Risk-Based Selection for Active Surveillance: Results of the Movember Foundation's Global Action Plan Prostate Cancer Active Surveillance (GAP3) Initiative.

PURPOSE: We sought to identify and validate known predictors of disease reclassification at 1 or 4 years to support risk-based selection of patients suitable for active surveillance. MATERIALS AND METHODS: An individual participant data meta-analysis using data from 25 established cohorts within the Movember Foundations GAP3 Consortium. In total 5,530 men were included. Disease reclassification was defined as any increase in Gleason grade group at biopsy at 1 and 4 years. Associations were estimated using random effect logistic regression models. The discriminative ability of combinations of predictors was assessed in an internal-external validation procedure using the AUC curve. RESULTS: Among the 5,570 men evaluated at 1 year, we found 815 reclassifications to higher Gleason grade group at biopsy (pooled reclassification rate 13%, range 0% to 31%). Important predictors were age, prostate specific antigen, prostate volume, T-stage and number of biopsy cores with prostate cancer. Among the 1,515 men evaluated at 4 years, we found 205 reclassifications (pooled reclassification rates 14%, range 3% to 40%), with similar predictors. The average areas under the receiver operating characteristic curve at internal-external validation were 0.68 and 0.61 for 1-year and 4-year reclassification, respectively. CONCLUSIONS: Disease reclassification occurs typically in 13% to 14% of biopsies at 1 and 4 years after the start of active surveillance with substantial between-study heterogeneity. Current guidelines might be extended by considering prostate volume to improve individualized selection for active surveillance. Additional predictors are needed to improve patient selection for active surveillance.

Comparing the prediction of prostate biopsy outcome using the Chinese Prostate Cancer Consortium (CPCC) Risk Calculator and the Asian adapted Rotterdam European Randomized Study of Screening for Prostate Cancer (ERSPC) Risk Calculator in Chinese and European men.

PURPOSE: To externally validate the clinical utility of Chinese Prostate Cancer Consortium Risk Calculator (CPCC-RC) and Asian adapted Rotterdam European Randomized Study of Screening for Prostate Cancer Risk Calculator 3 (A-ERSPC-RC3) for prediction prostate cancer (PCa) and high-grade prostate cancer (HGPCa, Gleason Score ≥ 3 + 4) in both Chinese and European populations. MATERIALS AND METHODS: The Chinese clinical cohort, the European population-based screening cohort, and the European clinical cohort included 2,508, 3,616 and 617 prostate biopsy-naive men, respectively. The area under the receiver operating characteristic curve (AUC), calibration plot and decision curve analyses were applied in the analysis. RESULTS: The CPCC-RC's predictive ability for any PCa (AUC 0.77, 95% CI 0.75-0.79) was lower than the A-ERSPC-RC3 (AUC 0.79, 95% CI 0.77-0.81) in the European screening cohort (p < 0.001), but similar for HGPCa (p = 0.24). The CPCC-RC showed lower predictive accuracy for any PCa (AUC 0.65, 95% CI 0.61-0.70), but acceptable predictive accuracy for HGPCa (AUC 0.73, 95% CI 0.69-0.77) in the European clinical cohort. The A-ERSPC-RC3 showed an AUC of 0.74 (95% CI 0.72-0.76) in predicting any PCa, and a similar AUC of 0.74 (95% CI 0.72-0.76) in predicting HGPCa in Chinese cohort. In the Chinese population, decision curve analysis revealed a higher net benefit for CPCC-RC than A-ERSPC-RC3, while in the European screening and clinical cohorts, the net benefit was higher for A-ERSPC-RC3. CONCLUSIONS: The A-ERSPC-RC3 accurately predict the prostate biopsy in a contemporary Chinese multi-center clinical cohort. The CPCC-RC can predict accurately in a population-based screening cohort, but not in the European clinical cohort.

E-bike and classic bicycle-related traumatic brain injuries presenting to the emergency department.

