Tumor Volume in Prostate Cancer and Serum Prostate-Specific Antigen

Review: Mathematical Modeling of Prostate Cancer and Clinical Application

We review and synthesize key findings and limitations of mathematical models for prostate cancer, both from theoretical work and data-validated approaches, especially concerning clinical applications. Our focus is on models of prostate cancer dynamics under treatment, particularly with a view toward optimizing hormone-based treatment schedules and estimating the onset of treatment resistance under various assumptions. Population models suggest that intermittent or adaptive therapy is more beneficial to delay cancer relapse as compared to the standard continuous therapy if treatment resistance comes at a competitive cost for cancer cells. Another consensus among existing work is that the standard biomarker for cancer growth, prostate-specific antigen, may not always correlate well with cancer progression. Instead, its doubling rate appears to be a better indicator of tumor growth. Much of the existing work utilizes simple ordinary differential equations due to difficulty in collecting spatial data and due to the early success of using prostate-specific antigen in mathematical modeling. However, a shift toward more complex and realistic models is taking place, which leaves many of the theoretical and mathematical questions unexplored. Furthermore, as adaptive therapy displays better potential than existing treatment protocols, an increasing number of studies incorporate this treatment into modeling efforts. Although existing modeling work has explored and yielded useful insights on the treatment of prostate cancer, the road to clinical application is still elusive. Among the pertinent issues needed to be addressed to bridge the gap from modeling work to clinical application are (1) real-time data validation and model identification, (2) sensitivity analysis and uncertainty quantification for model prediction, and (3) optimal treatment/schedule while considering drug properties, interactions, and toxicity. To address these issues, we suggest in-depth studies on various aspects of the parameters in dynamical models such as the evolution of parameters over time. We hope this review will assist future attempts at studying prostate cancer.

Serum carbohydrate antigen 125 levels and incident risk of type 2 diabetes mellitus in middle-aged and elderly Chinese population: The Dongfeng-Tongji cohort study

OBJECTIVES

The aim of this study was to investigate the association between serum carbohydrate antigen 125 concentrations and incident type 2 diabetes mellitus risk in a prospective cohort.

METHODS

We included 18,983 eligible participants aged 63.1 years derived from the Dongfeng-Tongji cohort at baseline from September 2008 to June 2010, and they were followed until October 2013. Cox proportional-hazards models were used to estimate the hazard ratios and 95% confidence interval of type 2 diabetes mellitus incidence in relation to carbohydrate antigen 125 concentrations.

RESULTS

In all, 1594 incident cases of type 2 diabetes mellitus were observed after a median follow-up of 4.6 years. Carbohydrate antigen 125 concentrations were categorized into four groups according to the quartiles of distribution: <1.1, 1.1-5.6, 5.6-10.0 and ⩾10 U/mL. Compared with participants in the lowest quartile, the hazard ratio (95% confidence interval) of type 2 diabetes mellitus was 0.97 (0.81-1.15), 1.23 (1.05-1.45) and 1.48 (1.27-1.74) for quartile 2-quartile 4 of carbohydrate antigen 125 concentrations after adjustment for potential confounders (p for trend < 0.001). With per-standard deviation increase in carbohydrate antigen 125 levels, the hazard ratio of type 2 diabetes mellitus increased 12% (95% confidence interval, 8-16).

CONCLUSION

Findings from this study indicated that serum carbohydrate antigen 125 concentrations were positively correlated with incident type 2 diabetes mellitus risk among a middle-aged and elderly Chinese population.

Mechanistic modelling of prostate-specific antigen dynamics shows potential for personalized prediction of radiation therapy outcome

External beam radiation therapy is a widespread treatment for prostate cancer. The ensuing patient follow-up is based on the evolution of the prostate-specific antigen (PSA). Serum levels of PSA decay due to the radiation-induced death of tumour cells and cancer recurrence usually manifest as a rising PSA. The current definition of biochemical relapse requires that PSA reaches nadir and starts increasing, which delays the use of further treatments. Also, these methods do not account for the post-radiation tumour dynamics that may contain early information on cancer recurrence. Here, we develop three mechanistic models of post-radiation PSA evolution. Our models render superior fits of PSA data in a patient cohort and provide a biological justification for the most common empirical formulation of PSA dynamics. We also found three model-based prognostic variables: the proliferation rate of the survival fraction, the ratio of radiation-induced cell death rate to the survival proliferation rate, and the time to PSA nadir since treatment termination. We argue that these markers may enable the early identification of biochemical relapse, which would permit physicians to subsequently adapt patient monitoring to optimize the detection and treatment of cancer recurrence.

Modeling therapeutic response to radioiodine in metastatic thyroid cancer: a proof-of-concept study for individualized medicine

Purpose

Radioiodine therapy (RAI) has traditionally been used as treatment for metastatic thyroid cancer, based on its ability to concentrate iodine. Propositions to maximize tumor response with minimizing toxicity, must recognize the infinite possibilities of empirical tests. Therefore, an approach of this study was to build a mathematical model describing tumor growth with the kinetics of thyroglobulin (Tg) concentrations over time, following RAI for metastatic thyroid cancer.

