not improve the accuracy in most other combinations of the degrees of obesity with TPV cut-off points. Thus, compared with serum PSA or fPSA, the absolute amount of PSA or fPSA protein mass improved the accuracy of predicting TPV in obese men very minimally and only for certain TPV cut-off points. Hence, these indicators may not provide clinically meaningful improvement in predicting TPV in obese men.

Serum Prostate-Specific Antigen (PSA) Concentration, PSA Mass, and Obesity: A Mathematical Analysis.

To provide a mathematical background for understanding the phenomenon of analyte hemodilution using a kinetic analysis. The first assumption for this analysis is that change in concentration of any analyte, such as prostate-specific antigen (PSA), is due to the flux of the analyte from an organ into the blood minus its flux from the blood. What results is a relatively simple differential equation that emphasizes the importance of plasma volume, organ mass, and two rate constants. The analyses demonstrate how serum PSA can be affected by plasma volume as well as body mass and how hemodilution due to obesity can be at least partly corrected for by expressing PSA in units of total mass or total mass density. At a time when obesity is prevalent, expressing analytes in units of total mass may make them relate more closely to disease status and prognosis.

Investigating the prostate specific antigen, body mass index and age relationship: is an age-BMI-adjusted PSA model clinically useful?

PurposePrevious studies indicate a possible inverse relationship between prostate-specific antigen (PSA) and body mass index (BMI), and a positive relationship between PSA and age. We investigated the associations between age, BMI, PSA, and screen-detected prostate cancer to determine whether an age–BMI-adjusted PSA model would be clinically useful for detecting prostate cancer.MethodsCross-sectional analysis nested within the UK ProtecT trial of treatments for localized cancer. Of 18,238 men aged 50–69 years, 9,457 men without screen-detected prostate cancer (controls) and 1,836 men with prostate cancer (cases) met inclusion criteria: no history of prostate cancer or diabetes; PSA < 10 ng/ml; BMI between 15 and 50 kg/m2. Multivariable linear regression models were used to investigate the relationship between log-PSA, age, and BMI in all men, controlling for prostate cancer status.ResultsIn the 11,293 included men, the median PSA was 1.2 ng/ml (IQR: 0.7–2.6); mean age 61.7 years (SD 4.9); and mean BMI 26.8 kg/m2 (SD 3.7). There were a 5.1% decrease in PSA per 5 kg/m2 increase in BMI (95% CI 3.4–6.8) and a 13.6% increase in PSA per 5-year increase in age (95% CI 12.0–15.1). Interaction tests showed no evidence for different associations between age, BMI, and PSA in men above and below 3.0 ng/ml (all p for interaction >0.2). The age–BMI-adjusted PSA model performed as well as an age-adjusted model based on National Institute for Health and Care Excellence (NICE) guidelines at detecting prostate cancer.ConclusionsAge and BMI were associated with small changes in PSA. An age–BMI-adjusted PSA model is no more clinically useful for detecting prostate cancer than current NICE guidelines. Future studies looking at the effect of different variables on PSA, independent of their effect on prostate cancer, may improve the discrimination of PSA for prostate cancer.

Periprostatic Fat: A Risk Factor for Prostate Cancer?

To evaluate whether periprostatic fat volume and periprostatic fat ratio as determined by multiparametric magnetic resonance imaging (mpMRI) correlate with the presence of high-grade prostate cancer. A total of 295 consecutive patients (median age: 64, range: 38-84) underwent mpMRI of the prostate gland between August 2013 and February 2015. All patients underwent a 3 Tesla mpMRI. Using DynaCAD (Invivo, Gainesville, FL), we calculated the prostate volume and volume of the periprostatic fat seen on mpMRI. The periprostatic fat ratio was calculated using the formula periprostatic fat volume/prostate volume. A higher periprostatic fat volume (P <.001) and a higher periprostatic fat ratio (P <.001) were significantly associated with a higher Gleason score. Periprostatic fat ratio is a better predictor of higher Gleason score compared with periprostatic fat volume (P < .001). There was no correlation observed between periprostatic fat ratio and prostate-specific antigen (median: 7.34, range: 0.36-59.7, P = .274), age (median: 64, range: 38-84, P = .665), or body mass index (median: 28.33, range: 17.99-45.44, P = .310). Patients with a higher periprostatic fat ratio were more likely to undergo intervention for prostate cancer. A higher periprostatic fat ratio is significantly associated with a higher Gleason score. Periprostatic fat ratio is a better predictor of higher Gleason score compared with periprostatic fat volume and may be an important risk factor in diagnosing patients with higher grade prostate cancer.

