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Denijs FB, van Harten MJ, Meenderink JJL, Leenen RCA, Remmers S, Venderbos LDF, van den Bergh RCN, Beyer K, Roobol MJ. Risk calculators for the detection of prostate cancer: a systematic review. Prostate Cancer Prostatic Dis 2024:10.1038/s41391-024-00852-w. [PMID: 38830997 DOI: 10.1038/s41391-024-00852-w] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2024] [Revised: 05/17/2024] [Accepted: 05/23/2024] [Indexed: 06/05/2024]
Abstract
BACKGROUND Prostate cancer (PCa) (early) detection poses significant challenges, including unnecessary testing and the risk of potential overdiagnosis. The European Association of Urology therefore suggests an individual risk-adapted approach, incorporating risk calculators (RCs) into the PCa detection pathway. In the context of 'The PRostate Cancer Awareness and Initiative for Screening in the European Union' (PRAISE-U) project ( https://uroweb.org/praise-u ), we aim to provide an overview of the currently available clinical RCs applicable in an early PCa detection algorithm. METHODS We performed a systematic review to identify RCs predicting detection of clinically significant PCa at biopsy. A search was performed in the databases Medline ALL, Embase, Web of Science Core Collection, Cochrane Central Register of Controlled Trials and Google Scholar for publications between January 2010 and July 2023. We retrieved relevant literature by using the terms "prostate cancer", "screening/diagnosis" and "predictive model". Inclusion criteria included systematic reviews, meta-analyses, and clinical trials. Exclusion criteria applied to studies involving pre-targeted high-risk populations, diagnosed PCa patients, or a sample sizes under 50 men. RESULTS We identified 6474 articles, of which 140 were included after screening abstracts and full texts. In total, we identified 96 unique RCs. Among these, 45 underwent external validation, with 28 validated in multiple cohorts. Of the externally validated RCs, 17 are based on clinical factors, 19 incorporate clinical factors along with MRI details, 4 were based on blood biomarkers alone or in combination with clinical factors, and 5 included urinary biomarkers. The median AUC of externally validated RCs ranged from 0.63 to 0.93. CONCLUSIONS This systematic review offers an extensive analysis of currently available RCs, their variable utilization, and performance within validation cohorts. RCs have consistently demonstrated their capacity to mitigate the limitations associated with early detection and have been integrated into modern practice and screening trials. Nevertheless, the lack of external validation data raises concerns about numerous RCs, and it is crucial to factor in this omission when evaluating whether a specific RC is applicable to one's target population.
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Affiliation(s)
- Frederique B Denijs
- Department of Urology, Erasmus MC Cancer Institute, University Medical Center Rotterdam, Rotterdam, The Netherlands.
| | - Meike J van Harten
- Department of Oncological Urology, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Jonas J L Meenderink
- Department of Urology, Erasmus MC Cancer Institute, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Renée C A Leenen
- Department of Urology, Erasmus MC Cancer Institute, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Sebastiaan Remmers
- Department of Urology, Erasmus MC Cancer Institute, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Lionne D F Venderbos
- Department of Urology, Erasmus MC Cancer Institute, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Roderick C N van den Bergh
- Department of Urology, Erasmus MC Cancer Institute, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Katharina Beyer
- Department of Urology, Erasmus MC Cancer Institute, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Monique J Roobol
- Department of Urology, Erasmus MC Cancer Institute, University Medical Center Rotterdam, Rotterdam, The Netherlands
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Orbe Villota PM, Leiva Centeno JA, Lugones J, Minuzzi PG, Varea SM. Comparison between the European Randomized Study for Screening of Prostate Cancer (ERSPC) and Prostate Biopsy Collaborative Group (PBCG) risk calculators: Prediction of clinically significant Prostate Cancer risk in a cohort of patients from Argentina. Actas Urol Esp 2024; 48:210-217. [PMID: 37827241 DOI: 10.1016/j.acuroe.2023.10.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2023] [Revised: 07/24/2023] [Accepted: 07/25/2023] [Indexed: 10/14/2023]
Abstract
OBJECTIVE To compare the performance of the risk calculators of the European Randomized Study for Screening of Prostate Cancer (ERSPC) and the Prostate Biopsy Collaborative Group (PBCG) in predicting the risk of presenting clinically significant prostate cancer. MATERIAL AND METHODS Retrospectively, patients who underwent prostate biopsy at Sanatorio Allende Cerro, Ciudad de Córdoba, Argentina, were identified from January 2018 to December 2021. The probability of having prostate cancer was calculated with the two calculators separately and then the results were compared to establish which of the two performed better. For this, areas under the curve (AUC) were analyzed. RESULTS 250 patients were included, 140 (56%) presented prostate cancer, of which 92 (65.71%) had clinically significant prostate cancer (Gleason score ≥7). The patients who presented cancer were older, had a higher prostate-specific antigen (PSA) value, and had a smaller prostate size. The AUC to predict the probability of having clinically significant prostate cancer was 0.79 and 0.73 for PBCG-RC and ERSPC-RC respectively (P=0.0084). CONCLUSION In this cohort of patients, both prostate cancer risk calculators performed well in predicting clinically significant prostate cancer risk, although the PBCG-RC showed better accuracy.