BACKGROUND: E-bike usage is increasingly popular and concerns about e-bike-related injuries and safety have risen as more injured e-bikers attend the emergency department (ED). Traumatic brain injury (TBI) is the main cause of severe morbidity and mortality in bicycle-related accidents. This study compares the frequency and severity of TBI after an accident with an e-bike or classic bicycle among patients treated in the ED. METHODS: This was a prospective cohort study of patients with bicycle-related injuries attending the ED of a level 1 trauma centre in the Netherlands between June 2016 and May 2017. The primary outcomes were frequency and severity of TBI (defined by the Abbreviated Injury Scale head score ≥1). Injury Severity Score, surgical intervention, hospitalisation and 30-day mortality were secondary outcomes. Independent risk factors for TBI were identified with multiple logistic regression. RESULTS: We included 834 patients, of whom there were 379 e-bike and 455 classic bicycle users. The frequency of TBI was not significantly different between the e-bike and classic bicycle group (respectively, n=56, 15% vs n=73, 16%; p=0.61). After adjusting for age, gender, velocity, anticoagulation use and alcohol intoxication the OR for TBI with an e-bike compared with classic bicycle was 0.90 (95% CI 0.56 to 1.45). Independent of type of bicycle, TBI was more likely if velocity was 26-45 km/hour, OR 8.14 (95% CI 2.36 to 28.08), the patient was highly alcohol intoxicated, OR 7.02 (95% CI 2.88 to 17.08) or used anticoagulants, OR 2.18 (95% CI 1.20 to 3.97). TBI severity was similar in both groups (p=0.65): eight e-bike and seven classic bicycle accident victims had serious TBI. CONCLUSION: The frequency and severity of TBI among patients treated for bicycle-related injuries at our ED was similar for e-bike and classic bicycle users. Velocity, alcohol intoxication and anticoagulant use were the main determinants of the risk of head injury regardless of type of bicycle used.

Prostate cancer upgrading with serial prostate magnetic resonance imaging and repeat biopsy in men on active surveillance: are confirmatory biopsies still necessary?

OBJECTIVES: To investigate whether serial prostate magnetic resonance imaging (MRI) may guide the utility of repeat targeted (TBx) and systematic biopsy (SBx) when monitoring men with low-risk prostate cancer (PCa) at 1-year of active surveillance (AS). PATIENTS AND METHODS: We retrospectively included 111 consecutive men with low-risk (International Society of Urological Pathology [ISUP] Grade 1) PCa, who received protocolled repeat MRI with or without TBx and repeat SBx at 1-year of AS. TBx was performed in Prostate Imaging-Reporting and Data System (PI-RADS) score ≥3 lesions (MRI-positive men). Upgrading defined as ISUP Grade ≥2 PCa (I), Grade ≥2 with cribriform growth/intraductal carcinoma PCa (II), and Grade ≥3 PCa (III) was investigated. Upgrading detected by TBx only (not by SBx) and SBx only (not by TBx) was investigated in MRI-positive and -negative men, and related to radiological progression on MRI (Prostate Cancer Radiological Estimation of Change in Sequential Evaluation [PRECISE] score). RESULTS: Overall upgrading (I) was 32% (35/111). Upgrading in MRI-positive and -negative men was 48% (30/63) and 10% (5/48) (P < 0.001), respectively. In MRI-positive men, there was upgrading in 23% (seven of 30) by TBx only and in 33% (10/30) by SBx only. Radiological progression (PRECISE score 4-5) in MRI-positive men was seen in 27% (17/63). Upgrading (I) occurred in 41% (seven of 17) of these MRI-positive men, while this was 50% (23/46) in MRI-positive men without radiological progression (PRECISE score 1-3) (P = 0.534). Overall upgrading (II) was 15% (17/111). Upgrading in MRI-positive and -negative men was 22% (14/63) and 6% (three of 48) (P = 0.021), respectively. In MRI-positive men, there was upgrading in three of 14 by TBx only and in seven of 14 by SBx only. Overall upgrading (III) occurred in 5% (five of 111). Upgrading in MRI-positive and -negative men was 6% (four of 63) and 2% (one of 48) (P = 0.283), respectively. In MRI-positive men, there was upgrading in one of four by TBx only and in two of four by SBx only. CONCLUSION: Upgrading is significantly lower in MRI-negative compared to MRI-positive men with low-risk PCa at 1-year of AS. In serial MRI-negative men, the added value of repeat SBx at 1-year surveillance is limited and should be balanced individually against the harms. In serial MRI-positive men, the added value of repeat SBx is substantial. Based on this cohort, SBx is recommended to be performed in combination with TBx in all MRI-positive men at 1-year of AS, also when there is no radiological progression.

