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.

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.

Early detection of prostate cancer: AUA Guideline.

PURPOSE: The guideline purpose is to provide the urologist with a framework for the early detection of prostate cancer in asymptomatic average risk men. MATERIALS AND METHODS: A systematic review was conducted and summarized evidence derived from over 300 studies that addressed the predefined outcomes of interest (prostate cancer incidence/mortality, quality of life, diagnostic accuracy and harms of testing). In addition to the quality of evidence, the panel considered values and preferences expressed in a clinical setting (patient-physician dyad) rather than having a public health perspective. Guideline statements were organized by age group in years (age <40; 40 to 54; 55 to 69; ≥ 70). RESULTS: Except prostate specific antigen-based prostate cancer screening, there was minimal evidence to assess the outcomes of interest for other tests. The quality of evidence for the benefits of screening was moderate, and evidence for harm was high for men age 55 to 69 years. For men outside this age range, evidence was lacking for benefit, but the harms of screening, including over diagnosis and overtreatment, remained. Modeled data suggested that a screening interval of two years or more may be preferred to reduce the harms of screening. CONCLUSIONS: The Panel recommended shared decision-making for men age 55 to 69 years considering PSA-based screening, a target age group for whom benefits may outweigh harms. Outside this age range, PSA-based screening as a routine could not be recommended based on the available evidence.

Improving the Early Detection of Clinically Significant Prostate Cancer in Men in the Challenging Prostate Imaging-Reporting and Data System 3 Category.

BACKGROUND: Prostate Imaging-Reporting and Data System (PI-RADS) category 3 is a challenging scenario for detection of clinically significant prostate cancer (csPCa) and some tools can improve the selection of appropriate candidates for prostate biopsy. OBJECTIVE: To assess the performance of the European Randomized Study of Screening for Prostate Cancer (ERSPC) magnetic resonance imaging (MRI) model, the new Proclarix test, and prostate-specific antigen density (PSAD) in selecting candidates for prostate biopsy among men in the PI-RADS 3 category. DESIGN SETTING AND PARTICIPANTS: We conducted a head-to-head prospective analysis of 567 men suspected of having PCa for whom guided and systematic biopsies were scheduled between January 2018 and March 2020 in a single academic institution. A PI-RADS v.2 category 3 lesion was identified in 169 men (29.8%). OUTCOME MEASUREMENT AND STATISTICAL ANALYSIS: csPCa, insignificant PCa (iPCa), and unnecessary biopsy rates were analysed. csPCa was defined as grade group ≥2. Receiver operating characteristic (ROC) curves, decision curve analysis curves, and clinical utility curves were plotted. RESULTS AND LIMITATIONS: PCa was detected in 53/169 men (31.4%) with a PI-RADS 3 lesion, identified as csPCa in 25 (14.8%) and iPCa in 28 (16.6%). The area under the ROC curve for csPCa detection was 0.703 (95% confidence interval [CI] 0.621-0.768) for Proclarix, 0.657 (95% CI 0.547-0.766) for the ERSPC MRI model, and 0.612 (95% CI 0.497-0.727) for PSAD (p = 0.027). The threshold with the highest sensitivity was 10% for Proclarix, 1.5% for the ERSPC MRI model, and 0.07 ng/ml/cm3 for PSAD, which yielded sensitivity of 100%, 91%, and 84%, respectively. Some 21.3%, 26.2%, and 7.1% of biopsies would be avoided with Proclarix, PSAD, and the ERSPC MRI model, respectively. Proclarix showed a net benefit over PSAD and the ERSPC MRI model. Both Proclarix and PSAD reduced iPCa overdetection from 16.6% to 11.3%, while the ERSPC MRI model reduced iPCa overdetection to 15.4%. CONCLUSIONS: Proclarix was more accurate in selecting appropriate candidates for prostate biopsy among men in the PI-RADS 3 category when compared to PSAD and the ERSPC MRI model. Proclarix detected 100% of csPCa cases and would reduce prostate biopsies by 21.3% and iPCa overdetection by 5.3%. PATIENT SUMMARY: We compared three methods and found that the Proclarix test can optimise the detection of clinically significant prostate cancer in men with a score of 3 on the Prostate Imaging-Reporting and Data System for magnetic resonance imaging scans.