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Affiliation(s)
| | | | - J Lugones
- Servicio de Diagnóstico por Imágenes, Sanatorio Allende, Córdoba, Argentina
| | - P G Minuzzi
- Servicio de Urología, Sanatorio Allende, Córdoba, Argentina
| | - S M Varea
- Servicio de Urología, Sanatorio Allende, Córdoba, Argentina
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3
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Hermanns T, Wettstein MS, Kaufmann B, Lautenbach N, Kaufmann E, Saba K, Schmid FA, Hötker AM, Müntener M, Umbehr M, Poyet C. BioPrev-C - development and validation of a contemporary prostate cancer risk calculator. Front Oncol 2024; 14:1343999. [PMID: 38450183 PMCID: PMC10915644 DOI: 10.3389/fonc.2024.1343999] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2023] [Accepted: 01/30/2024] [Indexed: 03/08/2024] Open
Abstract
Objectives To develop a novel biopsy prostate cancer (PCa) prevention calculator (BioPrev-C) using data from a prospective cohort all undergoing mpMRI targeted and transperineal template saturation biopsy. Materials and methods Data of all men who underwent prostate biopsy in our academic tertiary care center between 11/2016 and 10/2019 was prospectively collected. We developed a clinical prediction model for the detection of high-grade PCa (Gleason score ≥7) based on a multivariable logistic regression model incorporating age, PSA, prostate volume, digital rectal examination, family history, previous negative biopsy, 5-alpha-reductase inhibitor use and MRI PI-RADS score. BioPrev-C performance was externally validated in another prospective Swiss cohort and compared with two other PCa risk-calculators (SWOP-RC and PBCG-RC). Results Of 391 men in the development cohort, 157 (40.2%) were diagnosed with high-grade PCa. Validation of the BioPrev C revealed good discrimination with an area under the curve for high-grade PCa of 0.88 (95% Confidence Interval 0.82-0.93), which was higher compared to the other two risk calculators (0.71 for PBCG and 0.84 for SWOP). The BioPrev-C revealed good calibration in the low-risk range (0 - 0.25) and moderate overestimation in the intermediate risk range (0.25 - 0.75). The PBCG-RC showed good calibration and the SWOP-RC constant underestimation of high-grade PCa over the whole prediction range. Decision curve analyses revealed a clinical net benefit for the BioPrev-C at a clinical meaningful threshold probability range (≥4%), whereas PBCG and SWOP calculators only showed clinical net benefit above a 30% threshold probability. Conclusion BiopPrev-C is a novel contemporary risk calculator for the prediction of high-grade PCa. External validation of the BioPrev-C revealed relevant clinical benefit, which was superior compared to other well-known risk calculators. The BioPrev-C has the potential to significantly and safely reduce the number of men who should undergo a prostate biopsy.