External validation of novel magnetic resonance imaging-based models for prostate cancer prediction.

OBJECTIVES: To validate, in an external cohort, three novel risk models, including the recently updated European Randomized Study of Screening for Prostate Cancer (ERSPC) risk calculator, that combine multiparametric magnetic resonance imaging (mpMRI) and clinical variables to predict clinically significant prostate cancer (PCa). PATIENTS AND METHODS: We retrospectively analysed 307 men who underwent mpMRI prior to transperineal ultrasound fusion biopsy between October 2015 and July 2018 at two German centres. mpMRI was rated by Prostate Imaging Reporting and Data System (PI-RADS) v2.0 and clinically significant PCa was defined as International Society of Urological Pathology Gleason grade group ≥2. The prediction performance of the three models (MRI-ERSPC-3/4, and two risk models published by Radtke et al. and Distler et al., ModRad and ModDis) were compared using receiver-operating characteristic (ROC) curve analyses, with area under the ROC curve (AUC), calibration curve analyses and decision curves used to assess net benefit. RESULTS: The AUCs of the three novel models (MRI-ERSPC-3/4, ModRad and ModDis) were 0.82, 0.85 and 0.83, respectively. Calibration curve analyses showed the best intercept for MRI-ERSPC-3 and -4 of 0.35 and 0.76. Net benefit analyses indicated clear benefit of the MRI-ERSPC-3/4 risk models compared with the other two validated models. The MRI-ERSPC-3/4 risk models demonstrated a discrimination benefit for a risk threshold of up to 15% for clinically significant PCa as compared to the other risk models. CONCLUSION: In our external validation of three novel prostate cancer risk models, which incorporate mpMRI findings, a head-to-head comparison indicated that the MRI-ERSPC-3/4 risk model in particular could help to reduce unnecessary biopsies.

Predicting biochemical recurrence and prostate cancer-specific mortality after radical prostatectomy: comparison of six prediction models in a cohort of patients with screening- and clinically detected prostate cancer.

OBJECTIVES: To perform a comparison and external validation of three models predicting biochemical recurrence (BCR) and three models predicting prostate cancer (PCa)-specific mortality (PCSM) in a screening setting, i.e. patients with screening-detected PCa (S-PCa) and in those with clinically detected PCa (C-PCa). SUBJECTS AND METHODS: We retrospectively evaluated 795 men with S-PCa, from the European Randomized Study of Screening for Prostate Cancer, Rotterdam, and 1123 men with C-PCa initially treated with RP. The discriminative ability of the models was assessed according to the area under the curve (AUC) of the receiver-operating characteristic, and calibration was assessed graphically using calibration plots. RESULTS: The median (interquartile range [IQR]) follow-up for the S-PCa group was 10.4 (6.8-14.3) years and for the C-PCa group it was 8.8 (4.8-12.9) years. A total of 123 men with S-PCa (15%) and 389 men with C-PCa (35%) experienced BCR. Of the men with S-PCa and BCR, 24 (20%) died from PCa and 29 (23%) died from other causes. Of the men with C-PCa and BCR, 68 (17%) died from PCa and 105 (27%) died from other causes. The discrimination of the models predicting BCR or PCSM was higher for men with S-PCa (AUC: BCR 0.77-0.84, PCSM 0.60-0.77) than for the men with C-PCa (AUC: BCR 0.75-0.79, PCSM 0.51-0.68) as a result of the similar patient characteristics of the men with S-PCa in the present study and those of the cohorts used to develop these models. The risk of BCR was typically overestimated, while the risk of PCSM was typically underestimated. CONCLUSION: Prediction models for BCR showed good discrimination and reasonable calibration for both men with S-PCa and men with C-PCa, and even better discrimination for men with S-PCa. For PCSM, the evaluated models are not applicable in both settings of this Dutch cohort as a result of substantial miscalibration. This warrants caution when using these models to communicate future risks in other clinical settings.

Age, gender, functional KSS, reason for revision and type of bone defect predict functional outcome 5 years after revision total knee arthroplasty: a multivariable prediction model.