Do Black NonHispanic Men Produce Less Prostate Specific Antigen in Benign Prostate Tissue or Cancer Compared to White NonHispanic Men with Gleason Score 6 (Grade Group 1) Prostate Cancer?

We evaluated prostate specific antigen production by benign prostate tissue and Gleason score 3+3=6 (Grade Group 1) prostate cancer in black and white nonHispanic men. We used Gleason score 3+3=6 (Grade Group 1) cases to assess prostate specific antigen production by benign prostate tissue in cases with low volume cancer that did not influence prostate specific antigen and inthose with high volume cancer in which gland weight did not influence prostate specific antigen. We then created age, prostate specific antigen andprostate weight adjusted cohorts to demonstrate tumor volume per 1 ng/ml prostate specific antigen and 1 μg prostate specific antigen mass. Prostate specific antigen density and prostate specific antigen mass density were used to adjust for prostate weight. Comparison of 58 black and 301 white men with low volume cancer demonstrated equal prostate specific antigen production by benign prostate tissue. Comparison of 30 black and 75 white men with high volume cancer indicated that prostate specific antigen was being driven by cancer volume, with lower prostate specific antigen production in black men. In the cohort of 54 black and 134 white men matched by age, prostate specific antigen and prostate weight, tumor volume per 1 ng/ml prostate specific antigen or 1 μg prostate specific antigen mass adjusted for prostate weight was 25% and 26% higher in black men, respectively. Benign prostate tissue produces equal amounts of prostate specific antigen in black and white men. Gleason score 3+3=6 (Grade Group 1) prostate cancer produces less prostate specific antigen in black men. These data should be considered for lowering prostate specific antigen and its derivatives in determining biopsy thresholds and for adjusting values for active surveillance criteria in black men.

Radical Prostatectomy Findings in White Hispanic/Latino Men With NCCN Very Low-risk Prostate Cancer Detected by Template Biopsy.

Radical prostatectomy (RP) outcomes have been studied in White and Black non-Hispanic men qualifying for Epstein active surveillance criteria (EASC). Herein, we first analyzed such outcomes in White Hispanic men. We studied 70 men with nonpalpable Gleason score 3+3=6 (Grade Group [GG] 1) prostate cancer (PCa) with ≤2 positive cores on biopsy who underwent RP. In 18 men, prostate-specific antigen (PSA) density (PSAD) was >0.15 ng/mL/g. Three of these had insignificant and 15 had significant PCa. The remaining 52 men qualified for EASC. One patient had no PCa identified at RP. Nineteen (37%) had significant PCa defined by volume (n=7), grade (n=7), and volume and grade (n=5). Nine cases were 3+4=7 (GG 2) (5/9 [56%] with pattern 4 <5%), 2 were 3+5=8 (GG 4), and 1 was 4+5=9 (GG 5). Patients with significant PCa more commonly had anterior dominant disease (11/19, 58%) versus patients with insignificant cancer (7/33, 21%) (P=0.01). In 12 cases with higher grade at RP, the dominant tumor nodule was anterior in 6 (50%) and posterior in 6 (median volumes: 1.1 vs. 0.17 cm, respectively; P=0.01). PSA correlated poorly with tumor volume (r=0.28, P=0.049). Gland weight significantly correlated with PSA (r=0.54, P<0.001). While PSAD and PSA mass density correlated with tumor volume, only PSA mass density distinguished cases with significant disease (median, 0.008 vs. 0.012 μg/g; P=0.03). In summary, a PSAD threshold of 0.15 works well in predicting significant tumor volume in Hispanic men. EASC appear to perform better in White Hispanic men than previously reported outcomes for Black non-Hispanic and worse than in White non-Hispanic men. Significant disease is often Gleason score 3+3=6 (GG 1) PCa >0.5 cm. Significant PCa is either a larger-volume anterior disease that may be detected by multiparametric magnetic resonance imaging-targeted biopsy or anterior sampling of the prostate or higher-grade smaller-volume posterior disease that in most cases should not pose immediate harm and may be detected by repeat template biopsies.

