Do prostate cancer risk models improve the predictive accuracy of PSA screening? A meta-analysis

Urinary RNA-based biomarkers for prostate cancer detection

Prostate cancer (PCa) is the commonest malignancy in the male population worldwide. Serum prostate specific antigen (PSA) test is the most important biomarker for the detection, follow-up and therapeutic monitoring of PCa. Defects in PSA specificity have elicited research for new biomarkers to improve early diagnosis and avoid false-positive results. This review evaluates urinary RNA-based biomarkers. Urine is a versatile body fluid for non-invasive biomarker detection in case of urological malignancies. The importance of RNA-based biomarkers has been demonstrated by the current use of PCA3, a long non coding RNA biomarker already approved by the Food and Drugs Administration. Through the years, other urinary RNA biomarkers have been evaluated, including the well-known TMPRSS2:ERG transcript, as well as many messenger RNAs, long non coding RNAs and micro-RNA. Validation of a specific urinary RNA-based marker or an algorithm of different biomarkers levels as diagnostic markers for PCa could be useful to avoid unnecessary prostate biopsies.

Evidenced-based clinical practice guideline for prostate cancer (summary: Japanese Urological Association, 2016 edition)

These guidelines cover a wide range of topics from prostate cancer epidemiology to palliative care. Questions arising in daily clinical practice have been extracted and formulated as clinical questions. In the 4 years since the previous edition, there have been major changes - for example, robot-assisted prostatectomy has rapidly come into widespread use, and new hormones and anticancer drugs have been developed for castration-resistant prostate cancer. In response to these developments, the number of fields included in this guideline was increased from 11 in the 2012 edition to 16, and the number of clinical questions was increased from 63 to 70. The number of papers identified in searches of the existing literature increased from 4662 in the first edition, published in 2006, to 10 490 in the 2012 edition. The number of references has reached 29 448 just during this review period, indicating the exponential increase in research on the topic of prostate cancer. Clinical answers have been prepared based on the latest evidence. Recommendation grades for the clinical answers were determined by radiologists, pathologists, and other specialists in addition to urologists in order to reflect the recent advances and diversity of prostate cancer treatment. Here, we present a short English version of the original guideline, and overview its key clinical issues.

Racial Variation in the Utility of Urinary Biomarkers PCA3 and T2ERG in a Large Multicenter Study

PURPOSE

To our knowledge it is unknown whether urinary biomarkers for prostate cancer have added utility to clinical risk calculators in different racial groups. We examined the utility of urinary biomarkers added to clinical risk calculators for predicting prostate cancer in African American and nonAfrican American men.

MATERIALS AND METHODS

Demographics, PCPT (Prostate Cancer Prevention Trial) risk scores, data on the biomarkers data PCA3 (prostate cancer antigen 3) and T2ERG (transmembrane protease serine 2 and v-ets erythroblastosis virus E26 oncogene homolog gene fusion), and biopsy pathology features were prospectively collected on 718 men as part of EDRN (Early Detection Research Network). Utility was determined by generating ROC curves and comparing AUC values for the baseline multivariable PCPT model and for models containing biomarker scores.

RESULTS

PCA3 and T2ERG added utility for the prediction of prostate cancer and clinically significant prostate cancer when combined with the PCPT Risk Calculator. This utility was seen in nonAfrican American men only for PCA3 (AUC 0.64 increased to 0.75 for prostate cancer and to 0.69-0.77 for clinically significant prostate cancer, both p <0.001) and for T2ERG (AUC 0.64-0.74 for prostate cancer, p <0.001, and 0.69-0.73 for clinically significant prostate cancer, p = 0.029). African American men did not have an added benefit with the addition of biomarkers, including PCA3 (AUC 0.75-0.77, p = 0.64, and 0.65-0.66, p = 0.74) and T2ERG (AUC 0.75-0.74, p = 0.74, and 0.65-0.64, p = 0.88), for prostate cancer and clinically significant prostate cancer, respectively. Limitations include the small number of African American men (72). The post hoc subgroup analysis nature of the study limited findings to being hypothesis generating.

CONCLUSIONS

As novel biomarkers are discovered, clinical utility should be established across demographically diverse cohorts.

Improving the evaluation and diagnosis of clinically significant prostate cancer in 2017

PURPOSE OF REVIEW

To provide an overview of the current state of the evidence and highlight recent advances in the evaluation and diagnosis of clinically significant prostate cancer, focusing on biomarkers, risk calculators and multiparametric MRI (mpMRI).

