Compliance with biopsy recommendations of a prostate cancer risk calculator

External validation of two MRI-based risk calculators in prostate cancer diagnosis

BACKGROUND

The diagnosis of (significant) prostate cancer ((s)PC) is impeded by overdiagnosis and unnecessary biopsy. Risk calculators (RC) have been developed to mitigate these issues. Contemporary RCs integrate clinical characteristics with mpMRI findings.

OBJECTIVE

To validate two of these models-the MRI-ERSPC-RC-3/4 and the risk model of van Leeuwen.

METHODS

265 men with clinical suspicion of PC were enrolled. Every patient received a prebiopsy mpMRI, which was reported according to PI-RADS v2.1, followed by MRI/TRUS fusion-biopsy. Cancers with ISUP grade ≥ 2 were classified as sPC.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

Statistical analysis was performed by comparing discrimination, calibration, and clinical utility RESULTS: There was no significant difference in discrimination between the RCs. The MRI-ERSPC-RC-3/4-RC showed a nearly ideal calibration-slope (0.94; 95% CI 0.68-1.20) than the van Leeuwen model (0.70; 95% CI 0.52-0.88). Within a threshold range up to 9% for a sPC, the MRI-ERSPC-RC-3/4-RC shows a greater net benefit than the van Leeuwen model. From 10 to 15%, the van Leeuwen model showed a higher net benefit compared to the MRI-ERSP-3/4-RC. For a risk threshold of 15%, the van Leeuwen model would avoid 24% vs. 14% compared to the MRI-ERSPC-RC-3/4 model; 6% vs. 5% sPC would be overlooked, respectively.

CONCLUSION

Both risk models supply accurate results and reduce the number of biopsies and basically no sPC were overlooked. The van Leeuwen model suggests a better balance between unnecessary biopsies and overlooked sPC at thresholds range of 10-15%. The MRI-ERSPC-RC-3/4 risk model provides better overall calibration.

Integrating inflammatory serum biomarkers into a risk calculator for prostate cancer detection

Improved prostate cancer detection methods would avoid over-diagnosis of clinically indolent disease informing appropriate treatment decisions. The aims of this study were to investigate the role of a panel of Inflammation biomarkers to inform the need for a biopsy to diagnose prostate cancer. Peripheral blood serum obtained from 436 men undergoing transrectal ultrasound guided biopsy were assessed for a panel of 18 inflammatory serum biomarkers in addition to Total and Free Prostate Specific Antigen (PSA). This panel was integrated into a previously developed Irish clinical risk calculator (IPRC) for the detection of prostate cancer and high-grade prostate cancer (Gleason Score ≥ 7). Using logistic regression and multinomial regression methods, two models (Logst-RC and Multi-RC) were developed considering linear and nonlinear effects of the panel in conjunction with clinical and demographic parameters for determination of the two endpoints. Both models significantly improved the predictive ability of the clinical model for detection of prostate cancer (from 0.656 to 0.731 for Logst-RC and 0.713 for Multi-RC) and high-grade prostate cancer (from 0.716 to 0.785 for Logst-RC and 0.767 for Multi-RC) and demonstrated higher clinical net benefit. This improved discriminatory power and clinical utility may allow for individualised risk stratification improving clinical decision making.

Real-world implementation of precision psychiatry: Transdiagnostic risk calculator for the automatic detection of individuals at-risk of psychosis

BACKGROUND

Risk estimation models integrated into Electronic Health Records (EHRs) can deliver innovative approaches in psychiatry, but clinicians' endorsement and their real-world usability are unknown. This study aimed to investigate the real-world feasibility of implementing an individualised, transdiagnostic risk calculator to automatically screen EHRs and detect individuals at-risk for psychosis.

METHODS

Feasibility implementation study encompassing an in-vitro phase (March 2018 to May 2018) and in-vivo phase (May 2018 to April 2019). The in-vitro phase addressed implementation barriers and embedded the risk calculator (predictors: age, gender, ethnicity, index cluster diagnosis, age*gender) into the local EHR. The in-vivo phase investigated the real-world feasibility of screening individuals accessing secondary mental healthcare at the South London and Maudsley NHS Trust. The primary outcome was adherence of clinicians to automatic EHR screening, defined by the proportion of clinicians who responded to alerts from the risk calculator, over those contacted.