PURPOSE: The number of revision total knee arthroplasties (rTKA) is increasing. Unfortunately, not all patients benefit from revision surgery. The aim of this study was to develop a clinical prediction model that can be used to predict the functional outcome 5 years after rTKA. METHODS: Data of patients receiving rTKA at Sint Maartenskliniek, Nijmegen, The Netherlands, from 2004 onwards were prospectively collected. Demographic and clinical variables and patient-reported outcome scores were collected and considered as potential predictors. Beneficial outcome was defined as an increase of ≥ 20 points on the functional knee society scores (fKSS) or an absolute fKSS ≥ 80 points 5 years after surgery. The prediction model was developed using backward logistic regression. Regression coefficients were converted into an easy to use prediction rule. RESULTS: Overall, 295 rTKA patients were included of whom 157 (53%) had beneficial fKSS 5 years later. Age, gender, femoral bone defects, preoperative fKSS, and stiffness as reason for revision were included in the model. Men had a higher chance of beneficial fKSS than women (OR 1.59, 95% CI 0.91-2.78). Patients with major bone defects (OR 0.44, 95% CI 0.22-0.85), higher age (IQR OR 0.39, 95% CI 0.26-0.58), higher preoperative fKSS (IQR OR 0.42, 95% CI 0.30-0.59), and severe stiffness (OR 0.48, 95% CI 0.20-1.15) had a lower chance of successful outcome. The model's AUC was 0.76, 95% CI 0.70-0.81. CONCLUSION: Easily determinable characteristics of patients who need rTKA can be used to predict future functional outcome. Young men with low preoperative fKSS without severe stiffness are more likely to achieve a beneficial outcome. LEVEL OF EVIDENCE: IV.

Reducing Biopsies and Magnetic Resonance Imaging Scans During the Diagnostic Pathway of Prostate Cancer: Applying the Rotterdam Prostate Cancer Risk Calculator to the PRECISION Trial Data.

BACKGROUND: Risk stratification in the diagnostic pathway of prostate cancer (PCa) can be used to reduce biopsies and magnetic resonance imaging (MRI) scans, while maintaining the detection of clinically significant PCa (csPCa). The use of highly discriminating and well-calibrated models will generate better clinical outcomes if context-dependent thresholds are used. OBJECTIVE: To retrospectively assess the effect of the upfront use of the Rotterdam Prostate Cancer Risk Calculator (RPCRC) developed in a screening cohort and the RPCRC-MRI developed in a clinical cohort while exploring the need to adapt thresholds in biopsy-naïve men in the PRECISION (Prostate Evaluation for Clinically Important Disease: Sampling Using Image Guidance or Not?) trial. DESIGN SETTING AND PARTICIPANTS: In the transrectal ultrasonography arm, we evaluated 188 men; in the MRI arm, we evaluated 206 (for the reduction of MRI scans) and 137 (for the reduction of targeted biopsies) men. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Performance was assessed by discrimination, calibration, and clinical utility. RESULTS AND LIMITATIONS: The performance of the RPCRC was good. However, intercept adjustment was warranted. Net benefit was observed from a recalibrated probability of 32% for any PCa and 10% for csPCa. After recalibration and applying a threshold of 20% for any PCa or 10% for csPCa, 28% of all biopsies could have been reduced, missing five cases of csPCa. The uncalibrated RPCRC could reduce 35% of all MRI scans, with a threshold of 20% for any PCa or 4% for csPCa. In the MRI arm, performance was good without stressing recalibration. Net benefit was observed from a probability of 22% for any PCa and 7% for csPCa. With a threshold of 20% for any PCa or 4% for csPCa, 9% of all targeted biopsies could be reduced, missing one grade group 2 PCa. CONCLUSIONS: The performance of the RPCRC and RPCRC-MRI in men included in the PRECISION trial was good, but recalibration and adaptation of the risk threshold of the RPCRC are indicated to reach optimal performance. PATIENT SUMMARY: In this report, we show that risk stratification with the Rotterdam Prostate Cancer Risk Calculator has added value in reducing harm, but adjustment to reflect the characteristics of the patient cohort is indicated.

Development of a prediction model in female pure or predominant urge urinary incontinence: a retrospective cohort study.