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Affiliation(s)
- Thomas Hermanns
- Department of Urology, University Hospital Zürich, University of Zürich, Zürich, Switzerland
| | - Marian S. Wettstein
- Department of Urology, University Hospital Zürich, University of Zürich, Zürich, Switzerland
| | - Basil Kaufmann
- Department of Urology, University Hospital Zürich, University of Zürich, Zürich, Switzerland
| | - Noémie Lautenbach
- Department of Urology, University Hospital Zürich, University of Zürich, Zürich, Switzerland
| | - Ernest Kaufmann
- Department of Urology, University Hospital Zürich, University of Zürich, Zürich, Switzerland
| | - Karim Saba
- Department of Urology, University Hospital Zürich, University of Zürich, Zürich, Switzerland
| | - Florian A. Schmid
- Department of Urology, University Hospital Zürich, University of Zürich, Zürich, Switzerland
| | - Andreas M. Hötker
- Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | | | - Martin Umbehr
- Department of Urology, Stadtspital Triemli, Zürich, Switzerland
| | - Cédric Poyet
- Department of Urology, University Hospital Zürich, University of Zürich, Zürich, Switzerland
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Pallauf M, Steinkohl F, Zimmermann G, Horetzky M, Rajwa P, Pradere B, Lindner AK, Pichler R, Kunit T, Shariat SF, Lusuardi L, Drerup M. External validation of two mpMRI-risk calculators predicting risk of prostate cancer before biopsy. World J Urol 2022; 40:2451-2457. [PMID: 35941246 PMCID: PMC9512729 DOI: 10.1007/s00345-022-04119-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2022] [Accepted: 07/22/2022] [Indexed: 11/05/2022] Open
Abstract
PURPOSE Risk calculators (RC) aim to improve prebiopsy risk stratification. Their latest versions now include multiparametric magnetic resonance imaging (mpMRI) findings. For their implementation into clinical practice, critical external validations are needed. METHODS We retrospectively analyzed the patient data of 554 men who underwent ultrasound-guided targeted and systematic prostate biopsies at 2 centers. We validated the mpMRI-RCs of Radtke et al. (RC-R) and Alberts et al. (RC-A), previously shown to predict prostate cancer (PCa) and clinically significant PCa (csPCa). We assessed these RCs' prediction accuracy by analyzing the receiver-operating characteristics (ROC) curve and evaluated their clinical utility using Decision Curve Analysis (DCA), including Net-Benefit and Net-Reduction curves. RESULTS We found that the Area Under the ROC Curve (AUC) for predicting PCa was 0.681 [confidence interval (CI) 95% 0.635-0.727] for RC-A. The AUCs for predicting csPCa were 0.635 (CI 95% 0.583-0.686) for RC-A and 0.676 (CI 95% 0.627-0.725) for RC-R. For example, at a risk threshold of 12%, RC-A needs to assess 334 and RC-R 500 patients to detect one additional true positive PCa or csPCa patient, respectively. At the same risk threshold of 12%, RC-A only needs to assess 6 and RC-R 16 patients to detect one additional true negative PCa or csPCa patient. CONCLUSION The mpMRI-RCs, RC-R and RC-A, are robust and valuable tools for patient counseling. Although they do not improve PCa and csPCa detection rates by a clinically meaningful margin, they aid in avoiding unnecessary prostate biopsies. Their implementation could reduce overdiagnosis and reduce PCa screening morbidity.
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Affiliation(s)
- Maximilian Pallauf
- Department of Urology, University Hospital Salzburg, Paracelsus Medical University, Muellner Hauptstraße 48, 5020, Salzburg, Austria
- Department of Urology, Comprehensive Cancer Center, Medical University of Vienna, Vienna, Austria
| | - Fabian Steinkohl
- Department of Radiology, Hospital St. Vinzenz Zams, Zams, Austria
| | - Georg Zimmermann
- Team Biostatistics and Big Medical Data, IDA Lab Salzburg, Paracelsus Medical University, Salzburg, Austria
- Research and Innovation Management, Paracelsus Medical University, Salzburg, Austria
| | - Maximilian Horetzky
- Department of Urology, University Hospital Salzburg, Paracelsus Medical University, Muellner Hauptstraße 48, 5020, Salzburg, Austria
| | - Pawel Rajwa
- Department of Urology, Comprehensive Cancer Center, Medical University of Vienna, Vienna, Austria
- Department of Urology, Medical University of Silesia, Zabrze, Poland
| | - Benjamin Pradere
- Department of Urology, Comprehensive Cancer Center, Medical University of Vienna, Vienna, Austria
- Department of Urology, La Croix du Sud Hôpital, Quint Fonsegrives, France
| | | | - Renate Pichler
- Department of Urology, Medical University of Innsbruck, Innsbruck, Austria
| | - Thomas Kunit
- Department of Urology, University Hospital Salzburg, Paracelsus Medical University, Muellner Hauptstraße 48, 5020, Salzburg, Austria
| | - Shahrokh F Shariat
- Department of Urology, Comprehensive Cancer Center, Medical University of Vienna, Vienna, Austria
- Department of Urology, Weill Cornell Medical College, New York, NY, USA
- Department of Urology, University of Texas Southwestern, Dallas, TX, USA
- Institute for Urology and Reproductive Health I.M. Sechenov First Moscow State Medical University, Moscow, Russia
- Hourani Center for Applied Scientific Research, Al-Ahliyya Amman University, Amman, Jordan
- Department of Urology, Second Faculty of Medicine, Charles University, Prague, Czech Republic
- Karl Landsteiner Society, Vienna, Austria
| | - Lukas Lusuardi
- Department of Urology, University Hospital Salzburg, Paracelsus Medical University, Muellner Hauptstraße 48, 5020, Salzburg, Austria
| | - Martin Drerup
- Department of Urology, University Hospital Salzburg, Paracelsus Medical University, Muellner Hauptstraße 48, 5020, Salzburg, Austria.