RESULTS

In-vitro phase: implementation barriers were identified/overcome with clinician and service user engagement, and the calculator was successfully integrated into the local EHR through the CogStack platform. In-vivo phase: 3722 individuals were automatically screened and 115 were detected. Clinician adherence was 74% without outreach and 85% with outreach. One-third of clinicians responded to the first email (37.1%) or phone calls (33.7%). Among those detected, cumulative risk of developing psychosis was 12% at six-month follow-up.

CONCLUSION

This is the first implementation study suggesting that combining precision psychiatry and EHR methods to improve detection of individuals with emerging psychosis is feasible. Future psychiatric implementation research is urgently needed.

A risk calculator to inform the need for a prostate biopsy: a rapid access clinic cohort

BACKGROUND

Prostate cancer (PCa) represents a significant healthcare problem. The critical clinical question is the need for a biopsy. Accurate risk stratification of patients before a biopsy can allow for individualised risk stratification thus improving clinical decision making. This study aims to build a risk calculator to inform the need for a prostate biopsy.

METHODS

Using the clinical information of 4801 patients an Irish Prostate Cancer Risk Calculator (IPRC) for diagnosis of PCa and high grade (Gleason ≥7) was created using a binary regression model including age, digital rectal examination, family history of PCa, negative prior biopsy and Prostate-specific antigen (PSA) level as risk factors. The discrimination ability of the risk calculator is internally validated using cross validation to reduce overfitting, and its performance compared with PSA and the American risk calculator (PCPT), Prostate Biopsy Collaborative Group (PBCG) and European risk calculator (ERSPC) using various performance outcome summaries. In a subgroup of 2970 patients, prostate volume was included. Separate risk calculators including the prostate volume (IPRCv) for the diagnosis of PCa (and high-grade PCa) was created.

RESULTS

IPRC area under the curve (AUC) for the prediction of PCa and high-grade PCa was 0.6741 (95% CI, 0.6591 to 0.6890) and 0.7214 (95% CI, 0.7018 to 0.7409) respectively. This significantly outperforms the predictive ability of cancer detection for PSA (0.5948), PCPT (0.6304), PBCG (0.6528) and ERSPC (0.6502) risk calculators; and also, for detecting high-grade cancer for PSA (0.6623) and PCPT (0.6804) but there was no significant improvement for PBCG (0.7185) and ERSPC (0.7140). The inclusion of prostate volume into the risk calculator significantly improved the AUC for cancer detection (AUC = 0.7298; 95% CI, 0.7119 to 0.7478), but not for high-grade cancer (AUC = 0.7256; 95% CI, 0.7017 to 0.7495). The risk calculator also demonstrated an increased net benefit on decision curve analysis.

CONCLUSION

The risk calculator developed has advantages over prior risk stratification of prostate cancer patients before the biopsy. It will reduce the number of men requiring a biopsy and their exposure to its side effects. The interactive tools developed are beneficial to translate the risk calculator into practice and allows for clarity in the clinical recommendations.

Prediction of High-grade Prostate Cancer Following Multiparametric Magnetic Resonance Imaging: Improving the Rotterdam European Randomized Study of Screening for Prostate Cancer Risk Calculators

BACKGROUND

The Rotterdam European Randomized Study of Screening for Prostate Cancer risk calculators (ERSPC-RCs) help to avoid unnecessary transrectal ultrasound-guided systematic biopsies (TRUS-Bx). Multivariable risk stratification could also avoid unnecessary biopsies following multiparametric magnetic resonance imaging (mpMRI).

OBJECTIVE

To construct MRI-ERSPC-RCs for the prediction of any- and high-grade (Gleason score ≥3 + 4) prostate cancer (PCa) in 12-core TRUS-Bx±MRI-targeted biopsy (MRI-TBx) by adding Prostate Imaging Reporting and Data System (PI-RADS) and age as parameters to the ERSPC-RC3 (biopsy-naïve men) and ERSPC-RC4 (previously biopsied men).