Prostate-specific antigen lowering effect of metabolic syndrome is influenced by prostate volume.

To investigate the influence of metabolic syndrome on prostate-specific antigen levels by considering prostate volume and plasma volume. We retrospectively analyzed 4111 men who underwent routine check-ups including prostate-specific antigen and transrectal ultrasonography. The definition of metabolic syndrome was based on the modified Adult Treatment Panel III criteria. Prostate-specific antigen mass density (prostate-specific antigen × plasma volume / prostate volume) was calculated for adjusting plasma volume and prostate volume. We compared prostate-specific antigen and prostate-specific antigen mass density levels of participants with metabolic syndrome (metabolic syndrome group, n = 1242) and without metabolic syndrome (non-prostate-specific antigen metabolic syndrome group, n = 2869). To evaluate the impact of metabolic syndrome on prostate-specific antigen, linear regression analysis for the natural logarithm of prostate-specific antigen was used. Patients in the metabolic syndrome group had significantly older age (P < 0.001), larger prostate volume (P < 0.001), higher plasma volume (P < 0.001) and lower mean serum prostate-specific antigen (non-metabolic syndrome group vs metabolic syndrome group; 1.22 ± 0.91 vs 1.15 ± 0.76 ng/mL, P = 0.006). Prostate-specific antigen mass density in the metabolic syndrome group was still significantly lower than that in the metabolic syndrome group (0.124 ± 0.084 vs 0.115 ± 0.071 μg/mL, P = 0.001). After adjusting for age, prostate volume and plasma volume using linear regression model, the presence of metabolic syndrome was a significant independent factor for lower prostate-specific antigen (prostate-specific antigen decrease by 4.1%, P = 0.046). Prostate-specific antigen levels in patients with metabolic syndrome seem to be lower, and this finding might be affected by the prostate volume.

Prostate-specific Antigen Mass Density—A Measure Predicting Prostate Cancer Volume and Accounting for Overweight and Obesity-related Prostate-specific Antigen Hemodilution

To test prostate-specific antigen mass density (PSAMD) as a predictor of total tumor volume (TTV) at radical prostatectomy (RP). We conducted a detailed pathologic analysis of 469 RP from men with NCCN low-risk prostate cancer who had Gleason score of 3 + 3 = 6 (grade group 1) at RP. We then compared the ability of PSA, PSA density (PSAD), PSA mass (PSAM-absolute amount of PSA in patient's circulation), and PSAM density (PSAM divided by prostate weight without seminal vesicles) to predict TTV at RP. PSAM was calculated by multiplying plasma volume (estimated body surface [weight, kg(0.425) × height, m(0.72) × 0.007184] × 1.67) by PSA. Performance of the above measures in different BMI categories was assessed. Kruskal-Wallis test was used to compare the means and Spearman's rank correlation coefficient to assess the correlations. The 469 men were normal weight (n = 129), overweight (n = 253), and obese (n = 87). Mean age of the patients' was 57.4 years and PSA of 4.53 ng/ml. Increase of prostate weight with body mass index (BMI) was reflected in PSAM (both P <.001) but not in other measures. BMI did not correlate with TTV and PSA. Among PSA, PSAD, PSAM, and PSAMD, PSAMD had the highest correlation with TTV (r = 0.336; P <.001). Prostate weight had stronger (negative) association with PSAMD (r = -0.394; <.001) than TTV. PSAMD is the biochemical measure with the best correlation with TTV at RP. Unlike other measures, it is not affected by BMI-related hemodilution. Thresholds should be established to use this more objective measure clinically in surveillance algorithms and in planning radical prostatectomy.