Reducing prostate biopsies and magnetic resonance imaging with prostate cancer risk stratification.

Objectives: To recalibrate and validate the European Randomized Study of Screening for Prostate Cancer risk calculators (ERSPC RCs) 3/4 and the magnetic resonance imaging (MRI)-ERSPC-RCs to a contemporary Norwegian setting to reduce upfront prostate multiparametric MRI (mpMRI) and prostate biopsies. Patients and Methods: We retrospectively identified and entered all men who underwent prostate mpMRI and subsequent prostate biopsy between January 2016 and March 2017 in a Norwegian centre into a database. mpMRI was reported using PI-RADS v2.0 and clinically significant prostate cancer (csPCa) defined as Gleason ≥ 3 + 4. Probabilities of csPCa and any prostate cancer (PCa) on biopsy were calculated by the ERSPC RCs 3/4 and the MRI-ERSPC-RC and compared with biopsy results. RCs were then recalibrated to account for differences in prevalence between the development and current cohorts (if indicated), and calibration, discrimination and clinical usefulness assessed. Results: Three hundred and three patients were included. The MRI-ERSPC-RCs were perfectly calibrated to our cohort, although the ERSPC RCs 3/4 needed recalibration. Area under the receiver operating curve (AUC) for the ERSPC RCs 3/4 was 0.82 for the discrimination of csPCa and 0.77 for any PCa. The AUC for the MRI-ERSPC-RCs was 0.89 for csPCa and 0.85 for any PCa. Decision curve analysis showed clear net benefit for both the ERSPC RCs 3/4 (>2% risk of csPCa threshold to biopsy) and for the MRI-ERSPC-RCs (>1% risk of csPCa threshold), with a greater net benefit for the MRI-RCs. Using a >10% risk of csPCa or 20% risk of any PCa threshold for the ERSPC RCs 3/4, 15.5% of mpMRIs could be omitted, missing 0.8% of csPCa. Using the MRI-ERSPC-RCs, 23.4% of biopsies could be omitted with the same threshold, missing 0.8% of csPCa. Conclusion: The ERSPC RCs 3/4 and MRI-ERSPC-RCs can considerably reduce both upfront mpMRI and prostate biopsies with little risk of missing csPCa.

Impact of cancer screening on metastasis: A prostate cancer case study.

BACKGROUND: Trials of cancer screening present results in terms of deaths prevented, but metastasis is also a key endpoint that screening seeks to prevent. We developed a framework for projecting overall (de novo and progressive) metastases prevented in a screening trial using prostate cancer screening as a case study. METHODS: Mechanistic simulation model in which screening shifts a fraction of cases that would be metastatic at diagnosis to being non-metastatic. This shift increases the incidence of non-overdiagnosed, organ-confined cases. We use estimates of the risk of metastatic progression for these cases to project how many progress to metastasis after diagnosis and tally the projected de novo and progressive metastatic cases with and without screening. We use data on stage shift from the European Randomized Study of Screening for Prostate Cancer (ERSPC) and data on the risk of metastatic progression from the Scandinavian Prostate Cancer Group-4 trial. We estimate the relative risk and absolute risk reductions in metastatic disease at diagnosis and compare these with reductions in overall metastases. RESULTS: Assuming no effect of screening beyond initial stage shift at diagnosis, the model projects a 43% reduction in metastasis at diagnosis but a 22% reduction in the cumulative probability of metastasis over 12 years in favor of screening. These results are consistent with the empirical findings from the ERSPC. CONCLUSION: Any reduction in metastatic disease at diagnosis under screening is likely to be an overly optimistic predictor of the impact of screening on overall metastasis and disease-specific mortality.

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.

Comparison of Two Prostate Cancer Risk Calculators that Include the Prostate Health Index.