DESIGN, SETTING, AND PARTICIPANTS

A total of 961 men received mpMRI and 12-core TRUS-Bx±MRI-TBx (in case of PI-RADS ≥3) in five institutions. Data of 504 biopsy-naïve and 457 previously biopsied men were used to adjust the ERSPC-RC3 and ERSPC-RC4.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

Logistic regression models were constructed. The areas under the curve (AUCs) of the original ERSPC-RCs and MRI-ERSPC-RCs (including PI-RADS and age) for any- and high-grade PCa were compared. Decision curve analysis was performed to assess the clinical utility of the MRI-ERSPC-RCs.

RESULTS AND LIMITATIONS

MRI-ERSPC-RC3 had a significantly higher AUC for high-grade PCa compared with the ERSPC-RC3: 0.84 (95% confidence interval [CI] 0.81-0.88) versus 0.76 (95% CI 0.71-0.80, p<0.01). Similarly, MRI-ERSPC-RC4 had a higher AUC for high-grade PCa compared with the ERSPC-RC4: 0.85 (95% CI 0.81-0.89) versus 0.74 (95% CI 0.69-0.79, p<0.01). Unlike for the MRI-ERSPC-RC3, decision curve analysis showed clear net benefit of the MRI-ERSPC-RC4 at a high-grade PCa risk threshold of ≥5%. Using a ≥10% high-grade PCa risk threshold to biopsy for the MRI-ERSPC-RC4, 36% biopsies are saved, missing low- and high-grade PCa, respectively, in 15% and 4% of men who are not biopsied.

CONCLUSIONS

We adjusted the ERSPC-RCs for the prediction of any- and high-grade PCa in 12-core TRUS-Bx±MRI-TBx. Although the ability of the MRI-ERSPC-RC3 for biopsy-naïve men to avoid biopsies remains questionable, application of the MRI-ERSPC-RC4 in previously biopsied men in our cohort would have avoided 36% of biopsies, missing high-grade PCa in 4% of men who would not have received a biopsy.

PATIENT SUMMARY

We have constructed magnetic resonance imaging-based Rotterdam European Randomized study of Screening for Prostate Cancer (MRI-ERSPC) risk calculators for prostate cancer prediction in transrectal ultrasound-guided biopsy and MRI-targeted biopsy by incorporating age and Prostate Imaging Reporting and Data System score into the original ERSPC risk calculators. The MRI-ERSPC risk calculator for previously biopsied men could be used to avoid one-third of biopsies following MRI.

Multivariable risk-based patient selection for prostate biopsy in a primary health care setting: referral rate and biopsy results from a urology outpatient clinic

Background

According to their guidelines, Dutch general practitioners (GPs) refer men with prostate-specific antigen (PSA) level ≥3.0 ng/mL to the urologist for risk-based patient selection for prostate biopsy using the Rotterdam Prostate Cancer Risk Calculator (RPCRC). Use of the RPCRC in primary care could optimize the diagnostic pathway even further by reducing unnecessary referrals. To investigate this, we calculated the risk and assessed the rate of men referred to the urologist with PSA level ≥3.0 ng/mL by implementing the RPCRC in a primary health care setting.

Methods

In January 2014, an exploratory study was initiated in collaboration with the primary health care facility of the GP laboratory in Rotterdam. GPs were given the possibility to refer men with a suspicion of prostate cancer (PCa) or a screening wish to this primary care facility (STAR-SHL) where further assessment was performed by specially trained personnel. Risk-based advice on referral to the urologist was given to the GP on the basis of the RPCRC results. If requested, advice on the treatment of lower urinary tract symptoms (LUTS) was provided. All men signed informed consent.

Results

Between January 2014 and September 2017, a total of 243 men, median age 64 [interquartile range (IQR), 57-70] years were referred for a consultation at the primary care facility. Of the 108 men with PSA level ≥3.0 ng/mL and a referral related to PCa, GPs were advised to refer 58 men to the urologist (54%). Of the men with available follow-up (FU) data [n=187, median FU, 16 (IQR, 9-25) months] 54 men were considered high-risk (i.e., had an elevated risk of PCa as calculated by the RPCRC). Of these men, 51 (94%) were actually referred to secondary care by their GP, and so far 38 men underwent biopsy. PCa was detected in 30 men [47% had Gleason score (GS) ≥3+4 PCa], translating to an overall positive predictive value (PPV) of 79%. Within the available FU time, 2 out of 38 (5%) men with PSA level ≥3.0 ng/mL which were considered low-risk have been diagnosed with GS 3+3 PCa.

Conclusions

Risk-stratification with the RPCRC in a primary health care setting could prevent almost half of referrals of men with PSA level ≥3.0 ng/mL to the urologist. In more than three-quarters of men referred for prostate biopsy, the suspicion of PCa was confirmed and almost half of men had clinically significant PCa (GS ≥3+4 PCa). These data show a huge potential for multivariable risk-stratification in primary care.

eHealth and mHealth in prostate cancer detection and active surveillance

eHealth and mobile health (mHealth) offer patients, healthcare providers, researchers, and policy makers new potential to improve wellness, practice prevention and reduce suffering from diseases. While the eHealth market is growing to an expected US $26 billion, its potential in the field of Urology is still underused. Research has shown that currently only 176 apps (of the 300,000 medical apps available) were found in the Apple App Store and Google Play Store, of which 20 were prostate cancer related. Three good examples of eHealth/mHealth applications are the Rotterdam Prostate Cancer Risk Calculator (RPCRC) website and app, the Prostate cancer Research International Active Surveillance (PRIAS) website and the Follow MyPSA app for men on active surveillance for prostate cancer: they are tools with a clear vision that offer true added value in daily clinical practice and which positively influence healthcare beyond borders. To increase the uptake of eHealth applications in the coming years, it is important to involve professionals in their design and development, and to guarantee the safety and privacy of its users and their data.

Prostate Health Index improves multivariable risk prediction of aggressive prostate cancer

OBJECTIVE

To examine the use of the Prostate Health Index (PHI) as a continuous variable in multivariable risk assessment for aggressive prostate cancer in a large multicentre US study.

MATERIALS AND METHODS

The study population included 728 men, with prostate-specific antigen (PSA) levels of 2-10 ng/mL and a negative digital rectal examination, enrolled in a prospective, multi-site early detection trial. The primary endpoint was aggressive prostate cancer, defined as biopsy Gleason score ≥7. First, we evaluated whether the addition of PHI improves the performance of currently available risk calculators (the Prostate Cancer Prevention Trial [PCPT] and European Randomised Study of Screening for Prostate Cancer [ERSPC] risk calculators). We also designed and internally validated a new PHI-based multivariable predictive model, and created a nomogram.

RESULTS

Of 728 men undergoing biopsy, 118 (16.2%) had aggressive prostate cancer. The PHI predicted the risk of aggressive prostate cancer across the spectrum of values. Adding PHI significantly improved the predictive accuracy of the PCPT and ERSPC risk calculators for aggressive disease. A new model was created using age, previous biopsy, prostate volume, PSA and PHI, with an area under the curve of 0.746. The bootstrap-corrected model showed good calibration with observed risk for aggressive prostate cancer and had net benefit on decision-curve analysis.

CONCLUSION

Using PHI as part of multivariable risk assessment leads to a significant improvement in the detection of aggressive prostate cancer, potentially reducing harms from unnecessary prostate biopsy and overdiagnosis.

Characteristics of Prostate Cancer Found at Fifth Screening in the European Randomized Study of Screening for Prostate Cancer Rotterdam: Can We Selectively Detect High-grade Prostate Cancer with Upfront Multivariable Risk Stratification and Magnetic Resonance Imaging?

BACKGROUND

The harm of screening (unnecessary biopsies and overdiagnosis) generally outweighs the benefit of reducing prostate cancer (PCa) mortality in men aged ≥70 yr. Patient selection for biopsy using risk stratification and magnetic resonance imaging (MRI) may improve this benefit-to-harm ratio.

OBJECTIVE

To assess the potential of a risk-based strategy including MRI to selectively identify men aged ≥70 yr with high-grade PCa.

DESIGN, SETTING, AND PARTICIPANTS

Three hundred and thirty-seven men with prostate-specific antigen ≥3.0 ng/ml at a fifth screening (71-75 yr) in the European Randomized study of Screening for Prostate Cancer Rotterdam were biopsied. One hundred and seventy-nine men received six-core transrectal ultrasound biopsy (TRUS-Bx), while 158 men received MRI, 12-core TRUS-Bx, and fusion TBx in case of Prostate Imaging Reporting and Data System ≥3 lesions.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

The primary outcome was the overall, low-grade (Gleason Score 3+3) and high-grade (Gleason Score ≥ 3+4) PCa rate. Secondary outcome was the low- and high-grade PCa rate detected by six-core TRUS-Bx, 12-core TRUS-Bx, and MRI ± TBx. Tertiary outcome was the reduction of biopsies and low-grade PCa detection by upfront risk stratification with the Rotterdam Prostate Cancer Risk Calculator 4.

RESULTS AND LIMITATIONS

Fifty-five percent of men were previously biopsied. The overall, low-grade, and high-grade PCa rates in biopsy naïve men were 48%, 27%, and 22%, respectively. In previously biopsied men these PCa rates were 25%, 20%, and 5%. Sextant TRUS-Bx, 12-core TRUS-Bx, and MRI ± TBx had a similar high-grade PCa rate (11%, 12%, and 11%) but a significantly different low-grade PCa rate (17%, 28%, and 7%). Rotterdam Prostate Cancer Risk Calculator 4-based stratification combined with 12-core TRUS-Bx ± MRI-TBx would have avoided 65% of biopsies and 68% of low-grade PCa while detecting an equal percentage of high-grade PCa (83%) compared with a TRUS-Bx all men approach (79%).

CONCLUSIONS

After four repeated screens and ≥1 previous biopsies in half of men, a significant proportion of men aged ≥70 yr still harbor high-grade PCa. Upfront risk stratification and the combination of MRI and TRUS-Bx would have avoided two-thirds of biopsies and low-grade PCa diagnoses in our cohort, while maintaining the high-grade PCa detection of a TRUS-Bx all men approach. Further studies are needed to verify these results.

PATIENT SUMMARY

Prostate cancer screening reduces mortality but is accompanied by unnecessary biopsies and overdiagnosis of nonaggressive tumors, especially in repeatedly screened elderly men. To tackle these drawbacks screening should consist of an upfront risk-assessment followed by magnetic resonance imaging and transrectal ultrasound-guided biopsy.

Clinical Consultation Guide: How to Optimize the Use of Prostate-specific Antigen in the Current Era

Optimizing the benefits versus harms of prostate-specific antigen screening can be achieved through stratifying screening and biopsy. This clinical consultation guide provides the scientific background and evidence-based recommendations.

Prostate-specific antigen-based prostate cancer screening: Past and future

Prostate-specific antigen-based prostate cancer screening remains a controversial topic. Up to now, there is worldwide consensus on the statement that the harms of population-based screening, mainly as a result of overdiagnosis (the detection of clinically insignificant tumors that would have never caused any symptoms), outweigh the benefits. However, worldwide opportunistic screening takes place on a wide scale. The European Randomized Study of Screening for Prostate Cancer showed a reduction in prostate cancer mortality through prostate-specific antigen based-screening. These population-based data need to be individualized in order to avoid screening in those who cannot benefit and start screening in those who will. For now, lacking a more optimal screening approach, screening should only be started after the process of shared decision-making. The focus of future research is the reduction of unnecessary testing and overdiagnosis by further research to better biomarkers and the value of the multiparametric magnetic resonance imaging, potentially combined in already existing prostate-specific antigen-based multivariate risk prediction models.

Role of PCA3 test in clinical decision making for prostate cancer diagnosis

AIM: To assess the role of PCA3 urine test in the management of patients with suspected prostate cancer after repeat negative prostate biopsies.

METHODS: Patients with suspected prostate cancer either due to high or rising prostate specific antigen (PSA) levels and with a history of prostate biopsy who were candidates for repeat procedure were prospectively recruited to undergo PCA3 urine test. The recommendations on further management including the decision whether to proceed or not to the biopsy were made based on the PCA3 score. Patients’ adherence with the recommendations and influence of the PCA3 test on clinical decision making were assessed. The contribution of the multivariate model was measured with a decision curve analysis.

RESULTS: Three hundred and fifty-six patients were recruited to the study and underwent the PCA3 test. Twenty-six percent of 263 patients underwent prostate biopsy despite the low risk designation by PCA3 and 30% of 93 men did not proceed to biopsy despite a high risk result, rendering overall adherence of 73%. The variables that significantly correlated with adherence were positive family history of prostate cancer and PSA more than 10 ng/mL. Pre-test clinical stage, the number and the results of previous biopsies were not associated with the adherence. The decision curve analysis gave identical results for cut-off points of 25 and 35. On multivariate analysis the model that included PCA3 score, serum PSA, family history and result of the previous biopsy best performed with Area Under the Curve of 0.77.

CONCLUSION: PCA3 urine test markedly outperforms PSA in a repeat biopsy setting. Urologists and patients demonstrate substantial confidence in this analysis and tend to follow its recommendations.

Demographic and clinical factors associated with referrals and compliance to biopsy of oral and maxillofacial lesions

BACKGROUND

The gold standard for diagnosing oral disease is tissue biopsy. Data regarding compliance with advised oral and maxillofacial (OMF) biopsy are scarce.

PURPOSE

To quantify compliance and evaluate the demographics and clinical factors associated with referrals and compliance with OMF biopsy procedures.

METHODS

Medical records of military personnel referred for a biopsy (RB; N = 669) of OMF lesions over a 4-year period were studied retrospectively. These patients were divided into performed the biopsy (PB; N = 386) and not perform biopsy (NPB; N = 283) groups. Demographic and clinical features were analyzed, and demographics were compared to a control group of general military personnel (N > 100,000).

RESULTS

The RB group differed from the control group regarding age >21 (OR = 1.681, P < 0.001) and education >12 years of schooling (OR = 1.545, P < 0.001). Differences between the PB and NPB groups related to the clinical features of the lesion but not to demographic parameters. Exophytic and suspected potentially malignant/malignant lesions were positively associated with higher compliance to biopsy (OR = 1.75, P = 0.004 and OR = 2.18, P = 0.017, respectively).

CONCLUSION

Referrals to biopsy of OMF lesions are significantly influenced by age and education, whereas compliance is influenced by clinical features or suspected malignancy. Clinicians and health authorities should be aware of non-compliance, enhance awareness to biopsy as the gold standard in the diagnostic workup of OMF lesions, and closely monitor compliance patterns of patients with clinical and demographic risk factors.

Determination of common urine substances as an assay for improving prostate carcinoma diagnostics

Recently, interest in the identification of non-invasive markers for prostate carcinoma detectable in the urine of patients has increased. In this study, we monitored the abundance of potential non-invasive markers of prostate carcinoma such as amino acid sarcosine, involved in the metabolism of amino acids and methylation processes, ongoing during the progression of prostate carcinoma. in addition, other potential prostate tumor markers were studied. The most significant markers, prostate-specific antigen (PSA) and free PSA (fPSA), already used in clinical diagnosis, were analyzed using an immunoenzymometric assay. Whole amino acid profiles were also determined to evaluate the status of amino acids in patient urine samples and to elucidate the possibility of their utilization for prostate carcinoma diagnosis. To obtain the maximum amount of information, the biochemical parameters were determined using various spectrophotometric methods. All results were subjected to statistical processing for revealing different correlations between the studied parameters. We observed alterations in most of the analyzed substances. Based on the results obtained, we concluded that the specificity of prostate carcinoma diagnosis could be improved by determination of common urine metabolites, since we compiled a set of tests, including the analysis of sarcosine, proline, PSA and uric acid in the urine. These metabolites were not observed in the urine obtained from healthy subjects, while their levels were elevated in all patients suffering from prostate carcinoma.

Can Western based online prostate cancer risk calculators be used to predict prostate cancer after prostate biopsy for the Korean population?

PURPOSE

To access the predictive value of the European Randomized Screening of Prostate Cancer Risk Calculator (ERSPC-RC) and the Prostate Cancer Prevention Trial Risk Calculator (PCPT-RC) in the Korean population.

MATERIALS AND METHODS

We retrospectively analyzed the data of 517 men who underwent transrectal ultrasound guided prostate biopsy between January 2008 and November 2010. Simple and multiple logistic regression analysis were performed to compare the result of prostate biopsy. Area under the receiver operating characteristics curves (AUC-ROC) and calibration plots were prepared for further analysis to compare the risk calculators and other clinical variables.

RESULTS

Prostate cancer was diagnosed in 125 (24.1%) men. For prostate cancer prediction, the area under curve (AUC) of the ERSPC-RC was 77.4%. This result was significantly greater than the AUCs of the PCPT-RC and the prostate-specific antigen (PSA) (64.5% and 64.1%, respectively, p<0.01), but not significantly different from the AUC of the PSA density (PSAD) (76.1%, p=0.540). When the results of the calibration plots were compared, the ERSPC-RC plot was more constant than that of PSAD.

CONCLUSION

The ERSPC-RC was better than PCPT-RC and PSA in predicting prostate cancer risk in the present study. However, the difference in performance between the ERSPC-RC and PSAD was not significant. Therefore, the Western based prostate cancer risk calculators are not useful for urologists in predicting prostate cancer in the Korean population.

Effect of sarcosine on antioxidant parameters and metallothionein content in the PC-3 prostate cancer cell line

Sarcosine is currently one of the most discussed markers of prostate cancer. It is involved in amino acid metabolism and methylation processes that occur during the progression of prostate cancer. In this study, we monitored the effect of the addition of sarcosine (0; 10; 250; 500; 1,000 and 1,500 µM) in a time-dependent manner (0-72 h) on the PC-3 prostate cancer cell line. For the assessment of cell viability, the commonly used MTT test was employed. Furthermore, ion-exchange liquid chromatography was used for the determination of sarcosine content in the PC-3 cells. We also determined metallothionein (MT) levels by chip capillary electrophoresis and Brdicka reaction in the cells treated with sarcosine. Sarcosine levels in the cells increased in a concentration-dependent manner levels increased from only 270 nM with the lowest applied concentration of sarcosine (10 µM) to 106 µM with the highest applied concentration of sarcosine (1,500 µM). There was a marginal change observed in the MT concentration. Finally, the antioxidant activity of the PC-3 cells was determined using five different spectrophotometric methods [2,2-diphenyl-1-picrylhydrazyl (DPPH), ferric reducing ability of plasma (FRAP), free radicals, N,N-dimethyl-p-phenylenediamine (DMPD) and 2,2'-azino-bis(3-ethylbenzothiazoline-6-sulphonic acid (ABTS)]. A significant negative correlation was observed between DPPH and FRAP (r=-0.68 at p<0.001) and between DMPD and ABST (r=-0.64 at p<0.001). Additionally, as regards the correlation between MT and DPPH, a significant positive trend (r=0.62 at p<0.001) was observed.

Risk stratification in prostate cancer screening

Screening for prostate cancer is a controversial topic within the field of urology. The US Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial did not demonstrate any difference in prostate-cancer-related mortality rates between men screened annually rather than on an 'opportunistic' basis. However, in the world's largest trial to date--the European Randomised Study of Screening for Prostate Cancer--screening every 2-4 years was associated with a 21% reduction in prostate-cancer-related mortality rate after 11 years. Citing the uncertain ratio between potential harm and potential benefit, the US Preventive Services Task Force recently recommended against serum PSA screening. Although this ratio has yet to be elucidated, PSA testing--and early tumour detection--is undoubtedly beneficial for some individuals. Instead of adopting a 'one size fits all' approach, physicians are likely to perform personalized risk assessment to minimize the risk of negative consequences, such as anxiety, unnecessary testing and biopsies, overdiagnosis, and overtreatment. The PSA test needs to be combined with other predictive factors or be used in a more thoughtful way to identify men at risk of symptomatic or life-threatening cancer, without overdiagnosing indolent disease. A risk-adapted approach is needed, whereby PSA testing is tailored to individual risk.

Active surveillance for low-risk prostate cancer

Active surveillance (AS) is an important management strategy for men diagnosed with low-risk prostate cancer (PCa). The need for AS is increasing due to the awareness that many PCa are identified that show a low growth potential and therefore are likely to remain clinically asymptomatic during the lifetime of an individual. Currently there is no good method to prevent the overdiagnosis of indolent cancers upfront. During the last decade, several studies on AS around the world have made observations that feed the discussion on how to select and monitor these patients, how to proceed with the research to develop a better and more precise clinical definition of indolent cancers and how to manage men under AS clinically. Furthermore, patients' perspectives have become clearer, and quality of life studies give direction to the practical approach and care for patients and partners. This paper reflects the consensus on the state of the art and the future direction of AS, based on the Inside Track Conference "Active Surveillance for low risk prostate cancer" (Chairmen: C.H. Bangma, NL, and L. Klotz, CA; Co-Chairmen: L.J. Denis, BE, and C. Parker, UK; Scientific Coordinators: M. J. Roobol, NL, and E.W. Steyerberg, NL), organized by the European School of Oncology in collaboration with Europa Uomo in Rotterdam, the Netherlands in January 2012. Topics for discussion were the optimisation of patient selection based on indolent disease definition, the incorporation of therapeutic agents into AS programs, the optimisation of patient care, and the application of emerging technologies and biomarkers.

A Calculator for Prostate Cancer Risk 4 Years After an Initially Negative Screen: Findings from ERSPC Rotterdam

BACKGROUND

Inconclusive test results often occur after prostate-specific antigen (PSA)-based screening for prostate cancer (PCa), leading to uncertainty on whether, how, and when to repeat testing.

OBJECTIVE

To develop and validate a prediction tool for the risk of PCa 4 yr after an initially negative screen.

DESIGN, SETTING, AND PARTICIPANTS

We analyzed data from 15 791 screen-negative men aged 55-70 yr at the initial screening round of the Rotterdam section of the European Randomized Study of Screening for Prostate Cancer.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

Follow-up and repeat screening at 4 yr showed either no PCa, low-risk PCa, or potentially high-risk PCa (defined as clinical stage >T2b and/or biopsy Gleason score ≥ 7 and/or PSA ≥ 10.0 ng/ml). A multinomial logistic regression analysis included initial screening data on age, PSA, digital rectal examination (DRE), family history, prostate volume, and having had a previous negative biopsy. The 4-yr risk predictions were validated with additional follow-up data up to 8 yr after initial screening.

RESULTS AND LIMITATIONS

Positive family history and, especially, PSA level predicted PCa, whereas a previous negative biopsy or a large prostate volume reduced the likelihood of future PCa. The risk of having PCa 4 yr after an initially negative screen was 3.6% (interquartile range: 1.0-4.7%). Additional 8-yr follow-up data confirmed these predictions. Although data were based on sextant biopsies and a strict protocol-based biopsy indication, we suggest that men with a low predicted 4-yr risk (eg, ≤ 1.0%) could be rescreened at longer intervals or not at all, depending on competing risks, while men with an elevated 4-yr risk (eg, ≥ 5%) might benefit from immediate retesting. These findings need to be validated externally.

CONCLUSIONS

This 4-yr future risk calculator, based on age, PSA, DRE, family history, prostate volume, and previous biopsy status, may be a promising tool for reducing uncertainty, unnecessary testing, and overdiagnosis of PCa.