Experimental Design

Data from 50 patients with metastatic papillary thyroid carcinoma treated within eight French institutions, followed over 3 years after initial RAI treatments, were included in the model. A semi-mechanistic mathematical model that describes the tumor growth under RAI treatment was designed.

Results

Our model was able to separate patients who responded to RAI from those who did not, concordant with the physicians' determination of therapeutic response. The estimated tumor doubling-time (Td was found to be the most informative parameter for the distinction between responders and non-responders. The model was also able to reclassify particular patients in early treatment stages.

Conclusions

The results of the model present classification criteria that could indicate whether patients will respond or not to RAI treatment, and provide the opportunity to perform personalized management plans.

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

OBJECTIVES

To provide a mathematical background for understanding the phenomenon of analyte hemodilution using a kinetic analysis.

METHODS

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.

RESULTS

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.

CONCLUSIONS

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.

Tissue-scale, personalized modeling and simulation of prostate cancer growth

Recently, mathematical modeling and simulation of diseases and their treatments have enabled the prediction of clinical outcomes and the design of optimal therapies on a personalized (i.e., patient-specific) basis. This new trend in medical research has been termed "predictive medicine." Prostate cancer (PCa) is a major health problem and an ideal candidate to explore tissue-scale, personalized modeling of cancer growth for two main reasons: First, it is a small organ, and, second, tumor growth can be estimated by measuring serum prostate-specific antigen (PSA, a PCa biomarker in blood), which may enable in vivo validation. In this paper, we present a simple continuous model that reproduces the growth patterns of PCa. We use the phase-field method to account for the transformation of healthy cells to cancer cells and use diffusion-reaction equations to compute nutrient consumption and PSA production. To accurately and efficiently compute tumor growth, our simulations leverage isogeometric analysis (IGA). Our model is shown to reproduce a known shape instability from a spheroidal pattern to fingered growth. Results of our computations indicate that such shift is a tumor response to escape starvation, hypoxia, and, eventually, necrosis. Thus, branching enables the tumor to minimize the distance from inner cells to external nutrients, contributing to cancer survival and further development. We have also used our model to perform tissue-scale, personalized simulation of a PCa patient, based on prostatic anatomy extracted from computed tomography images. This simulation shows tumor progression similar to that seen in clinical practice.

Prostate specific antigen kinetics following robotic stereotactic body radiotherapy for localized prostate cancer

BACKGROUND

Stereotactic body radiotherapy (SBRT) has emerged as an effective treatment for localized prostate cancer. However, prostate specific antigen (PSA) kinetics after prostate SBRT have not been well characterized. The purpose of this study was to analyze the trend in PSA decline following robotic SBRT from a prospective cohort of patients.

MATERIAL AND METHODS

In total 175 patients were treated definitively for localized prostate cancer to a dose of 35-36.25 Gy in 5 fractions using robotic SBRT in the absence of androgen deprivation therapy (ADT). PSA and testosterone were collected at regular intervals following treatment and patients were assessed for biochemical failure and benign PSA bounce. A PSA nadir threshold of 0.5 ng/ml was used as a predictor of long-term disease-free survival. Multivariate logistic regression was used to assess the effect of disease specific covariates on the likelihood of achieving a PSA nadir less than threshold. PSA kinetics were analyzed a multi-component exponential model accounting for benign and malignant sources of PSA.

RESULTS AND CONCLUSION

At a median follow-up of 3 years, 70% of patients achieved a PSA nadir below 0.5 ng/ml with a median PSA nadir of 0.3 ng/ml at a median time to nadir of 30 months. In our cohort, 36.2% experienced a benign PSA bounce. Absence of PSA bounce, initial PSA, and testosterone at the time of nadir proved to be significant predictors of achieving a PSA nadir below threshold. PSA kinetics after prostate SBRT were well described with a functional volume model with fitted half-lives of 4.4 and 14.8 months for malignant and benign sources of PSA, respectively. Patients treated with prostate SBRT experience an initial period of rapid PSA decline followed by a slow decline which will likely result in lower PSA nadirs after longer follow-up. The long-term disease specific impacts of these results remain to be determined.

A critical review of the analytical approaches for circulating tumor biomarker kinetics during treatment

Changes in serum tumor biomarkers may indicate treatment efficacy. Traditional tumor markers may soon be replaced by novel serum biomarkers, such as circulating tumor cells (CTCs) or circulating tumor nucleic acids. Given their promising predictive values, studies of their kinetics are warranted. Many methodologies meant to assess kinetics of traditional marker kinetics during anticancer treatment have been reported. Here, we review the methodologies, the advantages and the limitations of the analytical approaches reported in the literature. Strategies based on a single time point were first used (baseline value, normalization, nadir, threshold at a time t), followed by approaches based on two or more time points [half-life (HL), percentage decrease, time-to-events…]. Heterogeneities in methodologies and lack of consideration of inter- and intra-individual variability may account for the inconsistencies and the poor utility in routine. More recently, strategies based on a population kinetics approach and mathematical modeling have been reported. The identification of equations describing individual kinetic profiles of biomarkers may be an alternative strategy despite its complexity and higher number of necessary measurements. Validation studies are required. Efforts should be made to standardize biomarker kinetic analysis methodologies to ensure the optimized development of novel serum biomarkers and avoid the pitfalls of traditional markers.