The Prevalence and Association of Varicoceles on Male Patients With Benign Prostatic Hyperplasia/Lower Urinary Tract Symptoms

To investigate the association between the prevalence of varicocele and benign prostatic hyperplasia (BPH)/lower urinary tract symptoms (LUTS) in elder man in China. A total of 831 BPH/LUTS outpatients who were 40 years or older were recruited. The patients' age, total prostatic volume (TPV), International Prostate Symptom Score, total prostate-specific antigen, nocturia, and body mass index were recorded. The presence and grade of varicocele were diagnosed by physical examination in combination with scrotal color Doppler. The total prevalence of varicocele was 53.0%. The prevalence values of varicoceles in patients were 40-49, 50-59, 60-69, 70-79 years old, and 80 or above were 43.0%, 42.4%, 54.0%, 59.5%, and 64.0%, respectively. When comparing with varicocele grade, TPV (P = .002) was found to be significantly different. Nocturia frequencies increased significantly in patients with varicocele (P < .01). There were no difference in terms of International Prostate Symptom Score, total prostate-specific antigen, and body mass index between patients with no varicocele and with grades 1, 2, and 3 varicoceles (P > .05). For elderly patients, the prevalence of varicocele shows an increasing trend with aging. Higher-grade varicoceles are associated with higher TPV and nocturia levels. Varicocele, which may be a factor that affects BPH/LUTS, cannot be overlooked.

Correlations of Metabolic Components with Prostate Volume in Middle-Aged Men Receiving Health Check-Up.

ObjectivesTo investigate the impact of metabolic components and body composition indices on prostate volume (PV) in a population of middle-aged men receiving health check-ups.MethodsSix hundred and sixteen men receiving health assessments were stratified to large and small prostates based on the cut-off of median PV. Their demographic data, health history, and international prostate symptoms scores (IPSS) were collected. Metabolic components and body composition indices were compared between subjects with large and small prostates. Moreover, the correlations between these parameters and PV were analyzed by multivariate logistic regression.ResultsThe median PV was 27 mL and mean age was 54.8 years. Subjects with large PV were older (56.5 vs. 52.7 years) and had higher serum prostate specific antigen (PSA) level (1.73 vs. 0.96 ng/mL), higher IPSS score (8.37 vs. 6.16), and higher body fat, body mass, and waist circumference (all p<0.05). In multivariate analysis, age (OR, 2.45; 95%CI, 1.74–3.45), serum PSA (OR, 2.75; 95%CI, 1.96–3.86), waist circumference (OR, 1.45; 95%CI, 1.02–2.07), fatness (OR, 1.47; 95%CI, 1.04–2.09), and body fat mass (OR, 1.43; 95%CI, 1.00–2.03) were significantly correlated with PV of study subjects. In subgroup analysis, raised waist circumference (OR, 1.89; 95%CI, 1.00–3.59) was the independent predictor of PV in subjects with bothersome lower urinary tract symptoms.ConclusionsSeveral metabolic components and body composition indices are significantly associated with PV of middle-aged men, including raised waist circumference, fatness, and body fat mass. Raised waist circumference is the only independent predictor of PV in middle-aged men with bothersome LUTS.

African-American Men with Gleason Score 3+3=6 Prostate Cancer Produce Less Prostate Specific Antigen than Caucasian Men: A Potential Impact on Active Surveillance

We assess the difference in prostate specific antigen production between African-American and Caucasian men with Gleason score 3+3=6 prostate cancer. We measured tumor volume in 414 consecutive radical prostatectomies from men with National Comprehensive Cancer Network(®) low risk prostate cancer (348 Caucasian, 66 African-American) who had Gleason score 3+3=6 disease at radical prostatectomy. We then compared clinical presentation, pathological findings, prostate specific antigen, prostate specific antigen density and prostate specific antigen mass (an absolute amount of prostate specific antigen in patient's circulation) between African-American and Caucasian men. The t-test and Wilcoxon rank sum were used for comparison of means. African-American and Caucasian men had similar clinical findings based on age, body mass index and prostate specific antigen. There were no statistically significant differences between the dominant tumor nodule volume and total tumor volume (mean 0.712 vs 0.665 cm(3), p=0.695) between African-American and Caucasian men. Prostates were heavier in African-American men (mean 55.4 vs 46.3 gm, p <0.03). Despite the significantly greater weight of benign prostate tissue contributing to prostate specific antigen in African-American men, prostate specific antigen mass was not different from that of Caucasian men (mean 0.55 vs 0.558 μg, p=0.95). Prostate specific antigen density was significantly less in African-American men due to larger prostates (mean 0.09 vs 0.105, p <0.02). African-American men with Gleason score 3+3=6 prostate cancer produce less prostate specific antigen than Caucasian men. African-American and Caucasian men had equal serum prostate specific antigen and prostate specific antigen mass despite significantly larger prostates in African-American men with all other parameters, particularly total tumor volume, being the same. This finding has practical implications in T1c cases diagnosed with prostate cancer due to prostate specific antigen screening. Lowering the prostate specific antigen density threshold in African-American men may account for this disparity, particularly in selecting patients for active surveillance programs.