Background: Urinary incontinence is a prevalent form of pelvic floor dysfunction, with a non-negligible impact on a patient's quality of life. There are several treatment options, varying from conservative to invasive. The aim of this study is to predict treatment outcomes of pure or predominant urge urinary incontinence (UUI) in women to support shared decision-making and manage patient expectations. Methods: Data on patient characteristics, disease history, and investigations of 512 consecutive women treated for UUI in three hospitals in the Netherlands were retrospectively collected. The predicted outcome was the short-term subjective continence outcome, defined as patient-reported continence 3 months after treatment categorized as cure (no urinary leakage), improvement (any degree of improvement of urinary leakage), and failure (no improvement or worsening of urinary leakage). Multivariable ordinal regression with backward stepwise selection was performed to analyze association between outcome and patient's characteristics. Interactions between patient characteristics and treatment were added to estimate individual treatment benefit. Discriminative ability was assessed with the ordinal c-statistic. Results: Conservative treatment was applied in 12% of the patients, pharmacological in 62%, and invasive in 26%. Subjective continence outcome was cure, improvement, and failure in 20%, 49%, and 31%, respectively. Number of incontinence episodes per day, voiding frequency during the day, subjective quantity of UI, coexistence of stress urinary incontinence (SUI), night incontinence, and bladder capacity and the interactions between these variables were included in the model. After internal validation, the ordinal c-statistic was 0.699. Conclusions: Six variables were of value to predict pure or predominant UUI treatment outcome in women. Further development into a comprehensive set of models for the use in various pelvic floor disorders and treatments is recommended to optimize individualized care. This model requires external validation before implementation in clinical practice.

Assessing a patient's individual risk of biopsy-detectable prostate cancer: Be aware of case mix heterogeneity and a priori likelihood.

The relation between prostate-specific antigen (PSA) and other relevant prebiopsy information is often combined in a risk calculator (RC). If the setting for RC use differs from that in which it was developed, there is a risk of making clinical decisions based on incorrect estimates of the absolute risk. The ERSPC-MRI RC predicts clinically significant prostate cancer (csPC; Gleason ≥ 3 + 4) on targeted and systematic biopsy using information on PSA, digital rectal examination, prostate volume, age, previous negative biopsy, and Prostate Imaging-Recording and Data System score. This calculator was developed on a clinical cohort of 961 men (2012-2017) with a csPC prevalence of 36%. Discrimination was good (area under the receiver operating characteristic curve 0.84). With the increasing use of multiparametric magnetic resonance imaging, we foresee that this RC will also be used for men with a lower a priori likelihood of PC. We investigated the effect of such a scenario on individual risk predictions. A small update of the intercept for the calculator can restore the accuracy to support decision-making with locally valid risk estimates. PATIENT SUMMARY: Decisions on who to refer for a prostate biopsy with its risk of sepsis and overdiagnosis require more than a prostate-specific antigen test. A prediction tool may take other relevant prebiopsy information into account, but may need to be updated to contemporary center-specific settings to provide accurate estimates of the risk of having prostate cancer.

Adherence to Active Surveillance Protocols for Low-risk Prostate Cancer: Results of the Movember Foundation's Global Action Plan Prostate Cancer Active Surveillance Initiative.

BACKGROUND: Active surveillance (AS) enrolment criteria and follow-up schedules for low-risk prostate cancer vary between institutions. However, uncertainty remains about adherence to these protocols. OBJECTIVE: To determine adherence to institution-specific AS inclusion criteria and follow-up schedules within the Movember Foundation's Global Action Plan Prostate Cancer Active Surveillance (GAP3) initiative. DESIGN, SETTING, AND PARTICIPANTS: We retrospectively assessed the data of 15 101 patients from 25 established AS cohorts worldwide between 2014 and 2016. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Adherence to individual AS inclusion criteria was rated on a five-point Likert scale ranging from poor to excellent. Nonadherence to follow-up schedules was defined as absence of repeat biopsy 1 yr after the scheduled date. Cohorts were pooled into annual and Prostate Cancer Research International: Active Surveillance (PRIAS)-based biopsy schedules, and a generalised linear mixed model was constructed to test for nonadherence. RESULTS AND LIMITATIONS: Serum prostate-specific antigen (PSA) inclusion criteria were followed in 92%, Gleason score (GS) criteria were followed in 97%, and the number of positive biopsy cores was followed in 94% of men. Both age and tumour stage (T stage) criteria had 99% adherence overall. Pooled nonadherence rates increased over time-8%, 16%, and 34% for annual schedules and 11%, 30%, and 29% for PRIAS-based schedules at 1, 4, and 7 yr, respectively-and did not differ between biopsy schedules. A limitation is that our results do not consider the use of multiparametric magnetic resonance imaging. CONCLUSIONS: In on-going development of evidence-based AS protocols, variable adherence to PSA and GS inclusion criteria should be considered. Repeat biopsy adherence reduces with increased duration of surveillance, independent of biopsy frequency. This emphasises the importance of risk stratification at the commencement of AS. PATIENT SUMMARY: We studied adherence to active surveillance protocols for prostate cancer worldwide. We found that inclusion criteria were generally followed well, but adherence to repeat biopsy reduced with time. This should be considered when optimising future active surveillance protocols.