RECENT FINDINGS

In 2017 there are numerous options to improve early detection as compared to a purely prostate-specific antigen (PSA)-based approach. All have strengths and drawbacks. In addition to repeating the PSA and performing clinical work-up (digital rectal examination and estimation of prostate volume), additional tests investigated in the initial biopsy setting are: %free PSA, Prostate Health Index, 4-kallikrein score, SelectMDx, and Michigan Prostate Score and in the repeat setting: %free PSA, Prostate Health Index, 4-kallikrein score, Prostate Cancer Antigen 3, and ConfirmMDx. Risk calculators are available for both biopsy settings and incorporate clinical data with, or without, biomarkers. mpMRI is an important diagnostic adjunct.

SUMMARY

There are numerous tests available that can help increase the specificity of PSA, in the initial and repeat biopsy setting. All coincide with a small decrease in sensitivity of detecting high-grade cancer. Cost effectiveness is crucial. The way forward is a multivariable risk assessment on the basis of readily available clinical data, potentially with the addition of PSA subforms, preferably at low cost. MRI in the prediagnostic setting is promising, but is not ready for 'prime time'.

What Is the Negative Predictive Value of Multiparametric Magnetic Resonance Imaging in Excluding Prostate Cancer at Biopsy? A Systematic Review and Meta-analysis from the European Association of Urology Prostate Cancer Guidelines Panel

CONTEXT

It remains unclear whether patients with a suspicion of prostate cancer (PCa) and negative multiparametric magnetic resonance imaging (mpMRI) can safely obviate prostate biopsy.

OBJECTIVE

To systematically review the literature assessing the negative predictive value (NPV) of mpMRI in patients with a suspicion of PCa.

EVIDENCE ACQUISITION

The Embase, Medline, and Cochrane databases were searched up to February 2016. Studies reporting prebiopsy mpMRI results using transrectal or transperineal biopsy as a reference standard were included. We further selected for meta-analysis studies with at least 10-core biopsies as the reference standard, mpMRI comprising at least T2-weighted and diffusion-weighted imaging, positive mpMRI defined as a Prostate Imaging Reporting Data System/Likert score of ≥3/5 or ≥4/5, and results reported at patient level for the detection of overall PCa or clinically significant PCa (csPCa) defined as Gleason ≥7 cancer.

EVIDENCE SYNTHESIS

A total of 48 studies (9613 patients) were eligible for inclusion. At patient level, the median prevalence was 50.4% (interquartile range [IQR], 36.4-57.7%) for overall cancer and 32.9% (IQR, 28.1-37.2%) for csPCa. The median mpMRI NPV was 82.4% (IQR, 69.0-92.4%) for overall cancer and 88.1% (IQR, 85.7-92.3) for csPCa. NPV significantly decreased when cancer prevalence increased, for overall cancer (r=-0.64, p<0.0001) and csPCa (r=-0.75, p=0.032). Eight studies fulfilled the inclusion criteria for meta-analysis. Seven reported results for overall PCa. When the overall PCa prevalence increased from 30% to 60%, the combined NPV estimates decreased from 88% (95% confidence interval [95% CI], 77-99%) to 67% (95% CI, 56-79%) for a cut-off score of 3/5. Only one study selected for meta-analysis reported results for Gleason ≥7 cancers, with a positive biopsy rate of 29.3%. The corresponding NPV for a cut-off score of ≥3/5 was 87.9%.

CONCLUSIONS

The NPV of mpMRI varied greatly depending on study design, cancer prevalence, and definitions of positive mpMRI and csPCa. As cancer prevalence was highly variable among series, risk stratification of patients should be the initial step before considering prebiopsy mpMRI and defining those in whom biopsy may be omitted when the mpMRI is negative.

PATIENT SUMMARY

This systematic review examined if multiparametric magnetic resonance imaging (MRI) scan can be used to reliably predict the absence of prostate cancer in patients suspected of having prostate cancer, thereby avoiding a prostate biopsy. The results suggest that whilst it is a promising tool, it is not accurate enough to replace prostate biopsy in such patients, mainly because its accuracy is variable and influenced by the prostate cancer risk. However, its performance can be enhanced if there were more accurate ways of determining the risk of having prostate cancer. When such tools are available, it should be possible to use an MRI scan to avoid biopsy in patients at a low risk of prostate cancer.

The Huashan risk calculators performed better in prediction of prostate cancer in Chinese population: a training study followed by a validation study

The performances of the Prostate Cancer Prevention Trial (PCPT) risk calculator and other risk calculators for prostate cancer (PCa) prediction in Chinese populations were poorly understood. We performed this study to build risk calculators (Huashan risk calculators) based on Chinese population and validated the performance of prostate-specific antigen (PSA), PCPT risk calculator, and Huashan risk calculators in a validation cohort. We built Huashan risk calculators based on data from 1059 men who underwent initial prostate biopsy from January 2006 to December 2010 in a training cohort. Then, we validated the performance of PSA, PCPT risk calculator, and Huashan risk calculators in an observational validation study from January 2011 to December 2014. All necessary clinical information were collected before the biopsy. The results showed that Huashan risk calculators 1 and 2 outperformed the PCPT risk calculator for predicting PCa in both entire training cohort and stratified population (with PSA from 2.0 ng ml⁻¹ to 20.0 ng m). In the validation study, Huashan risk calculator 1 still outperformed the PCPT risk calculator in the entire validation cohort (0.849 vs 0.779 in area under the receiver operating characteristic curve [AUC] and stratified population. A considerable reduction of unnecessary biopsies (approximately 30%) was also observed when the Huashan risk calculators were used. Thus, we believe that the Huashan risk calculators (especially Huashan risk calculator 1) may have added value for predicting PCa in Chinese population. However, these results still needed further evaluation in larger populations.

Improving the Rotterdam European Randomized Study of Screening for Prostate Cancer Risk Calculator for Initial Prostate Biopsy by Incorporating the 2014 International Society of Urological Pathology Gleason Grading and Cribriform growth

BACKGROUND

The survival rate for men with International Society of Urological Pathology (ISUP) grade 2 prostate cancer (PCa) without invasive cribriform (CR) and intraductal carcinoma (IDC) is similar to that for ISUP grade 1. If updated into the European Randomized Study of Screening for Prostate Cancer (ERSPC Rotterdam) risk calculator number 3 (RC3), this may further improve upfront selection of men who need a biopsy.

OBJECTIVE

To improve the number of possible biopsies avoided, while limiting undiagnosed clinically important PCa by applying the updated RC3 for risk-based patient selection.

DESIGN, SETTING, AND PARTICIPANTS

The RC3 is based on the first screening round of the ERSPC Rotterdam, which involved 3616 men. In 2015, histopathologic slides for PCa cases (n=885) were re-evaluated. Low-risk (LR) PCa was defined as ISUP grade 1 or 2 without CR/IDC. High-risk (HR) PCa was defined as ISUP grade 2 with CR/IDC and PCa with ISUP grade≥3.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

We updated the RC3 using multinomial logistic regression analysis, including data on age, PSA, digital rectal examination, and prostate volume, for predicting LR and HR PCa. Predictive accuracy was quantified using receiver operating characteristic analysis and decision curve analysis.

RESULTS AND LIMITATIONS

Men without PCa could effectively be distinguished from men with LR PCa and HR PCa (area under the curve 0.70, 95% confidence interval [CI] 0.68-0.72 and 0.92, 95% CI 0.90-0.94). At a 1% risk threshold, the updated calculator would lead to a 34% reduction in unnecessary biopsies, while only 2% of HR PCa cases would be undiagnosed.

CONCLUSIONS

A relatively simple risk stratification tool augmented with a highly sensitive contemporary pathologic biopsy classification would result in a considerable decrease in unnecessary prostate biopsies and overdiagnosis of potentially indolent disease.

PATIENT SUMMARY

We improved a well-known prostate risk calculator with a new pathology classification system that better reflects disease burden. This new risk calculator allows individualized prediction of the chance of having (potentially aggressive) biopsy-detectable prostate cancer and can guide shared decision-making when considering prostate biopsy.

Rotterdam Prostate Cancer Risk Calculator: Development and Usability Testing of the Mobile Phone App

Background

The use of prostate cancer screening tools that take into account relevant prebiopsy information (ie, risk calculators) is recommended as a way of determining the risk of cancer and the subsequent need for a prostate biopsy. This has the potential to limit prostate cancer overdiagnosis and subsequent overtreatment. mHealth apps are gaining traction in urological practice and are used by both practitioners and patients for a variety of purposes.