Correlation of High Body Mass Index With More Advanced Localized Prostate Cancer at Radical Prostatectomy Is Not Reflected in PSA Level and PSA Density but Is Seen in PSA Mass.

Prostate cancer screening algorithms and preoperative nomograms do not include patients' body mass index (BMI). We evaluated outcomes at radical prostatectomy (RP) adjusted to BMI. Serum prostate-specific antigen (PSA) levels, PSA mass, PSA density (PSAD), and RP findings were analyzed with respect to BMI in 4,926 men who underwent RP between 2005 and 2014. In total, 1,001 (20.3%) men were normal weight, 2,547 (51.7%) were overweight, and 1,378 (28%) were obese. Median PSA levels (ng/mL) were normal weight, 5.0; overweight, 5.1; and obese, 5.2 (P = .094). Median PSA mass increased with increasing BMI: 15.9 vs 17.4 vs 19.4 μg (P < .001). Median PSAD was not significantly different: 0.11 vs 0.11 vs 0.11 ng/mL/g (P = .084). Median prostate weight increased with increasing BMI: 44 vs 45 vs 49 g (P < .001). Median prostatectomy tumor volume increased with increasing BMI: 3.9 vs 4.7 vs 5.9 cm(3) (P < .001). Overweight and obese patients had a higher Gleason score and more locally advanced cancer (P < .001). Frequency of positive surgical margins increased with higher BMIs (P < .001). Frequency of lymph node metastasis did not differ significantly (P = .088). While BMI correlates with tumor volume, Gleason score, and extent of disease at RP, there is no routinely measured clinical parameter reflecting this. Only PSA mass highlights this correlation. Thus, BMI and potentially PSA mass should be taken into account in predictive algorithms pertaining to prostate cancer and its surgical treatment.

Optimisation of an electrochemical impedance spectroscopy aptasensor by exploiting quartz crystal microbalance with dissipation signals

The response of an Electrochemical Impedance Spectroscopy (EIS) sensor using DNA aptamers is affected by many factors, such as DNA density, charge and conformational changes upon DNA-target binding, and buffer conditions. We report here for the first time on the optimisation of an EIS aptamer-based sensor by using Quartz Crystal Microbalance with Dissipation mode (QCM-D). As a case study, we employed a DNA aptamer against Prostate-Specific Antigen (PSA). PSA detection was achieved by functionalising the gold sensor surface via thiol chemistry with different ratios of thiolated-DNA aptamer and 6-mercapto-1-hexanol (MCH) used as spacer molecules. PSA binding efficiency can be monitored by measuring QCM-D signals which not only provide information about the mass of PSA bound on the sensor surface, but also crucial information about the aptamer conformation and layer hydration.Data generated through QCM-D analysis provided the optimal conditions in terms of aptamer/MCH ratio to maximise the PSA binding. The ratio of 1:200 for DNA aptamer/spacer molecule was found to be optimal for ensuring maximum PSA binding. However, this study showed how a maximum analyte binding does not necessarily correspond to a maximum EIS response, which revealed to be enhanced if a ratio of 1:100 for DNA aptamer/spacer molecule was used. Moreover, by monitoring the QCM-D signal, for the first time, a value of the dissociation constant (Kd), equal to 37nM, was found for the PSA DNA aptamer towards its target. The combination of QCM-D with EIS techniques provides further insight into the effects of mass loading and charge effects that govern the response of an EIS aptasensor, serving as a valuable support for future EIS aptamer-based applications.