Association between carcinoembryonic antigen, carbohydrate antigen 19-9 and body mass index in colorectal cancer patients

Carbohydrate antigen 19-9 (CA19-9) and carcinoembryonic antigen (CEA) have been well recognized as tumor markers for colorectal cancer. Previous studies suggested that obesity is inversely associated with the screening of CEA and CA19-9 levels and may reduce screening sensitivity. This study was conducted to evaluate the association of body mass index (BMI) with serum CEA and CA19-9 concentration in colorectal cancer patients. A total of 300 patients were enrolled in the study, selected from 2,950 consecutive colorectal cancer patients who underwent surgical treatment between August, 1994 and December, 2005. The association of BMI with CEA concentration, total circulating CEA mass and plasma volume was assessed by determining P-values for trends. The multivariate linear regression analysis was used to adjust for clinicopathological confounding factors to analyze the main outcome measures when CEA and CA19-9 had been log-transformed. Increased BMI was linearly correlated with a higher plasma volume. Using the stepwise method, the multiple regression model including BMI categories was reconstructed as follows: log_e[CEA]=0.208+0.241[liver metastasis]+0.051 [differentiation]+0.092[TNM]; log_e[CA19-9]=0.969+0.233 [gender]+0.141[ascites]+0.09[TNM]. The mean survival time in CEA⁺/CA19-9⁻, CEA⁺/CA19-9⁺, CEA⁻/CA19-9⁻ and CEA⁻/CA19-9⁺ patients was 84.8, 58.2, 100.6 and 74.7 months, respectively. The 1-/3-year survival rates in each group was 76.0/59.8, 66.2/43.5, 96.3/87.6 and 71.7/41.0, respectively. In conclusion, the decreased concentration of CEA and CA19-9 in patients of higher BMIs may be the result of the hemodilution effect. The BMI factor should be considered during the surveillance of colorectal cancer. In addition, patients with simultaneous positive expression of CEA and CA19-9 exhibited shorter survival time.

Comprehensive analysis of post-diagnostic prostate-specific antigen kinetics as predictor of a prostate cancer progression in active surveillance patients

WHAT'S KNOWN ON THE SUBJECT? AND WHAT DOES THE STUDY ADD?: A significant proportion of patients diagnosed with prostate cancer do not require immediate treatment and could be managed by active surveillance, which usually includes serial measurements of prostate-specific antigen (PSA) levels and regular biopsies. The rate of rise in PSA levels, which could be calculated as PSA velocity or PSA doubling time, was previously suggested to be associated with the biological aggressiveness of prostate cancer. Although these parameters are obvious candidates for predicting tumour progression in active surveillance patients, earlier studies that examined this topic provided conflicting results. Our analysis showed that PSA velocity and PSA doubling time calculated at different time-points, by different methods, over different intervals, and in different sub-groups of active surveillance patients provide little if any prognostic information. Although we found some significant associations between PSA velocity and the risk of progression as determined by biopsy, the actual clinical significance of this association was small. Furthermore, PSA velocity did not add to the predictive accuracy of total PSA.

OBJECTIVE

To study whether prostate-specific antigen (PSA) velocity (PSAV) and PSA doubling time (PSADT) are associated with biopsy progression in patients managed by active surveillance.

PATIENTS AND METHODS

Our inclusion criteria for active surveillance are biopsy Gleason sum <7, two or fewer positive biopsy cores, ≤20% tumour present in any core, and clinical stage T1-T2a. Changes in any of these parameters during the follow-up that went beyond these limits are considered to be progression. This study included 250 patients who had at least one surveillance biopsy, an available PSA measured no earlier than 3 months before diagnosis, and at least one PSA measurement before each surveillance biopsy. We evaluated the association between PSA kinetics and progression at successive surveillance biopsies in different sub-groups of patients by calculating the area under the curve (AUC) as well as sensitivity and specificity of different thresholds.

RESULTS

Over a median follow-up of 3.0 years, the disease of 64 (26%) patients progressed. PSADT was not associated with biopsy progression, whereas PSAV was only weakly associated with progression in certain sub-groups. However, incorporation of PSAV in models including total PSA resulted in a moderate increase in AUC only when the entire cohort was analysed. In other sub-groups the predictive accuracy of total PSA was not significantly improved by adding PSAV.

CONCLUSIONS

Our findings confirm that PSA kinetics should not be used in decision-making in patients with low-risk prostate cancer managed by active surveillance. Regular surveillance biopsies should remain as the principal method of monitoring cancer progression in these men.

Effect of Roux-en-Y gastric bypass on testosterone and prostate-specific antigen

Background

Obese men have lower serum levels of testosterone, dehydroepiandrosterone (DHEA) and prostate-specific antigen (PSA), but an increased risk of dying from prostate cancer. The aim of this study was to examine the effect of surgically induced weight loss on serum testosterone, DHEA and PSA levels in obese men.

Methods

Consecutive men undergoing Roux-en-Y gastric bypass (RYGB) participated in a prospective, longitudinal study. Main outcomes were changes were body mass index (BMI), percentage excess weight loss, serum levels of testosterone, DHEA and PSA, PSA mass and plasma volume, measured before operation and 3, 6 and 12 months later.

Results

In 64 patients, mean BMI fell from 48·2 kg/m2 before operation to 39·2, 35·6 and 32·4 kg/m2 at 3, 6 and 12 months after RYGB. Testosterone levels rose significantly from 259 ng/dl to 386, 452 and 520 ng/dl respectively. Serum PSA levels increased significantly from 0·51 ng/ml to 0·67 ng/ml at 12 months. There were no significant changes in DHEA or PSA mass.

Conclusion

RYGB normalizes the serum testosterone level. PSA levels increase with weight loss and may be inversely correlated with changes in plasma volume, indicating that PSA levels may be artificially low in obese men owing to haemodilution.

Serum CA125 concentration has inverse correlation with metabolic syndrome

Serum carbohydrate antigen 125 (CA-125) is a marker of ovarian cancer and obesity that is related with an increased risk of ovarian cancer. Obesity is a key factor of metabolic syndrome. We evaluated the relationship between CA-125 concentration and metabolic syndrome. The data from subjects who had any cancer and chronic infection were excluded. The data of 12,196 healthy Korean women were analyzed. After CA-125 concentration was divided by quartiles, the prevalence of metabolic syndrome and its components were compared. The lowest quartile of CA-125 compared with the highest quartile showed elevated values of most of metabolic parameters. In addition, as the quartile of CA-125 increased, metabolic derangement decreased. Increased numbers of metabolic syndrome components showed an inverse association with CA-125 levels (P < 0.001). The odds ratio (OR) for the lowest CA-125 quartile vs the highest CA-125 quartile significantly increased in the presence of metabolic syndrome (OR = 1.202, 95% Confidence Interval [CI] 1.013-1.423), elevated triglyceride (OR = 1.381, 95% CI 1.167-1.633), and low high-density lipoprotein cholesterol (OR = 1.168, 95% CI 1.039-1.312). The presence of metabolic syndrome, elevated triglyceride, or low high-density lipoprotein cholesterol negatively correlates with CA-125 concentration.

Effect of obesity on prostate-specific antigen, prostate volume, and international prostate symptom score in patients with benign prostatic hyperplasia

PURPOSE

We examined the correlation between body mass index (BMI) as a marker of obesity and prostate-specific antigen (PSA), prostate volume (PV), and International Prostate Symptom Score (IPSS) in patients with benign prostatic hyperplasia (BPH).

MATERIALS AND METHODS

From January 2008 to December 2008, we examined 258 patients diagnosed with BPH. Patients taking 5α-reductase inhibitors or those diagnosed with prostate cancer were excluded from this study. BPH was defined as PV≥25 ml and IPSS≥8. BMI (kg/m(2)) was categorized into 4 groups as follows: BMI<18.5 (underweight), BMI 18.5-23.0 (normal), BMI 23.0-27.5 (overweight), and BMI>27.5 (obese). The relationships between PSA, PV, IPSS, and BMI were analyzed by correlation analysis and one-way ANOVA.

RESULTS

The mean age of the patients was 65.19±9.13 years and their mean BMI was 23.7±4.4 kg/m(2). The mean PSA values of each BMI group were as follows: 3.42±1.53, 3.07±1.88, 2.74±1.75, and 2.60±1.44 ng/ml. The PSA value was lowest in the obese group. The correlation analysis showed a negative correlation between BMI and PSA (Pearson's correlation coefficient=-0.142, p=0.023) and positive correlations between BMI and PV (Pearson's correlation coefficient=0.32, p=0.001) and IPSS (Pearson's correlation coefficient=0.470, p=0.02). These correlations were also confirmed by one-way ANOVA.

CONCLUSIONS

Patients with an elevated BMI tended to have lower PSA values, larger PVs, and a higher IPSS. We suggest that weight loss could be helpful for BPH symptom relief as well as for detection of coexisting prostate cancer in BPH patients.

PSA mass as a marker of prostate cancer progression after radical prostatectomy

Background

Obese patients with prostate cancer may have lower preoperative PSA concentration due to hemodilution. Lower PSA concentration may falsely affect assessing the risk of progression after radical prostatectomy (RP). The aim of this study was to determine preoperative PSA mass as the absolute amount of PSA protein secreted into circulation, and evaluation of its usefulness in prediction of biochemical recurrence after RP.

Material/Methods

177 patients after RP due to prostate cancer were included in the study. On the basis of formulas, PSA mass was calculated {PSA mass [μg] = (weight [kg])^0.425 × (height [cm])^0.72 × 0.007184 × 1.670 × PSA concentration [ng/ml]}. Patients were divided into 3 groups according to increasing values of PSA mass. The following features were assessed and compared between these groups (χ-square test): pathologic stage T3, nodal metastases, positive surgical margins, biochemical and local recurrence and the rate of death. Cancer-specific survival was assessed depending on PSA mass (Kaplan-Meier curves with log rank test). The usefulness of PSA mass in prediction of biochemical recurrence was compared with PSA concentration (logistic regression with ROC curves).

Results

Pathologic stage T3, nodal metastases, positive surgical margins and progression were more common in patients with higher levels of PSA mass (p<0.01). Cancer-specific survival was significantly shorter in patients with elevated values of PSA mass (p=0.02). Preoperative PSA mass was a more sensitive predictor of biochemical recurrence than was PSA concentration (p=0.04).

Conclusions

The preoperative PSA mass is a better predictor of biochemical recurrence after RP than PSA concentration.

Influence of obesity on the serum carcinoembryonic antigen value in patients with colorectal cancer

BACKGROUND

Prior studies suggest that obesity is inversely associated with tumor marker concentration and may reduce diagnostic precision. This study was undertaken to evaluate the association between body mass index (BMI) and serum carcinoembryonic antigen (CEA) concentrations in colorectal cancer patients.

METHODS

We analyzed the association between BMI and CEA concentration in a group of 2,845 patients who underwent surgical treatment for colorectal adenocarcinoma from 1995 to 2009. Multivariate linear regression analysis was applied to adjust for clinicopathologic confounding factors to analyze main outcome measures. The association of BMI with plasma volume, CEA concentration, and total circulating CEA mass was assessed by determining P values for trends. We also developed a regression formula to calculate the effect of obesity on the serum CEA levels.

RESULTS

Increased BMI was linearly correlated with higher plasma volume (P < 0.001 for trend) and lower adjusted CEA concentrations after controlling for potentially confounding factors (P ≤ 0.005 for trend in stage II and III tumors). Our theoretical model suggests that a CEA value of 7.0 ng/mL in patients of normal weight corresponds to 6.1 ng/mL in obese patients.

CONCLUSIONS

The hemodilution effect from increased plasma volume may account for the decreased CEA concentrations observed in patients with higher BMI.

IMPACT

Obesity might be one of the factors that affect CEA value, leading to loss of sensitivity and diagnostic accuracy in the CEA test. The BMI status of patients should be taken into account during assessment of serum CEA during the surveillance of colorectal cancer.

Serum prostate-specific antigen is better correlated to body surface area than body mass index in a population of healthy Korean men

It has been suggested that the larger vascular volume among obese men causes a dilution effect, decreasing the concentration of serum prostate-specific antigen (PSA). However, plasma volume is proportional to body surface area (BSA) rather than to body mass index (BMI). We determined whether serum PSA level is better correlated to BSA than BMI in a population of ostensibly healthy Korean men. Data from 2604 men who visited our health promotion center were evaluated. All men underwent anthropometric measurements, digital rectal examination, serum PSA determination, and transrectal ultrasound examination. The correlation between serum PSA and other parameters was statistically analyzed. The mean age was 49.9 years and the mean serum PSA level was 1.14 ng/mL. The multivariate analysis revealed that the serum PSA was positively correlated with age, prostate volume, and negatively correlated with BSA only and not with BMI. In addition, BSA, rather than BMI, was the significant factor in predicting the prostate volume. Our results suggest that men with larger BSA (rather than BMI), have larger prostate volumes, and lower serum PSA.

Dissecting the dynamics of serum prostate-specific antigen

I have examined more than 800 values of serum prostate-specific antigen (PSA) in 119 American Veterans during the time before their diagnosis of prostate cancer. These values appear to follow an exponential model with respect to time. Specifically, the model comprises a sum of 2 exponential functions: one for an early, slowly rising component of PSA and a second for a later, faster rising component. The parameters of each component comprise an amplitude and a relative velocity. Whereas the relative velocity of the slow component is significantly associated with the volume of benign tissue, both the amplitude and relative velocity of the fast component are significantly associated with the volume of tumor. The results suggest that at the time of diagnosis of prostate cancer the level and velocity of PSA reflect the combination of slow and fast components. Thus, this model provides insight into how benign and malignant tissues in the prostate determine the dynamics of PSA.

Obesity-PSA relationship: a new formula

To clinically apply the inverse PSA-body mass index (BMI) correlation and enhance PSA sensitivity in obese cases, a new formula is warranted. An innovated BMI-PSA equation is designed. PSA-BMI adjusted formula (named Hekal's equation): measured total PSA (ng ml(-1)) multiplied by age (years) and divided by BMI of the patient. The formula is applied over a randomly chosen 1000 cases of different PSA, BMI, age and trans-rectal ultrasound biopsy results, the yield of new PSA is correlated with pathology and age-specific PSA adjustment values. Among the 988 cases with complete data, obesity (BMI: 30-35 kg m(-2)) in 236 cases (23.8%) and 79 cases (7.9%) have BMI>35 kg m(-2). Mean PSA was 5.8 ng ml(-1) (s.d.+/-8.4 ng ml(-1)). Cases stratified based on their age (every 10 years). The new equation was applied. Obesity is detected in 33.5 and 43.6% of fifth and sixth decade of life respectively (P=0.02), with low measured PSA values (2.1, 3.8 ng ml(-1), respectively). By such PSA measurement biopsy may be omitted, missing 53.3% of malignant cases. In contrast, PSA adjusted were 4 and 9.3 ng ml(-1) within the same group of patients. With such values, the decision of a biopsy could not be missed for the targeted groups. Specificity and sensitivity of adjusted PSA values at cutoff point 4 ng ml(-1) was 41.7 and 70%, respectively. Based on our results, the new PSA-BMI adjusted formula is reproducible, easy applied formula. With such a formula the higher sensitivity of PSA in obese patients could be achieved. The misleading low PSA in obese cases in the fifth and sixth decade will be corrected.

Prognostic value of modeled PSA clearance on biochemical relapse free survival after radical prostatectomy

PURPOSES

Using population kinetic approach, we modeled PSA decline equations in patients with prostate cancer after radical prostatectomy (RP). We looked for relationships between early PSA decrease profile, characterized by PSA clearance (CL(PSA)) or half-life (HL(PSA)), and the 2-year biochemical relapse free survival (bRFS).

PATIENTS AND METHODS

We performed a retrospective study on 55 patients treated with RP and with at least 2 PSA measurements in the post-operative month. A population kinetic model was investigated with NONMEM. The prognostic factors regarding bRFS were assessed using univariate and multivariate analyses.

RESULTS

The best model describing the PSA post-operative decrease was bi-compartmental and fit patient data well. Median CL(PSA) was 0.034 (terciles were 0.023 and 0.048). The significant prognostic factors associated with a better bRFS with univariate analysis were lower CL(PSA) terciles (2-year bRFS = 100% vs. 85.1% vs. 66.7% if CL(PSA) < 0.023, 0.023 <or= CL(PSA) < 0.048 or CL(PSA) >or= 0.0480, P = 0.006) as well as initial PSA < 7 ng/ml, pT2 stage (vs. pT3), pN0 (vs. pN1) and low main Gleason score (3/5 vs. 4/5). Among these factors, CL(PSA) was the only independent prognostic factor with multivariate analysis regarding bRFS (HR = 0.92, 95%CI = [0.86-0.98], P = 0.0088).

CONCLUSION

CL(PSA) determined with 4 PSA concentrations in the first month following the RP may predict the biochemical relapse risk of prostate cancer patients, thus enabling early identification of high-risk patients requiring adjuvant treatment. A prospective validation of these results is required.

Has blood volume an impact on serum PSA levels?

PURPOSE

Prostate-specific antigen (PSA) is measured in circulating blood volume (BV), which is known to have a wide inter- and intraindividual variability. As data investigating the potential impact of different BV on PSA test validity are scant, we determined the relationship between BV and serum PSA values.

METHODS

Men aged 41-60 years, participating in a health screening project, were evaluated. Serum samples of fasting patients were drawn between 8.00 and 10.00 a.m., all PSA measurements were determined in the same laboratory. Circulating BV was calculated according to the Retzlaff formula based on height, weight and haematocrit.

RESULTS

A total of 400 men with a mean age of 47.9 years entered the analysis. Mean PSA was 1.20 ng/ml (range 0.23-8.59 ng/ml) and mean BV was 3,370 ml (range 2,380-4,220 ml). Mean PSA values stratified from lowest to the highest third of BV were 1.22, 1.17 and 1.19 ng/ml in the total cohort. The respective figures for men aged 41-50 years were 1.08, 0.98 and 1.03 ng/ml, and for those aged 51-60 years: 1.47, 1.48 and 1.53 ng/ml. Neither BV nor three other related biometrical parameters (body mass index, waist-hip ratio, body fat percentage) revealed a correlation with the PSA values.

CONCLUSION

Our data suggest that BV does not have a significant impact on serum PSA values. To exclude a potential minor impact of BV on PSA, larger study cohorts, however, are required.

The role of transforming growth factor-beta-mediated tumor-stroma interactions in prostate cancer progression: an integrative approach

We have implemented a hybrid cellular automata model based on the structure of human prostate that recapitulates key interactions in nascent tumor foci between tumor cells and adjacent stroma. Model simulations show how stochastic interactions between tumor cells and stroma may lead to a structural suppression of tumor growth, modest proliferation, or unopposed tumor growth. The model incorporates key aspects of prostate tumor progression, including transforming growth factor-beta (TGF-beta), matrix-degrading enzyme activity, and stromal activation. It also examines the importance of TGF-beta during tumor progression and the role of stromal cell density in regulating tumor growth. The validity of one of the key predictions of the model about the effect of epithelial TGF-beta production on glandular stability was tested in vivo. These experimental results confirmed the ability of the model to generate testable biological predictions in addition to providing new avenues of experimental interest. This work underscores the need for more pathologically representative models to cooperatively drive computational and biological modeling, which together could eventually lead to more accurate diagnoses and treatments of prostate cancer.

Percentage of tumor in prostatectomy specimens: a study of American Veterans

In this study, I have estimated the percentage of tumor by visual estimate in 447 prostatectomy specimens from American Veterans Affairs patients and related this measurement to overall survival. Although percentage of tumor was significantly related to the serum prostate-specific antigen level, tumor stage, and Gleason score-that is, it was not statistically independent from these-it was more closely associated with overall survival than any of them. Altogether, 2 variables available at the time of the prostatectomy related to survival: patient age (P = .0032; Cox proportional hazards model analysis) and percentage of tumor (P = .0013; Cox model). Patient age undoubtedly reflects the combination of comorbidities and general expected length of life. Percentage of tumor, by contrast, seems to efficiently reflect any undue hazard for early death due to prostate cancer. The results suggest that percentage of tumor is a useful prognostic variable for understanding risk of early death after prostatectomy.

Relationship between serum prostate-specific antigen levels and components of metabolic syndrome in healthy men

OBJECTIVES

To assess the correlation between age, body mass index, systolic and diastolic blood pressure (BP), triglycerides, high-density lipoprotein (HDL), and fasting blood glucose (FBG) and the serum prostate-specific antigen (PSA) level and to determine the significant factors for predicting the serum PSA level in men with a low risk of prostate cancer.

METHODS

A total of 38 356 healthy male employees of the Korea Electric Power Corporation who were <60 years old and had a serum PSA level of <4 ng/mL were enrolled in this study from January 2002 to December 2006. Their BP, body weight, and body height were measured, and biochemical analyses of FBG, triglycerides, HDL, and serum PSA were performed.

RESULTS

The mean age +/- standard deviation was 44.38 +/- 7.90 years; the mean serum PSA level was 0.89 +/- 0.51 ng/mL; and the incidence of metabolic syndrome was 25.8%. On univariate analysis, significant correlations were noted between the serum PSA level and body mass index, diastolic BP, HDL, and FBG (P < .05). Multiple logistic regression analyses using 4 percentiles (10th, 25th, 75th, and 90th percentile) of the serum PSA level revealed trends for a positive association between older age and diastolic BP and the serum PSA level. The body mass index, HDL, and FBG correlated negatively with the serum PSA level.

CONCLUSIONS

These results suggest that the serum PSA level is significantly influenced by age and some components of the metabolic syndrome (obesity, diastolic BP, HDL, and FBG).

Advantages of prostate-specific antigen (PSA) clearance model over simple PSA half-life computation to describe PSA decrease after prostate adenomectomy

OBJECTIVES

A population kinetic approach based on PSA clearance (CL(PSA)) may be a more rational strategy to characterize prostate-specific antigen (PSA) decrease profile after prostate surgery than the commonly used method (half-life from mono/bi-exponential models).

METHODS

We used 182 post-adenomectomy PSA concentrations from 56 benign prostatic hyperplasia patients to build, with NONMEM software, a multi-exponential and a CL(PSA) model for comparison.

RESULTS

The best multi-exponential model was PSA(t)=4.96e(-)(0.269t)+3.10e(-)(0.16t)+0.746e(+)(0.0002t) with a stable median residual PSA at 0.64 ng/mL. The best model parametrized with clearance was CL(PSA)=0.0229()(AGE/69)(3.78). Akaike information criteria and standard errors favored the CL(PSA) model. Median peripheral zone and transitional zone productions were 0.034 ng/mL/cm(3) and 0.136 ng/mL/g. A threshold at 2 ng/mL on day 90 allowed for a diagnostic of biochemical relapse diagnostic.

CONCLUSIONS

The population CL(PSA) model was superior to the multi-exponential approach for investigating individual post-adenomectomy PSA decreases.

A mathematical model for the proliferation of bacteria in the urinary bladder due to enlarged prostate

Urinary retention due to enlargement of the prostate (prostate hypertrophy) leads to increased proliferation of bacteria in the bladder. This in turn increases the infection rate. The reason is that the enlarged prostate presses on the urine channel and tends to close it. Thus the out flux of the bladder consists of repeatedly small amounts of fluid during a day. A mathematical dynamic model with differential equations is developed for the proliferation of bacteria in the urinary bladder (vesica urinary). The model accounts for how this proliferation is associated with varying amounts of mass of urine within the bladder. Parameters are estimated from published data and analytical and numerical results are presented. The relationships between the proliferation of bacteria within the bladder and the type of urinal out flux from the bladder are examined. The proliferation is shown to depend on the amount of mass of urine and the out flux of urine from the bladder. In the normal situation the bladder is drained successfully which also drains the bacteria. In the abnormal situation the bladder drains only partly. Despite frequent urination, substantial urine mass in the bladder on the average allows bacteria to proliferate and increase in number through time. The simulations depend on the numerical values of the parameters which again depend on the prostate condition of each male adult under scrutiny. By determining the parameters for each male, the dynamic model can be used as a powerful tool by which the proliferation of bacteria in the bladder can be studied and controlled by different means. Three clinical advices are provided. First, try to achieve that the proliferation rate of bacteria in the bladder is as small as possible, e.g. through altering the pH or chemical composition within the bladder. Second, try to achieve that the out flux of urine from the bladder is substantial, through sufficient drinking. Third, try to achieve that the mass of urine in the bladder is as small as possible, through sufficient urination. The intrinsic parameters for each male can be used to pinpoint the actual out flux during a day necessary to keep the number of bacteria in the bladder low. Suggestions for how to test the model are briefly presented.

Pilot study to explore effects of low-fat, flaxseed-supplemented diet on proliferation of benign prostatic epithelium and prostate-specific antigen

OBJECTIVES

Dietary factors may influence the prostate and have an impact on prostatic growth and disease. A small number of studies have suggested that flaxseed-supplemented, fat-restricted diets may thwart prostate cancer growth in both animals and humans. Unknown, however, is the potential effect of such a diet on benign prostatic epithelium.

METHODS

We undertook a pilot study to explore whether a flaxseed-supplemented, fat-restricted diet affects the proliferation rates in benign epithelium. We also explored the effects on circulating levels of prostate-specific antigen (PSA), total testosterone, and cholesterol. Fifteen men who were scheduled to undergo repeat prostate biopsy were instructed to follow a low-fat (less than 20% kcal), flaxseed-supplemented (30 g/day) diet and were provided with a supply of flaxseed to last throughout the 6-month intervention period. The PSA, total testosterone, and cholesterol levels were determined at baseline and at 6 months of follow-up. Reports from the original and repeat biopsies were compared, and proliferation (MIB-1) rates were quantified in the benign prostatic epithelium.

RESULTS

Statistically significant decreases in PSA (8.47 +/- 3.82 to 5.72 +/- 3.16 ng/mL; P = 0.0002) and cholesterol (241.1 +/- 30.8 to 213.3 +/- 51.2 mg/dL; P = 0.012) were observed. No statistically significant change was seen in total testosterone (434.5 +/- 143.6 to 428.3 +/- 92.5 ng/dL). Although 6-month repeat biopsies were not performed in 2 cases because of PSA normalization, of the 13 men who underwent repeat biopsy, the proliferation rates in the benign epithelium decreased significantly from 0.022 +/- 0.027 at baseline to 0.007 +/- 0.014 at 6 months of follow-up (P = 0.0168).

CONCLUSIONS

These pilot data suggest that a flaxseed-supplemented, fat-restricted diet may affect the biology of the prostate and associated biomarkers. A randomized controlled trial is needed to determine whether flaxseed supplementation, a low-fat diet, or a combination of the two regimens may be of use in controlling overall prostatic growth.

Eligibility and outcomes reporting guidelines for clinical trials for patients in the state of a rising prostate-specific antigen: recommendations from the Prostate-Specific Antigen Working Group

PURPOSE

To define methodology to show clinical benefit for patients in the state of a rising prostate-specific antigen (PSA).

RESULTS

HYPOTHESIS

A clinical states framework was used to address the hypothesis that definitive phase III trials could not be conducted in this patient population.

PATIENT POPULATION

The Group focused on men with systemic (nonlocalized) recurrence and a defined risk of developing clinically detectable metastases. Models to define systemic versus local recurrence, and risk of metastatic progression were discussed.

INTERVENTION

Therapies that have shown favorable effects in more advanced clinical states; meaningful biologic surrogates of activity linked with efficacy in other tumor types; and/or effects on a target or pathway known to contribute to prostate cancer progression in this state can be considered for evaluation.

OUTCOMES

An intervention-specific posttherapy PSA-based outcome definition that would justify further testing should be described at the outset. Reporting: Trial reports should include a table showing the number of patients who achieve a specific PSA-based outcome, the number who remain enrolled onto the trial, and the number who came off study at different time points. The term PSA response should be abandoned.

TRIAL DESIGN

The phases of drug development for this state are optimizing dose and schedule, demonstration of a treatment effect, and clinical benefit. To move a drug forward should require a high bar that includes no rise in PSA in a defined proportion of patients for a specified period of time at a minimum. Agents that do not produce this effect can only be tested in combination. The preferred end point of clinical benefit is prostate cancer-specific survival; the time to development of metastatic disease is an alternative.

CONCLUSION

Methodology to show that an intervention alters the natural history of prostate cancer is described. At each stage of development, only agents with sufficient activity should be moved forward.