Objective

The impetus of the study was to design, develop, and assess a smartphone app for prostate cancer screening, based on the Rotterdam Prostate Cancer Risk Calculator (RPCRC).

Methods

The results of the Rotterdam arm of the European Randomized Study of Screening for Prostate Cancer (ERSPC) study were used to elaborate several algorithms that allowed the risk of prostate cancer to be estimated. A step-by-step workflow was established to ensure that depending on the available clinical information the most complete risk model of the RPCRC was used. The user interface was designed and then the app was developed as a native app for iOS. The usability of the app was assessed using the Post-Study System Usability Questionnaire (PSSUQ) developed by IBM, in a group of 92 participants comprising urologists, general practitioners, and medical students.

Results

A total of 11 questions were built into the app, and, depending on the answers, one of the different algorithms of the RPCRC could be used to predict the risk of prostate cancer and of clinically significant prostate cancer (Gleason score ≥7 and clinical stage >T2b). The system usefulness, information quality, and interface quality scores were high—92% (27.7/30), 87% (26.2/30), and 89% (13.4/15), respectively. No usability problems were identified.

Conclusions

The RPCRC app is helpful in predicting the risk of prostate cancer and, even more importantly, clinically significant prostate cancer. Its algorithms have been externally validated before and the usability score shows the app’s interface is well designed. Further usability testing is required in different populations to verify these results and ensure that it is easy to use, to warrant a broad appeal, and to provide better patient care.

Magnetic Resonance Imaging Provides Added Value to the Prostate Cancer Prevention Trial Risk Calculator for Patients With Estimated Risk of High-grade Prostate Cancer Less Than or Equal to 10

OBJECTIVE

To determine the added value of prostate magnetic resonance imaging (MRI) to the Prostate Cancer Prevention Trial risk calculator.

METHODS

Between January 2012 and December 2015, 339 patients underwent prostate MRI prior to biopsy at our institution. MRI was considered positive if there was at least 1 Prostate Imaging Reporting and Data System 4 or 5 MRI suspicious region. Logistic regression was used to develop 2 models: biopsy outcome as a function of the (1) Prostate Cancer Prevention Trial risk calculator alone and (2) combined with MRI findings.

RESULTS

When including all patients, the Prostate Cancer Prevention Trial with and without MRI models performed similarly (area under the curve [AUC] = 0.74 and 0.78, P = .06). When restricting the cohort to patients with estimated risk of high-grade (Gleason ≥7) prostate cancer ≤10%, the model with MRI outperformed the Prostate Cancer Prevention Trial alone model (AUC = 0.69 and 0.60, P = .01). Within this cohort of patients, there was no significant difference in discrimination between models for those with previous negative biopsy (AUC = 0.61 vs 0.63, P = .76), whereas there was a significant improvement in discrimination with the MRI model for biopsy-naïve patients (AUC = 0.72 vs 0.60, P = .01).

CONCLUSION

The use of prostate MRI in addition to the Prostate Cancer Prevention Trial risk calculator provides a significant improvement in clinical risk discrimination for patients with estimated risk of high-grade (Gleason ≥7) prostate cancer ≤10%. Prebiopsy prostate MRI should be strongly considered for these patients.

Clarifying the PSA grey zone: The management of patients with a borderline PSA

INTRODUCTION

Prostate specific antigen is a marker for prostate cancer and a key diagnostic tool, yet when to refer patients with a borderline PSA is currently unclear. This review describes how to assess a patient with borderline PSA and provides an algorithm for management.

METHODS

Current literature on reference values, factors affecting PSA, indications for referral, non-invasive investigations and the role of MRI were reviewed. Medline and EMBASE were searched using MeSH terms.

RESULTS

The literature suggests that a PSA of over 1.5 ng/mL should be used as a cut-off to consider further testing for all age groups. There is strong evidence to show that adjuncts are useful when interpreting PSA results, most notably percentage free PSA and proPSA. Considerable weighting should also be given to the ERSPC risk calculator when deciding when to refer. Multi-parametric MRI is valuable in closely examining suspicious lesions to reduce the number of negative biopsies. MRI fusion biopsy (TRUS, transrectal ultrasonography or transperineal) should be considered over standard TRUS biopsy to detect more clinically significant disease.

CONCLUSIONS

Management of borderline PSA is not straightforward. A cut-off of 1.5 ng/mL should be used in conjunction with digital rectal exam, risk calculation and PSA adjuncts. Imaging and biopsy should utilise mpMRI to achieve improved diagnosis of clinically significant prostate cancer, with fewer unnecessary investigations.

What's new in screening in 2015?

PURPOSE OF REVIEW

The aim of this review was to highlight important articles in the field of prostate cancer screening published during 2015 and early 2016. Four major areas were identified for the purpose: screening strategies, post-United States Preventive Services Task Force (USPSTF) 2011-2012, screening trends/patterns, and shared decision making.

RECENT FINDINGS

Several studies furthered the evidence that screening reduces the risk of metastasis and death from prostate cancer. Multiplex screening strategies are of proven benefit; genetics and MRI need further evaluation. Prostate-specific antigen (PSA) screening rates declined in men above age of 50 years, as did the overall prostate cancer incidence following the USPSTF 2011-2012 recommendation against PSA. The consequences of declining screening rates will become apparent in the next few years. More research is needed to identify the most optimal approach to engage in, and implement, an effective shared decision-making in clinical practice.

SUMMARY

Data emerging in 2015 provided evidence on the question of how best to screen and brought more steps in the right direction of 'next-generation prostate cancer screening'. Screening is an ongoing process in all men regardless of whether or not they might benefit from early detection and treatment. After the USPSTF 2011-2012 recommendation, the rates of PSA testing are declining; however, this decline is observed in all men and not solely in those who will not benefit from the screening. The long-term effect of this recommendation might not be as anticipated. More studies are needed on how to implement the best available evidence on who, and when, to screen in clinical practice.

EAU-ESTRO-SIOG Guidelines on Prostate Cancer. Part 1: Screening, Diagnosis, and Local Treatment with Curative Intent

OBJECTIVE

To present a summary of the 2016 version of the European Association of Urology (EAU) - European Society for Radiotherapy & Oncology (ESTRO) - International Society of Geriatric Oncology (SIOG) Guidelines on screening, diagnosis, and local treatment with curative intent of clinically localised prostate cancer (PCa).

EVIDENCE ACQUISITION

The working panel performed a literature review of the new data (2013-2015). The guidelines were updated and the levels of evidence and/or grades of recommendation were added based on a systematic review of the evidence.

EVIDENCE SYNTHESIS

BRCA2 mutations have been added as risk factors for early and aggressive disease. In addition to the Gleason score, the five-tier 2014 International Society of Urological Pathology grading system should now be provided. Systematic screening is still not recommended. Instead, an individual risk-adapted strategy following a detailed discussion and taking into account the patient's wishes and life expectancy must be considered. An early prostate-specific antigen test, the use of a risk calculator, or one of the promising biomarker tools are being investigated and might be able to limit the overdetection of insignificant PCa. Breaking the link between diagnosis and treatment may lower the overtreatment risk. Multiparametric magnetic resonance imaging using standardised reporting cannot replace systematic biopsy, but robustly nested within the diagnostic work-up, it has a key role in local staging. Active surveillance always needs to be discussed with very low-risk patients. The place of surgery in high-risk disease and the role of lymph node dissection have been clarified, as well as the management of node-positive patients. Radiation therapy using dose-escalated intensity-modulated technology is a key treatment modality with recent improvement in the outcome based on increased doses as well as combination with hormonal treatment. Moderate hypofractionation is safe and effective, but longer-term data are still lacking. Brachytherapy represents an effective way to increase the delivered dose. Focal therapy remains experimental while cryosurgery and HIFU are still lacking long-term convincing results.

CONCLUSIONS

The knowledge in the field of diagnosis, staging, and treatment of localised PCa is evolving rapidly. The 2016 EAU-ESTRO-SIOG Guidelines on PCa summarise the most recent findings and advice for the use in clinical practice. These are the first PCa guidelines endorsed by the European Society for Radiotherapy and Oncology and the International Society of Geriatric Oncology and reflect the multidisciplinary nature of PCa management. A full version is available from the EAU office and online (http://uroweb.org/guideline/prostate-cancer/).

PATIENT SUMMARY

The 2016 EAU-STRO-IOG Prostate Cancer (PCa) Guidelines present updated information on the diagnosis, and treatment of clinically localised prostate cancer. In Northern and Western Europe, the number of men diagnosed with PCa has been on the rise. This may be due to an increase in opportunistic screening, but other factors may also be involved (eg, diet, sexual behaviour, low exposure to ultraviolet radiation). We propose that men who are potential candidates for screening should be engaged in a discussion with their clinician (also involving their families and caregivers) so that an informed decision may be made as part of an individualised risk-adapted approach.

Prediction of Prostate Cancer: External Validation of the ERSPC Risk Calculator in a Contemporary Dutch Clinical Cohort

BACKGROUND

The validity of prediction models needs external validation to assess their value beyond the original development setting.

OBJECTIVE

To report the diagnostic accuracy of the European Randomized Study of Screening for Prostate Cancer (ERSPC) risk calculator (RC)3 and RC4 in a contemporary Dutch clinical cohort.

DESIGN, SETTING, AND PARTICIPANTS

We retrospectively identified all men who underwent prostate biopsy (PBx) in the Jeroen Bosch Hospital, The Netherlands, between 2007 and 2016. Patients were included if they met ERSPC RC requirements of age (50-80 yr), prostate-specific antigen (PSA) (0.4-50 ng/ml), and prostate volume (10-150ml). The probability of a positive biopsy for prostate cancer (PCa) and significant PCa (Gleason score ≥7 and/or higher than T2b) were calculated and compared with PBx pathology results.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

Evaluation was performed by calibration, discrimination, and clinical usefulness using calibration plots, area under the receiver operating characteristic curves (AUCs), and decision curve analyses (DCAs), respectively.

RESULTS AND LIMITATIONS

A total of 2270 PBx sessions were eligible for final analysis. Discriminative ability of RC3 (AUC) was 0.78 and 0.90 for any PCa and significant PCa, respectively. For RC4 the calculated AUCs were 0.62 (any PCa) and 0.76 (significant PCa). The calibration plots of RC3 showed good results for both any PCa risk and significant PCa risk. In the repeat PBx group, RC4 tended to underestimate outcomes for PCa and showed moderate calibration for significant PCa. DCA showed an overall net benefit compared with PSA and digital rectal examination (DRE) alone. Limitations of this study are its retrospective single-institution design, retrospectively assessed DRE outcomes, no time restrictions between the first and repeat biopsy sessions, and no anterior sampling in the repeat PBx protocol.

CONCLUSIONS

The ERSPC RCs performed well in a contemporary clinical setting. Most pronounced in the biopsy-naive group, both RCs should be favoured over a PSA plus DRE-based stratification in the decision whether or not to perform PBx.

PATIENT SUMMARY

We looked at the ability of the existing European Randomized Study of Screening for Prostate Cancer risk calculator (RC), using different clinical data to predict the presence of prostate cancer in Dutch men. The RC performed well and should be favoured in the decision of whether or not to perform prostate biopsies over the conventional diagnostic pathway.

Biomarkers in localized prostate cancer

Biomarkers can improve prostate cancer diagnosis and treatment. Accuracy of prostate-specific antigen (PSA) for early diagnosis of prostate cancer is not satisfactory, as it is an organ- but not cancer-specific biomarker, and it can be improved by using models that incorporate PSA along with other test results, such as prostate cancer antigen 3, the molecular forms of PSA (proPSA, benign PSA and intact PSA), as well as kallikreins. Recent reports suggest that new tools may be provided by metabolomic studies as shown by preliminary data on sarcosine. Additional molecular biomarkers have been identified by the use of genomics, proteomics and metabolomics. We review the most relevant biomarkers for early diagnosis and management of localized prostate cancer.

Risk prediction tools for cancer in primary care

Numerous risk tools are now available, which predict either current or future risk of a cancer diagnosis. In theory, these tools have the potential to improve patient outcomes through enhancing the consistency and quality of clinical decision-making, facilitating equitable and cost-effective distribution of finite resources such as screening tests or preventive interventions, and encouraging behaviour change. These potential uses have been recognised by the National Cancer Institute as an ‘area of extraordinary opportunity' and an increasing number of risk prediction models continue to be developed. The data on predictive utility (discrimination and calibration) of these models suggest that some have potential for clinical application; however, the focus on implementation and impact is much more recent and there remains considerable uncertainty about their clinical utility and how to implement them in order to maximise benefits and minimise harms such as over-medicalisation, anxiety and false reassurance. If the potential benefits of risk prediction models are to be realised in clinical practice, further validation of the underlying risk models and research to assess the acceptability, clinical impact and economic implications of incorporating them in practice are needed.

Risk-based Patient Selection for Magnetic Resonance Imaging-targeted Prostate Biopsy after Negative Transrectal Ultrasound-guided Random Biopsy Avoids Unnecessary Magnetic Resonance Imaging Scans

BACKGROUND

Multiparametric magnetic resonance imaging (mpMRI) is increasingly used in men with suspicion of prostate cancer (PCa) after negative transrectal ultrasound (TRUS)-guided random biopsy. Risk-based patient selection for mpMRI could help to avoid unnecessary mpMRIs.

OBJECTIVE

To study the rate of potentially avoided mpMRIs after negative TRUS-guided random biopsy by risk-based patient selection using the Rotterdam Prostate Cancer Risk Calculator (RPCRC).

DESIGN, SETTING, AND PARTICIPANTS

One hundred and twenty two consecutive men received a mpMRI scan and subsequent MRI-TRUS fusion targeted biopsy in case of suspicious lesion(s) (Prostate Imaging Reporting and Data System ≥ 3) after negative TRUS-guided random biopsy. Men were retrospectively stratified according to the RPCRC biopsy advice to compare targeted biopsy outcomes after risk-based patient selection with standard (prostate specific antigen and/or digital rectal examination-driven) patient selection.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

The rate of potentially avoided mpMRIs by RPCRC-based patient selection in relation to the rate of missed high-grade (Gleason ≥ 3+4) PCa. Receiver operating characteristic curve analysis was performed to determine the area under the curve of the RPCRC for (high-grade) PCa.

RESULTS AND LIMITATIONS

Of the 60 men with a positive biopsy advice, six (10%) had low-grade PCa and 28 (47%) had high-grade PCa in targeted biopsy. Of the 62 men with a negative advice, two (3%) had low-grade PCa and three (5%) had high-grade PCa. Upfront RPCRC-based patient selection would have avoided 62 (51%) of 122 mpMRIs and two (25%) of eight low-grade PCa diagnoses, missing three (10%) of 31 high-grade PCa. The area under the curve of the RPCRC for PCa and high-grade PCa was respectively 0.76 (95% confidence interval 0.67-0.85) and 0.84 (95% confidence interval 0.76-0.93).

CONCLUSIONS

Risk-based patient selection with the RPCRC can avoid half of mpMRIs after a negative prostate specific antigen and/or digital rectal examination-driven TRUS-guided random biopsy. Further improvement in risk-based patient selection for mpMRI could be made by adjusting the RPCRC for MRI-targeted biopsy outcome prediction.

PATIENT SUMMARY

The suspicion of prostate cancer remains in many men after a negative ultrasound-guided prostate biopsy. These men increasingly receive an often unnecessary magnetic resonance imaging (MRI) scan. We found that patient selection for MRI based on the Rotterdam Prostate Cancer Risk Calculator biopsy advice could avoid half of the MRIs.

Development and external validation of a prostate health index-based nomogram for predicting prostate cancer

To develop and externally validate a prostate health index (PHI)-based nomogram for predicting the presence of prostate cancer (PCa) at biopsy in Chinese men with prostate-specific antigen 4–10 ng/mL and normal digital rectal examination (DRE). 347 men were recruited from two hospitals between 2012 and 2014 to develop a PHI-based nomogram to predict PCa. To validate these results, we used a separate cohort of 230 men recruited at another center between 2008 and 2013. Receiver operator curves (ROC) were used to assess the ability to predict PCa. A nomogram was derived from the multivariable logistic regression model and its accuracy was assessed by the area under the ROC (AUC). PHI achieved the highest AUC of 0.839 in the development cohort compared to the other predictors (p < 0.001). Including age and prostate volume, a PHI-based nomogram was constructed and rendered an AUC of 0.877 (95% CI 0.813–0.938). The AUC of the nomogram in the validation cohort was 0.786 (95% CI 0.678–0.894). In clinical effectiveness analyses, the PHI-based nomogram reduced unnecessary biopsies from 42.6% to 27% using a 5% threshold risk of PCa to avoid biopsy with no increase in the number of missed cases relative to conventional biopsy decision.

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.

Current challenges in prostate cancer: an interview with Prostate Cancer UK

In this video Q&A, we talk to Iain Frame and Sarah Cant from Prostate Cancer UK about the current challenges in prostate cancer research and policy and how these are being addressed.