BACKGROUND: Risk prediction models for prostate cancer (PCa) have become important tools in reducing unnecessary prostate biopsies. The Prostate Health Index (PHI) may increase the predictive accuracy of such models. OBJECTIVES: To compare two PCa risk calculators (RCs) that include PHI. DESIGN, SETTING, AND PARTICIPANTS: We evaluated the predictive performance of a previously developed PHI-based nomogram and updated versions of the European Randomized Study of Screening for Prostate Cancer (ERSPC) RCs based on digital rectal examination (DRE): RC3 (no prior biopsy) and RC4 (prior biopsy). For the ERSPC updates, the original RCs were recalibrated and PHI was added as a predictor. The PHI-updated ERSPC RCs were compared with the Lughezzani nomogram in 1185 men from four European sites. Outcomes were biopsy-detectable PC and potentially advanced or aggressive PCa, defined as clinical stage >T2b and/or a Gleason score ≥7 (clinically relevant PCa). RESULTS AND LIMITATIONS: The PHI-updated ERSPC models had a combined area under the curve for the receiver operating characteristic (AUC) of 0.72 for all PCa and 0.68 for clinically relevant PCa. For the Lughezzani PHI-based nomogram, AUCs were 0.75 for all PCa and 0.69 for clinically relevant PCa. For men without a prior biopsy, PHI-updated RC3 resulted in AUCs of 0.73 for PCa and 0.66 for clinically relevant PCa. Decision curves confirmed these patterns, although the number of clinically relevant cancers was low. CONCLUSION: Differences between RCs that include PHI are small. Addition of PHI to an RC leads to further reductions in the rate of unnecessary biopsies when compared to a strategy based on prostate-specific antigen measurement. PATIENT SUMMARY: Risk prediction models for prostate cancer have become important tools in reducing unnecessary prostate biopsies. We compared two risk prediction models for prostate cancer that include the Prostate Health Index. We found that these models are equivalent to each other, and both perform better than the prostate-specific antigen test alone in predicting cancer.

An early-detection programme for prostate cancer in Saudi men: A call from a tertiary-care centre in the Eastern province.

OBJECTIVE: To review the mode of presentation and clinical course of patients with prostate cancer during a specified period, as the detection rate is tending to increase, with most patients presenting at an advanced stage, and yet the overall incidence and prevalence rates are low. PATIENTS AND METHODS: We retrospectively reviewed all aspects of care for patients who were diagnosed between May 2006 and July 2010. RESULTS: In all, 76 men had a histologically confirmed prostatic adenocarcinoma diagnosed between May 2006 and July 2010 (mean age 71.1 years, SD 8). The median (range) prostate-specific antigen level at diagnosis was 52 (1.2-16,230) ng/mL. Of the patients, 74% had a Gleason grade of â©¾ 7 on diagnosis, and 64% had extraprostatic disease on presentation. Active surveillance was adopted in four patients, and four others were maintained on watchful waiting. Six patients had a radical prostatectomy, in one of whom it was a salvage procedure. Six patients received external-beam radical radiotherapy, five of whom had neoadjuvant, concurrent and adjuvant hormonal therapy. All remaining patients were treated primarily with androgen-deprivation therapy (ADT). Of the patients on hormonal manipulation, in 56% the cancer became castrate-resistant within the mean (SD) follow-up of 17.2 (15) months. Of patients treated primarily with ADT, 34% died. The death rate among the whole group was 23%. Both percentages include both prostate cancer-specific and non-specific mortality. CONCLUSION: An advanced stage of disease at presentation mandates an early-detection, hospital-based screening programme. Further research should include many more patients and be based in several centres.

Screening for Prostate Cancer: A Review of the ERSPC and PLCO Trials.

The advent of prostate-specific antigen (PSA) testing in the early 1980s revolutionized the diagnosis of prostate cancer. As a result of PSA testing, there has been a surge in the number of prostate cancer diagnoses. This review examines the results of 2 recent landmark trials that studied the effect of screening on prostate cancer mortality: the European Randomized Study of Screening for Prostate Cancer (ERSPC) and the US-based Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial.