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Clinical decisions based on the test results for prostate-specific antigen often result in overdiagnosis and overtreatment. Multiparametric magnetic resonance imaging (mpMRI) can be used to identify high-grade prostate cancer (HGPCa; Gleason score ≥3 + 4); however, certain limitations remain such as inter-reader variability and false negatives. The combination of mpMRI and prostate cancer (PCa) biomarkers (prostate-specific antigen density, Proclarix, TMPRSS2:ERG gene fusion, Michigan prostate score, ExoDX prostate intelliscore, four kallikrein score, select molecular diagnosis, prostate health index, and prostate health index density) demonstrates high accuracy in the diagnosis of HGPCa, ensuring that patients avoid unnecessary prostate biopsies with a low leakage rate. This manuscript describes the characteristics and diagnostic performance of each biomarker alone and in combination with mpMRI, with the intension to provide a basis for decision-making in the diagnosis and treatment of HGPCa. Additionally, we explored the applicability of the combination protocol to the Asian population.

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OBJECTIVES: This study aimed to assess the efficacy of multiparametric ultrasonography (mpUS) combined with serological examination, as a non-invasive method, in detecting prostate cancer (PCa) or high-grade prostate cancer (HGPCa) respectively. METHODS: A cohort of 245 individuals with clinically suspected PCa were enrolled. All subjects underwent a comprehensive evaluation, including basic data collection, serological testing, mpUS and prostate biopsy. Random Forest (RF) models were developed, and the mean area under the curve (AUC) in 100 cross-validations was used to assess the performance in distinguishing PCa from HGPCa. RESULTS: mpUS features showed significant differences (p < 0.001) between the PCa and non-PCa groups, as well as between the HGPCa and low-grade prostate cancer (LGPCa) groups including prostate-specific antigen density (PSAD), transrectal real-time elastography (TRTE) and intensity difference (ID). The RF model, based on these features, demonstrated an excellent discriminative ability for PCa with a mean area under the curve (AUC) of 0.896. Additionally, another model incorporating free prostate-specific antigen (FPSA) and color Doppler flow imaging (CDFI) achieved a high accuracy in predicting HGPCa with a mean AUC of 0.830. The nomogram derived from these models exhibited excellent individualized prediction of PCa and HGPCa. CONCLUSION: The RF models incorporating mpUS and serological variables achieved satisfactory accuracies in predicting PCa and HGPCa.

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BACKGROUND: A model was built that characterized effects of individual factors on five-year prostate cancer (PCa) risk in the Prostate, Lung, Colon, and Ovarian Cancer Screening Trial (PLCO) and the Selenium and Vitamin E Cancer Prevention Trial (SELECT). This model was validated in a third San Antonio Biomarkers of Risk (SABOR) screening cohort. METHODS: A prediction model for 1- to 5-year risk of developing PCa and Gleason > 7 PCa (HG PCa) was built on PLCO and SELECT using the Cox proportional hazards model adjusting for patient baseline characteristics. Random forests and neural networks were compared to Cox proportional hazard survival models, using the trial datasets for model building and the SABOR cohort for model evaluation. The most accurate prediction model is included in an online calculator. RESULTS: The respective rates of PCa were 8.9%, 7.2%, and 11.1% in PLCO (n = 31,495), SELECT (n = 35,507), and SABOR (n = 1790) over median follow-up of 11.7, 8.1 and 9.0 years. The Cox model showed higher prostate-specific antigen (PSA), BMI and age, and African American race to be associated with PCa and HGPCa. Five-year risk predictions from the combined SELECT and PLCO model effectively discriminated risk in the SABOR cohort with C-index 0.76 (95% CI [0.72, 0.79]) for PCa, and 0.74 (95% CI [0.65,0.83]) for HGPCa. CONCLUSIONS: A 1- to 5-year PCa risk prediction model developed from PLCO and SELECT was validated with SABOR and implemented online. This model can individualize and inform shared screening decisions.

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Grade group 4 and 5 (GG-45) prostate cancer (PCa) patients are at the highest risk of lethal outcomes, yet lack genomic risk stratification for prognosis and treatment selection. Here, we assess whether transcriptomic interactions between tumor immune content score (ICS) and the Decipher genomic classifier can identify most lethal subsets of GG-45 PCa. We utilized whole transcriptome data from 8071 tumor tissue (6071 prostatectomy and 2000 treatment-naïve biopsy samples) to derive four immunogenomic subtypes using ICS and Decipher. When compared across all grade groups, GG-45 samples had the highest proportion of most aggressive subtype-ICSHigh/DecipherHigh. Subsequent analyses within the GG-45 patient samples (n = 1420) revealed that the ICSHigh/DecipherHigh subtype was associated with increased genomic radiosensitivity. Additionally, in a multivariable model (n = 335), ICSHigh/DecipherHigh subtype had a significantly higher risk of distant metastasis (hazard ratio [HR] = 5.41; 95% confidence interval [CI], 2.76-10.6; p ≤ 0.0001) and PCa-specific mortality (HR = 10.6; 95% CI, 4.18-26.94; p ≤ 0.0001) as compared with ICSLow/DecipherLow. The novel immunogenomic subtypes establish a very strong synergistic interaction between ICS and Decipher in identifying GG-45 patients who experience the most lethal outcomes. PATIENT SUMMARY: In this analysis, we identified a novel interaction between the total immune content of prostate tumors and genomic classifier to identify the most lethal subset of patients with grade groups 4 and 5. Our results will aid in the subtyping of aggressive prostate cancer patients who may benefit from combined immune-radiotherapy modalities.

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INTRODUCTION: The aim of this article was to investigate the relationship between statins and the risk of different stages or grades of prostate cancer. METHODS: A comprehensive literature search was performed for articles published until December 18, 2020, on the PubMed, Embase, and the Cochrane Library databases. The pooled relative risk (RR) and 95% confidence interval (CI) were then analyzed using the STATA.16.0 software. RESULTS: A total of 588,055 patients from 14 studies were included in the analysis. We found that the use of statins expressed a significant correlation with a lower risk of advanced prostate cancer (RR = 0.81, 95% CI: 0.73-0.91; RR = 0.86, 95% CI: 0.75-0.99, respectively). However, no evidence suggested that the use of statins was beneficial for the prevention of localized prostate cancer incidence. Similarly, the pooled results also revealed no association between the use of statins and the risk of high-grade and low-grade prostate cancer. CONCLUSION: It has been found that the use of statins is associated with a lower risk of advanced prostate cancer but was not related to the risk of localized, low-grade, or high-grade prostate cancer.

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BACKGROUND: Due to the invasiveness of prostate biopsy, a prediction model of the individual risk of a positive biopsy result could be helpful to guide clinical decision-making. Most existing models are based on transrectal ultrasonography (TRUS)-guided biopsy. On the other hand, transperineal template-guided prostate biopsy (TTPB) has been reported to be more accurate in evaluating prostate cancer. The objective of this study is to develop a prediction model of the detection of high-grade prostate cancer (HGPC) on initial TTPB. RESULT: A total of 1352 out of 3794 (35.6%) patients were diagnosed with prostate cancer, 848 of whom had tumour with Grade Group 2-5. Age, PSA, PV, DRE and f/t PSA are independent predictors of HGPC with p < 0.001. The model showed good discrimination ability (c-index 0.886) and calibration during internal validation and good clinical performance was observed through decision curve analysis. The external validation of CPCC-RC, an existing model, demonstrated that models based on TRUS-guided biopsy may underestimate the risk of HGPC in patients who underwent TTPB. CONCLUSION: We established a prediction model which showed good discrimination ability and calibration in predicting the detection of HGPC by initial TTPB. This model can be used to aid clinical decision making for Chinese patients and other Asian populations with similar genomic backgrounds, after external validations are conducted to further confirm its clinical applicability.

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Prostate cancer is a multifocal disease, but if and how individual prostate tumours influence each other is largely unknown. We therefore explored signs of direct or indirect tumour-tumour interactions in experimental models and patient samples. Low-metastatic AT1 and high-metastatic MatLyLu (MLL) Dunning rat prostate cancer cells were injected into separate lobes of the ventral prostate of immunocompetent rats. AT1 tumours growing in the same prostate as MLL tumours had increased tumour size and proliferation compared to AT1 tumours growing alone. In addition, the vasculature and macrophage density surrounding the AT1 tumours were increased by MLL tumour closeness. In patient prostatectomy samples, selected to contain an index tumour [tumour with the highest grade, International Society of Urological Pathology (ISUP) grade 1, 2, 3 or 4] and a low-grade satellite tumour (ISUP grade 1), cell proliferation in low-grade satellite tumours gradually increased with increasing histological grade of the index tumour. The density of blood vessels and CD68+ macrophages also increased around the low-grade satellite tumour if a high-grade index tumour was present. This suggests that high-grade tumours, by changing the prostate microenvironment, may increase the aggressiveness of low-grade lesions in the organ. Future studies are needed to explore the mechanisms behind tumour-tumour interactions and their clinical importance. © 2020 The Authors. The Journal of Pathology published by John Wiley & Sons, Ltd. on behalf of The Pathological Society of Great Britain and Ireland.

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PURPOSE: To explore the potential value of MRI texture analysis (TA) combined with prostate-related biomarkers to predict high-grade prostate cancer (HGPCa). MATERIALS AND METHODS: Eighty-five patients who underwent MRI scanning, including T2-weighted imaging (T2WI) and diffusion-weighted imaging (DWI) prior to trans-rectal ultrasound (TRUS)-guided core prostate biopsy, were retrospectively enrolled. TA parameters derived from T2WI and DWI, prostate-specific antigen (PSA), and free PSA (fPSA) were compared between the HGPCa and non-high-grade prostate cancer (NHGPCa) groups using independent Student's t-test and the Mann-Whitney U test. Logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the predictive value for HGPCa. RESULTS: Univariate analysis showed that PSA and entropy based on apparent diffusion coefficient (ADC) map differed significantly between the HGPCa and NHGPCa groups and showed higher diagnostic values for HGPCa (area under the curve (AUC) = 82.0% and 80.0%, respectively). Logistic regression and ROC curve analyses revealed that kurtosis, skewness and entropy derived from ADC maps had diagnostic power to predict HGPCa; when the three texture parameters were combined, the area under the ROC curve reached the maximum (AUC = 84.6%; 95% confidence interval (CI): 0.758, 0.935; P = 0.000). CONCLUSION: TA parameters derived from ADC may be a valuable tool in predicting HGPCa. The combination of specific textural parameters extracted from ADC map may be additional tools to predict HGPCa.

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Background: To explore the prediction value of PI-RADS v2 in high-grade prostate cancer and establish a prediction model combined with related variables of prostate cancer. Material and Methods: A total of 316 patients with newly discovered prostate cancer at Zhongnan Hospital of Wuhan University and Renmin Hospital of Wuhan University from December 2017 to August 2019 were enrolled in this study. The clinic information as age, tPSA, fPSA, prostate volume, Gleason score and PI-RADS v2 score have been collected. Univariate analysis was performed based on every variable to investigate the risk factors of high-grade prostate cancer. ROC curves were generated for the risk factors to distinguish the cut-off points. Logistic regression analyses were used to investigate the independent risk factors of high-grade prostate cancer. Nomogram prediction model was generated based on multivariate logistic regression analysis. The calibration curve, ROC curve, leave-one-out cross validation and independent external validation were performed to evaluate the discriminative ability, accuracy and stability of the nomogram prediction model. Results: Of 316 patients, a total of 187 patients were diagnosed as high-grade prostate cancer. Univariate analysis showed tPSA, fPSA, prostate volume, PSAD and PI-RADS v2 score were significantly different between the high- and low-grade prostate cancer patients. Univariate and multivariate logistic regression analyses showed only tPSA, prostate volume and PI-RADS v2 score were the independent risk factors of high-grade prostate cancer. The nomogram could predict the probability of high-grade prostate cancer, with a sensitivity of 79.4% and a specificity of 77.6%. The calibration curve displayed good agreement of the predicted probability with the actual observed probability. AUC of the ROC curve was 0.840 (0.797-0.884). Leave-one-out cross validation indicated the nomogram prediction model could classify 81.4% cases accurately. External data validation was performed with a sensitivity of 80.6% and a specificity of 77.3%, the Kappa value was 0.5755. Conclusions: PI-RADS v2 score had the value in predicting high-grade prostate cancer and the nomogram prediction model may help early diagnose the high risk prostate cancer.

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BACKGROUND/AIM: We have previously found elevated levels of endoglin (CD105) in the prostate cancer (PC) tissue of men with poor prognosis, compared to men with indolent disease. Herein, we examined whether plasma levels of the soluble form of CD105 (sCD105) differ according to the PC grade at diagnosis. PATIENTS AND METHODS: We measured sCD105 in 73 subjects with biopsy-confirmed PC at the Durham, North Carolina, Veteran Affairs Health System. The association between sCD105 and intermediate/high-grade PC risk [Gleason Group (GG) 2-5 vs. 1] was examined using regression models. RESULTS: Of 73 men, 27 had low-grade PC and 46 high-grade PC. Higher GG was linked to lower sCD105 (GG1: 6938 pg/ml, GG2-3: 6150 pg/ml, GG4-5: 5554 pg/ml; p=0.012). On multivariable analysis, lower sCD105 was associated with increased high-grade PC risk (ORper 1000 units=1.33, p=0.028). CONCLUSION: Lower sCD105 levels were associated with intermediate and high-risk PC. Further investigation is warranted in a larger PC cohort.

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Dietary omega-3 fatty acids (ω3), particularly long-chain ω3 (LCω3), have protective effects against prostate cancer (PCa) in experimental studies. Observational studies are conflicting, possibly because of the biomarker used. This study aimed at evaluating associations between grade reclassification and ω3 levels assessed in prostatic tissue, red blood cells (RBC), and diet. We conducted a validation cross-sectional study nested within a phase II clinical trial. We identified 157 men diagnosed with low-risk PCa who underwent a first active surveillance repeat prostate biopsy session. Fatty acid (FA) intake was assessed using a food frequency questionnaire and their levels measured in prostate tissue and RBC. Associations were evaluated using logistic regression. At first repeat biopsy session, 39 (25%) men had high-grade PCa (grade group ≥2). We found that high LCω3-eicosapentaenoic acid (EPA) level in prostate tissue (odds ratio (OR) 0.25; 95% (confidence interval (CI) 0.08-0.79; p-trend = 0.03) was associated with lower odds of high-grade PCa. Similar results were observed for LCω3 dietary intake (OR 0.30; 95% CI 0.11-0.83; p-trend = 0.02) but no association for RBC. LCω3-EPA levels in the target prostate tissue are inversely associated with high-grade PCa in men with low-risk PCa, supporting that prostate tissue FA, but not RBC FA, is a reliable biomarker of PCa risk.

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BACKGROUND: The accuracy of 18F-fluorodeoxyglucose positron emission tomography/computed tomography (FDG-PET/CT) to stage prostate cancer (PCa) is limited. However, Gleason 8-10 PCa and more aggressive metastatic PCa have been shown to exhibit a higher glycolytic activity. OBJECTIVE: To evaluate the potential of intraprostatic FDG uptake to prognose Gleason 8-10 PCa patients prior to prostatectomy, based on tumour intrinsic biology. DESIGN, SETTING, AND PARTICIPANTS: FDG-PET/CT and a bone scan were performed as a staging procedure prior to prostatectomy in 148 consecutive patients diagnosed with PCa with a Gleason sum of ≥8 at biopsy. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: The FDG-PET/CT images were blind reviewed. Lymph node (LN) metastasis and intraprostatic FDG uptake were systematically recorded, and correlated with the patients' clinicopathological characteristics. RESULTS AND LIMITATIONS: FDG-PET/CT detected foci of intraprostatic FDG uptake in 66% of patients. An intraprostatic FDG uptake of maximum intraprostatic standardised uptake value (SUVmax) of ≥4.6 was statistically significantly associated with a higher pathological Gleason ≥8, extracapsular extension, seminal vesicle invasion, and pathological LN metastasis. In multivariate analysis, an intraprostatic SUVmax of ≥4.6 was associated with a two-fold increased risk of biochemical recurrence in the year following surgery. Patients with an intraprostatic SUVmax of ≥4.6 had estimated median biochemical recurrence-free survival (BFS) of 11.3mo compared with 49.5mo for those with a lower SUVmax. Finally, high intraprostatic FDG uptake was associated with shorter time to castration resistance following radical prostatectomy (RP). CONCLUSIONS: Preoperative intraprostatic FDG uptake is an integrator of adverse pathological prognostic factors, predicting BFS and castration resistance following RP in patients with a Gleason score ≥8 PCa at biopsy. These results support the use of preoperative FDG-PET/CT as a tool to distinguish at diagnosis very high-risk Gleason 8-10 PCa patients in whom novel neoadjuvant or adjuvant therapies should be explored. PATIENT SUMMARY: This study shows that an increased use of glucose by prostate cancer cells detected by 18F-fluorodeoxyglucose positron emission tomography molecular imaging can identify aggressive prostate cancers.

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BACKGROUND: Discriminating indolent from clinically significant prostate cancer (PCa) in the initial biopsy setting remains an important issue. Prospectively evaluated diagnostic assays are necessary to ensure efficacy and clinical adoption. OBJECTIVE: Performance and utility assessment of ExoDx Prostate (IntelliScore) (EPI) urine exosome gene expression assay versus standard clinical parameters for discriminating Grade Group (GG) ≥2 PCa from GG1 PCa and benign disease on initial biopsy. DESIGN, SETTING, AND PARTICIPANTS: A two-phase adaptive clinical utility study (NCT03031418) comparing EPI results with biopsy outcomes in men, with age ≥50 yr and prostate-specific antigen (PSA) 2-10ng/ml, scheduled for initial prostate biopsy. After EPI performance assessment during phase I, a clinical implementation document (ie, CarePath) was developed for utilizing the EPI test in phase II, where the biopsy decision is uncertain. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Performance evaluation of the EPI test in patients enrolled in phase I and publication of a consensus CarePath for phase II. RESULTS AND LIMITATIONS: In a total of 503 patients, with median age of 64 yr, median PSA 5.4ng/ml, 14% African American, 70% Caucasian, 53% positive biopsy rate (22% GG1, 17% GG2, and 15% ≥ GG3), EPI was superior to an optimized model of standard clinical parameters with an area under the curve (AUC) 0.70 versus 0.62, respectively, comparable with previously published results (n=519 patients, EPI AUC 0.71). Validated cut-point 15.6 would avoid 26% of unnecessary prostate biopsies and 20% of total biopsies, with negative predictive value (NPV) 89% and missing 7% of ≥GG2 PCa. Alternative cut-point 20 would avoid 40% of unnecessary biopsies and 31% of total biopsies, with NPV 89% and missing 11% of ≥GG2 PCa. The clinical investigators reached consensus recommending use of the 15.6 cut-point for phase II. Outcome of the decision impact cohort in phase II will be reported separately. CONCLUSIONS: EPI is a noninvasive, easy-to-use, gene expression urine assay, which has now been successfully validated in over 1000 patients across two prospective validation trials to stratify risk of ≥GG2 from GG1 cancer and benign disease. The test improves identification of patients with higher grade disease and would reduce the total number of unnecessary biopsies. PATIENT SUMMARY: It is challenging to predict which men are likely to have high-grade prostate cancer (PCa) at initial biopsy with prostate-specific antigen 2-10ng/ml. This study further demonstrates that the ExoDx Prostate (IntelliScore) test can predict ≥GG2 PCa at initial biopsy and defer unnecessary biopsies better than existing risk calculator's and standard clinical data.

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The 4Kscore® Test (OPKO Diagnostics, Woburn, MA) is a blood test utilized prior to a prostate biopsy to determine a patient's risk of high-grade prostate cancer (PCa) should the biopsy be performed, thus providing critical information in the clinical management of men with a suspicious prostate-specific antigen value or digital rectal examination result. Multiple US and European clinical studies confirmed that a prebiopsy 4Kscore Test has a high degree of discrimination for a subsequent discovery of high-grade (Gleason score ≥7) PCa. The aim of this study was to evaluate the predictive accuracy of the 4Kscore Test to discriminate between patients with and without high-grade PCa based on published clinical validation studies. A systematic review and meta-analysis of the eligible 4Kscore Test clinical validation studies was conducted. The pooled area under the curve (AUC) of the 4Kscore Test as reported from all the studies, and the heterogeneity among these studies were analyzed and repeated for subgroups of the studies. Twelve clinical validation studies were included in the meta-analysis, comprising a total of 11,134 patients. The pooled AUC to discriminate for high-grade PCa for all 12 studies was 0.81 (fixed effects 95% CI, 0.80-0.83). Restricting the analysis to the six publications that used the contemporary 4Kscore Test algorithm led to very similar results (AUC 0.81; 95% CI, 0.79-0.83). Heterogeneity was high among all of the 12 studies, as well as among the six publications that used the contemporary 4Kscore Test (Cochrane's Q test, p = 0.001 for both); however, in both cases, after exclusion of a single outlying study with a much lower AUC, heterogeneity was no longer significant (p = 0.08 and p = 0.21). The pooled estimate of 4Kscore Test discrimination (AUC) for high-grade PCa is >0.80, and is consistent across multiple US and European clinical validation studies.

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INTRODUCTION: To prevent the overdiagnosis and overtreatment of prostate cancer (PC), therapeutic strategies have been established such as active surveillance and focal therapy, as well as methods for clarifying the diagnosis of high-grade prostate cancer (HGPC) (defined as a Gleason score ≥7), such as multiparametric magnetic resonance imaging and new markers such as the 4Kscore test (4KsT). By means of a pilot study, we aim to test the ability of the 4KsT to identify HGPC in prostate biopsies (Bx) and compare the test with other multivariate prognostic models such as the Prostate Cancer Prevention Trial Risk Calculator 2.0 (PCPTRC 2.0) and the European Research Screening Prostate Cancer Risk Calculator 4 (ERSPC-RC 4). MATERIAL AND METHODS: Fifty-one patients underwent a prostate Bx according to standard clinical practice, with a minimum of 10 cores. The diagnosis of HGPC was agreed upon by 4 uropathologists. We compared the predictions from the various models by using the Mann-Whitney U test, area under the ROC curve (AUC) (DeLong test), probability density function (PDF), box plots and clinical utility curves. RESULTS: Forty-three percent of the patients had PC, and 23.5% had HGPC. The medians of probability for the 4KsT, PCPTRC 2.0 and ERSPC-RC 4 were significantly different between the patients with HGPC and those without HGPC (p≤.022) and were more differentiated in the case of 4KsT (51.5% for HGPC [25-75 percentile: 25-80.5%] vs. 16% [P 25-75: 8-26.5%] for non-HGPC; p=.002). All models presented AUCs above 0.7, with no significant differences between any of them and 4KsT (p≥.20). The PDF and box plots showed good discriminative ability, especially in the ERSPC-RC 4 and 4KsT models. The utility curves showed how a cutoff of 9% for 4KsT identified all cases of HGPC and provided a 22% savings in biopsies, which is similar to what occurs with the ERSPC-RC 4 models and a cutoff of 3%. CONCLUSIONS: The assessed predictive models offer good discriminative ability for HGPCs in Bx. The 4KsT is a good classification model as a whole, followed by ERSPC-RC 4 and PCPTRC 2.0. The clinical utility curves help suggest cutoff points for clinical decisions: 9% for 4KsT and 3% for ERSPC-RC 4. This preliminary study should be interpreted with caution due to its limited sample size.

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Better biomarkers that can discriminate between aggressive and indolent phenotypes of prostate cancer are urgently needed. In the first 20 years of the prostate-specific antigen (PSA) era, screening for prostate cancer has successfully reduced prostate cancer mortality, but has led to significant problems with overdiagnosis and overtreatment. As a result, many men are subjected to unnecessary prostate biopsies and overtreatment of indolent cancer in order to save one man from dying of prostate cancer. A novel blood test known as the 4Kscore® Test (OPKO Lab, Nashville, TN) incorporates a panel of four kallikrein protein biomarkers (total PSA, free PSA, intact PSA, and human kallikrein-related peptidase 2) and other clinical information in an algorithm that provides a percent risk for a high-grade (Gleason score ≥ 7) cancer on biopsy. In 10 peer-reviewed publications, the four kallikrein biomarkers and algorithm of the 4Kscore Test have been shown to improve the prediction not only of biopsy histopathology, but also surgical pathology and occurrence of aggressive, metastatic disease. Recently, a blinded prospective trial of the 4Kscore Test was conducted across the United States among 1012 men. The 4Kscore Test replicated previous European results showing accuracy in predicting biopsy outcome of Gleason score ≥ 7. In a recent case-control study nested within a population-based cohort from Västerbotten, Sweden, the four kallikrein biomarkers of the 4Kscore Test also predicted the risk for aggressive prostate cancer that metastasized within 20 years after the test was administered. These results indicate that men with an abnormal PSA or digital rectal examination result, and for whom an initial or repeat prostate biopsy is being considered, would benefit from a reflex 4Kscore Test to add important information to the clinical decision-making process. A high-risk 4Kscore Test result may be used to select men with a high probability of aggressive prostate cancer who would benefit from a biopsy of the prostate to prevent an adverse and potentially lethal outcome from prostate cancer. Men with a low 4Kscore Test result may safely defer biopsy.

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BACKGROUND: There is evidence that obesity is associated with an aggressive prostate cancer (PC). Furthermore, preclinical studies suggest that oestrogens may play a pivotal role in this context. The biological processes underlying these observations are not fully understood. We prospectively evaluated whether obesity and/or preoperative estradiol levels are associated with high-grade cancer in patients with clinically localized PC at the time they underwent radical retropubic prostatectomy (RRP). METHODS: Preoperative sex hormone serum 17ß-estradiol (E2) as well as body mass index (BMI) and waist circumference (WC) were assessed in a cohort of 746 consecutive men treated with RP from February 2011 to October 2014. The data were correlated with patient-specific and clinicopathologic variables. RESULTS: A total of 746 patients underwent RRP. Median age was 68.0 years. Median E2 serum level was 18.3 ng/l (IQR 12.9-24.2 ng/l). Median BMI was 26.6 kg/m(2) (IQR 24.6-29.1 kg/m(2)), and the median WC was 103 cm (IQR 96-110 cm). Serum E2 below or above the normal range was not found more frequently in obese patients (high BMI: p = 0.62; large WC: p = 0.83). E2 was not associated with BMI in our cohort of patients (r = 0.07, p = 0.10) or WC (r = 0.07, p = 0.10). There was no association between preoperative serum E2 levels and tumour stage (p = 0.86, Fisher's exact), tumour grade (p = 0.37), lymph node involvement (p = 0.59) or Gleason score (p = 0.44). However, obesity correlated with tumour stage and grade (p = 0.036, Fisher's exact) and nodal metastasis (p = 0.039, Fishers' exact). CONCLUSION: Pretreatment serum 17ß-estradiol (E2) cannot be considered as a suitable marker for aggressive tumour disease in patients with localized prostate cancer.

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BACKGROUND: High calcium intake has been associated with an increased risk of advanced-stage and high-grade prostate cancer. Several studies have found a positive association between phosphorus intake and prostate cancer risk. OBJECTIVE: We investigated the joint association between calcium and phosphorus and risk of prostate cancer in the Health Professionals Follow-Up Study, with a focus on lethal and high-grade disease. DESIGN: In total, 47,885 men in the cohort reported diet data in 1986 and every 4 y thereafter. From 1986 to 2010, 5861 cases of prostate cancer were identified, including 789 lethal cancers (fatal or metastatic). We used Cox proportional hazards models to assess the association between calcium and phosphorus intake and prostate cancer, with adjustment for potential confounding. RESULTS: Calcium intakes >2000 mg/d were associated with greater risk of total prostate cancer and lethal and high-grade cancers. These associations were attenuated and no longer statistically significant when phosphorus intake was adjusted for. Phosphorus intake was associated with greater risk of total, lethal, and high-grade cancers, independent of calcium and intakes of red meat, white meat, dairy, and fish. In latency analysis, calcium and phosphorus had independent effects for different time periods between exposure and diagnosis. Calcium intake was associated with an increased risk of advanced-stage and high-grade disease 12-16 y after exposure, whereas high phosphorus was associated with increased risk of advanced-stage and high-grade disease 0-8 y after exposure. CONCLUSIONS: Phosphorus is independently associated with risk of lethal and high-grade prostate cancer. Calcium may not have a strong independent effect on prostate cancer risk except with long latency periods.

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