A Tool for Shared Decision Making on Referral for Prostate Biopsy in the Primary Care Setting: Integrating Risks of Cancer with Life Expectancy.

Prostate cancer (PCa) testing involves a complex individually based decision making process. It should consider competing risks from other comorbidities when estimating a survival benefit from the early detection of clinically significant (cs)PCa. We aimed to develop a prediction tool that provides concrete advice for the general practitioner (GP) on whether to refer a man for further assessment. We hereto combined the probability of detecting csPCa and the potential overall survival benefit from early detection and treatment. The PCa detection probabilities were derived from 3616 men enrolled in the Dutch arm of the European Randomized Study of Screening for Prostate Cancer (ERSPC). Survival estimates were derived from 19,834 men from the Surveillance, Epidemiology, and End Results (SEER) registry, ERSPC, and Dutch life tables. Treatment benefit was estimated from the Prostate Cancer Intervention versus Observation Trial (PIVOT, n = 731). The prediction of csPCa detection was based on prostate-specific antigen (PSA), age, %freePSA, and digital rectal examination (DRE). The life expectancy (LE) for patients with PCa receiving no treatment was adjusted for age and Charlson comorbidity index. A negative impact on LE and treatment benefit was found with higher age and more comorbidity. The proposed integrated approach may support triage at GP practices, as PCa is a heterogeneous disease in predominantly elderly men.

Reducing unnecessary biopsies while detecting clinically significant prostate cancer including cribriform growth with the ERSPC Rotterdam risk calculator and 4Kscore.

INTRODUCTION: The use of risk calculators predicting clinically significant prostate cancer (csCaP) on biopsy reduces unnecessary biopsies and overdiagnosis of indolent disease compared to a Prostate Specific Antigen (PSA) strategy. Updating these tools using more specific outcome measures and contemporary predictors could potentially lead to further reductions. Our objective was to assess clinical impact of the 4 kallikrein (4K) score, the Rotterdam Prostate Cancer Risk Calculator (RPCRC), and the combination of both for predicting csCaP based on the latest International Society of Urological Pathology grading system and cribriform growth pattern. MATERIALS AND METHODS: Our prospective cohort consisted of 2,872 men from the first screening round in the European Randomized Study of Screening for Prostate Cancer Rotterdam; biopsy indication PSA ≥ 3.0. The predictive performance of the 4Kscore, RPCRC, and the combination of RPCRC with 4Kscore were assessed with area under the receiver operator characteristic curve (AUC) and calibration plots. Decision curve analysis was used to evaluate the reduction of unnecessary biopsy and indolent CaP. RESULTS: The csCaP was present in 242 (8%) men, and indolent CaP in 578 (20%). The 4Kscore and RPCRC had similar high AUCs (0.88 vs. 0.87; P = 0.41). The 4Kscore-RPCRC combination improved AUC to 0.89 compared to 4Kscore (P < 0.01) and RPCRC (P < 0.01). The RPCRC and 4Kscore reduced the number of Bx with 42 and 44, respectively, per 100 men at risk compared to a ≥PSA 3.0 strategy without increasing missed csCaP. The RPCRC-4Kscore combination resulted in a slight additional net reduction of 3.3 biopsies per 100 men. CONCLUSIONS: The RPCRC and 4Kscore had similar reductions of unnecessary biopsies and overdiagnosis of indolent disease. Combination of both models slightly reduced unnecessary biopsies further. Gain in net benefit must, however, be weighed against additional costs and availability of tests.

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.

What is an acceptable false negative rate in the detection of prostate cancer?

BACKGROUND: In prostate cancer (PCa) screening men and their physicians aim to rule out the presence of potentially life threatening PCa. To date, prostate specific antigen (PSA) testing and systematic prostate biopsy (Bx)-in case of an elevated PSA-are still the main modes of PCa detection. Often uncertainty remains when a PSA-test is <3.0 ng/mL or a Bx shows a benign result, leading to the continuous repeating of procedures. Here we assess the potential consequences of false negatives by studying follow-up data of a purely PSA-based approach with applying sextant Bx, an approach considered to have a high risk of missing PCa diagnosis. METHODS: Our study population consisted of 19,970 men from the ERSPC project section Rotterdam, initially screened in 1993-1999. We assessed clinically significant Gleason ≥3+4 PCa (csPCa) diagnosis within the 4-year screening interval and subsequent screening round 4 years later in men having a PSA <3.0 ng/mL at initial screening (no Bx) and men with Bx (PSA >3.0 ng/mL), but no PCa detected at that time. In addition, we addressed PCa mortality and PCa diagnosis for men with a negative PSA test and negative Bx, who were retested every 4 years covering a 15-year follow-up. RESULTS: A total of 14,935 men had PSA <3.0 ng/mL in the initial screening round, of whom 75 (0.5%) were diagnosed with csPCa at a subsequent screening examination and 2 (<0.1%) in the 4-year screening interval. For 2,260 men with a previously negative Bx at first screening, the figures were 17 (0.8%) and 2 (0.1%) respectively. Indolent PCa (Gleason ≤3+3) was diagnosed in 312 (2%) men with PSA <3.0 ng/mL initially and 115 (5%) men with initial negative Bx. After a 15-year follow-up, 45 (0.3%) PCa deaths occurred in men with initially low PSA, and 29 men (0.2%) had metastasis. For men with negative Bx, 11 (0.5%) PCa deaths occurred and 4 (0.2%) experienced metastasis. CONCLUSIONS: The false negative rates for men with PSA <3.0 ng/mL and negative sextant Bx are extremely low but not negligible. Proper risk stratification before deciding to biopsy is expected to hardly miss any clinical significant PCa diagnosis. This is especially relevant with the increased use of the relatively expensive multi-parametric magnetic resonance imaging (mpMRI) guided targeted Bx procedures.

Head-to-head comparison of prostate cancer risk calculators predicting biopsy outcome.

BACKGROUND: Multivariable risk calculators (RCs) predicting prostate cancer (PCa) aim to reduce unnecessary workup (e.g., MRI and biopsy) by selectively identifying those men at risk for PCa or clinically significant PCa (csPCa) (Gleason ≥7). The lack of an adequate comparison makes choosing between RCs difficult for patients, clinicians and guideline developers. We aim to perform a head-to-head comparison of seven well known RCs predicting biopsy outcome. METHODS: Our study comprised 7,119 men from ten independent contemporary cohorts in Europe and Australia, who underwent prostate biopsy between 2007 and 2015. We evaluated the performance of the ERSPC RPCRC, Finne, Chun, ProstataClass, Karakiewicz, Sunnybrook, and PCPT 2.0 (HG) RCs in predicting the presence of any PCa and csPCa. Performance was assessed by discrimination, calibration and net benefit analyses. RESULTS: A total of 3,458 (48%) PCa were detected; 1,784 (25%) men had csPCa. No particular RC stood out predicting any PCa: pooled area under the ROC-curve (AUC) ranged between 0.64 and 0.72. The ERSPC RPCRC had the highest pooled AUC 0.77 (95% CI: 0.73-0.80) when predicting csPCa. Decision curve analysis (DCA) showed limited net benefit in the detection of csPCa, but that can be improved by a simple calibration step. The main limitation is the retrospective design of the study. CONCLUSIONS: No particular RC stands out when predicting biopsy outcome on the presence of any PCa. The ERSPC RPCRC is superior in identifying those men at risk for csPCa. Net benefit analyses show that a multivariate approach before further workup is advisable.

Reporting and Interpreting Decision Curve Analysis: A Guide for Investigators.

CONTEXT: Urologists regularly develop clinical risk prediction models to support clinical decisions. In contrast to traditional performance measures, decision curve analysis (DCA) can assess the utility of models for decision making. DCA plots net benefit (NB) at a range of clinically reasonable risk thresholds. OBJECTIVE: To provide recommendations on interpreting and reporting DCA when evaluating prediction models. EVIDENCE ACQUISITION: We informally reviewed the urological literature to determine investigators' understanding of DCA. To illustrate, we use data from 3616 patients to develop risk models for high-grade prostate cancer (n=313, 9%) to decide who should undergo a biopsy. The baseline model includes prostate-specific antigen and digital rectal examination; the extended model adds two predictors based on transrectal ultrasound (TRUS). EVIDENCE SYNTHESIS: We explain risk thresholds, NB, default strategies (treat all, treat no one), and test tradeoff. To use DCA, first determine whether a model is superior to all other strategies across the range of reasonable risk thresholds. If so, that model appears to improve decisions irrespective of threshold. Second, consider if there are important extra costs to using the model. If so, obtain the test tradeoff to check whether the increase in NB versus the best other strategy is worth the additional cost. In our case study, addition of TRUS improved NB by 0.0114, equivalent to 1.1 more detected high-grade prostate cancers per 100 patients. Hence, adding TRUS would be worthwhile if we accept subjecting 88 patients to TRUS to find one additional high-grade prostate cancer or, alternatively, subjecting 10 patients to TRUS to avoid one unnecessary biopsy. CONCLUSIONS: The proposed guidelines can help researchers understand DCA and improve application and reporting. PATIENT SUMMARY: Decision curve analysis can identify risk models that can help us make better clinical decisions. We illustrate appropriate reporting and interpretation of decision curve analysis.

Reduction of MRI-targeted biopsies in men with low-risk prostate cancer on active surveillance by stratifying to PI-RADS and PSA-density, with different thresholds for significant disease.

BACKGROUND: The fear of undergrading prostate cancer (PCa) in men on active surveillance (AS) have led to strict criteria for monitoring, which have resulted in good long-term cancer-specific survival, proving the safety of this approach. Reducing undergrading, MRI-targeted biopsies are increasingly used in men with low-risk disease despite their undefined role yet. The objective of this study is to investigate the rate of upgrading using MRI-targeted biopsies in men with low-risk disease on AS, stratified on the basis of PI-RADS and PSA-density, with the aim to reduce potential unnecessary repeat biopsy procedures. METHODS: A total of 331 men were prospectively enrolled following the MRI-PRIAS protocol. MR imaging was according to Prostate Imaging Reporting and Data System (PI-RADSv2) guidelines. Suspicious MRI lesions (PI-RADS 3-5) were additionally targeted by MRI-TRUS fusion biopsies. Outcome measure was upgrading to Gleason score (GS) ≥3+4 with MRI-targeted biopsies, stratified for PI-RADS and PSA-density. RESULTS: In total, 25% (82/331) of men on AS showed upgrading from GS 3+3. Only 3% (11/331) was upgraded to GS ≥8. In 60% (198/331) a suspicious MRI lesion was identified, but in only 41% (82/198) of men upgrading was confirmed. PI-RADS 3, 4 and 5 categorized index lesions, showed upgrading in 30%, 34% and 66% of men, respectively. Stratification to PI-RADS 4-5, instead of PI-RADS 3-5, would have missed a small number of high volume Gleason 4 PCa in PI-RADS 3 category. However, further stratification into PI-RADS 3 lesions and PSA-density <0.15 ng/mL2 could result in a safe targeted biopsy reduction of 36% in this category, without missing any upgrades. CONCLUSIONS: Stratification with the combination of PI-RADS and PSA-density may reduce unnecessary additional MRI biopsy testing. Overall, the high rate of detected upgrading in men on AS may result in an unintended tightening of continuing in AS. Since patients, included under current AS criteria showed extremely favorable outcome, there might be no need to further restrict continuing on AS with MRI and targeted biopsies.

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.