- Department of Urology, Hospital Barmherzige Brüder Salzburg, Salzburg, Austria.
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Gupta K, Perchik JD, Fang AM, Porter KK, Rais-Bahrami S. Augmenting prostate magnetic resonance imaging reporting to incorporate diagnostic recommendations based upon clinical risk calculators. World J Radiol 2022; 14:249-255. [PMID: 36160831 PMCID: PMC9453318 DOI: 10.4329/wjr.v14.i8.249] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/22/2022] [Revised: 06/27/2022] [Accepted: 07/25/2022] [Indexed: 02/08/2023] Open
Abstract
Risk calculators have offered a viable tool for clinicians to stratify patients at risk of prostate cancer (PCa) and to mitigate the low sensitivity and specificity of screening prostate specific antigen (PSA). While initially based on clinical and demographic data, incorporation of multiparametric magnetic resonance imaging (MRI) and the validated prostate imaging reporting and data system suspicion scoring system has standardized and improved risk stratification beyond the use of PSA and patient parameters alone. Biopsy-naïve patients with lower risk profiles for harboring clinically significant PCa are often subjected to uncomfortable, invasive, and potentially unnecessary prostate biopsy procedures. Incorporating risk calculator data into prostate MRI reports can broaden the role of radiologists, improve communication with clinicians primarily managing these patients, and help guide clinical care in directing the screening, detection, and risk stratification of PCa.
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Affiliation(s)
- Karisma Gupta
- Department of Radiology, University of Washington, Seattle, WA 98195, United States
| | - Jordan D Perchik
- Department of Radiology, University of Alabama at Birmingham, Birmingham, AL 35233, United States
| | - Andrew M Fang
- Department of Urology, University of Alabama at Birmingham, Birmingham, AL 35233, United States
| | - Kristin K Porter
- Department of Radiology, University of Alabama at Birmingham, Birmingham, AL 35233, United States
| | - Soroush Rais-Bahrami
- Department of Radiology, University of Alabama at Birmingham, Birmingham, AL 35233, United States
- Department of Urology, University of Alabama at Birmingham, Birmingham, AL 35233, United States
- O'Neal Comprehensive Cancer Center, University of Alabama at Birmingham, Birmingham, AL 35233, United States
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6
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Chau EM, Russell B, Santaolalla A, Van Hemelrijck M, McCracken S, Page T, Liyanage SH, Aning J, Gnanapragasam VJ, Acher P. MRI-based nomogram for the prediction of prostate cancer diagnosis: A multi-centre validated patient–physician decision tool. JOURNAL OF CLINICAL UROLOGY 2022. [DOI: 10.1177/20514158211065949] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/02/2023]
Abstract
Objective: To update and externally validate a magnetic resonance imaging (MRI)-based nomogram for predicting prostate biopsy outcomes with a multi-centre cohort. Materials and methods: Prospective data from five UK-based centres were analysed. All men were biopsy naïve. Those with missing data, no MRI, or prostate-specific antigen (PSA) > 30 ng/mL were excluded. Logistic regression analysis was used to confirm predictors of prostate cancer outcomes including MRI-PIRADS (Prostate Imaging Reporting and Data System) score, PSA density, and age. Clinically significant disease was defined as International Society of Urological Pathology (ISUP) Grade Group ⩾ 2 (Gleason grade ⩾ 7). Biopsy strategy included transrectal and transperineal approaches. Nomograms were produced using logistic regression analysis results. Results: A total of 506 men were included in the analysis with median age 66 (interquartile range (IQR) = 60–69). Median PSA was 6.6 ng/mL (IQR = 4.72–9.26). PIRADS ⩾ 3 was reported in 387 (76.4%). Grade Group ⩾ 2 detection was 227 (44.9%) and 318 (62.8%) for any cancer. Performance of the MRI-based nomogram was an area under curve (AUC) of 0.84 (95% confidence interval (CI) = 0.81–0.88) for Grade Group ⩾ 2% and 0.85 (95% CI = 0.82–0.88) for any prostate cancer. Conclusion: We present external validation of a novel MRI-based nomogram in a multi-centre UK-based cohort, showing good discrimination in identifying men at high risk of having clinically significant disease. These findings support this risk calculator use in the prostate biopsy decision-making process. Level of evidence: 2c
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Affiliation(s)
- Edwin M Chau
- Department of Urology, Southend University Hospital, UK
| | - Beth Russell
- Translational Oncology and Urology Research, King’s College London, UK
| | - Aida Santaolalla
- Translational Oncology and Urology Research, King’s College London, UK
| | | | - Stuart McCracken
- Department of Urology, South Tyneside and Sunderland NHS Trust, UK
| | - Toby Page
- Department of Urology, Newcastle Hospitals NHS Trust, UK
| | | | | | - Vincent J Gnanapragasam
- Department of Urology, Cambridge University Hospitals Trust, UK
- Division of Urology, Department of Surgery, University of Cambridge, UK
| | - Peter Acher
- Department of Urology, Southend University Hospital, UK
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7
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Brinkley GJ, Fang AM, Rais-Bahrami S. Integration of magnetic resonance imaging into prostate cancer nomograms. Ther Adv Urol 2022; 14:17562872221096386. [PMID: 35586139 PMCID: PMC9109484 DOI: 10.1177/17562872221096386] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2021] [Accepted: 04/05/2022] [Indexed: 11/16/2022] Open
Abstract
The decision whether to undergo prostate biopsy must be carefully weighed. Nomograms have widely been utilized as risk calculators to improve the identification of prostate cancer by weighing several clinical factors. The recent inclusion of multiparametric magnetic resonance imaging (mpMRI) findings into nomograms has drastically improved their nomogram's accuracy at identifying clinically significant prostate cancer. Several novel nomograms have incorporated mpMRI to aid in the decision-making process in proceeding with a prostate biopsy in patients who are biopsy-naïve, have a prior negative biopsy, or are on active surveillance. Furthermore, novel nomograms have incorporated mpMRI to aid in treatment planning of definitive therapy. This literature review highlights how the inclusion of mpMRI into prostate cancer nomograms has improved upon their performance, potentially reduce unnecessary procedures, and enhance the individual risk assessment by improving confidence in clinical decision-making by both patients and their care providers.
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Affiliation(s)
- Garrett J Brinkley
- Heersink School of Medicine, The University of Alabama at Birmingham, Birmingham, AL, USA
| | - Andrew M Fang
- Department of Urology, The University of Alabama at Birmingham, Birmingham, AL, USA
| | - Soroush Rais-Bahrami
- Department of Urology, The University of Alabama at Birmingham, Faculty Office Tower 1107, 510 20th Street South, Birmingham, AL 35294, USA
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8
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Bandala-Jacques A, Castellanos Esquivel KD, Pérez-Hurtado F, Hernández-Silva C, Reynoso-Noverón N. Prostate Cancer Risk Calculators for Healthy Populations: Systematic Review. JMIR Cancer 2021; 7:e30430. [PMID: 34477564 PMCID: PMC8449298 DOI: 10.2196/30430] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2021] [Revised: 07/12/2021] [Accepted: 07/28/2021] [Indexed: 11/15/2022] Open
Abstract
Background Screening for prostate cancer has long been a debated, complex topic. The use of risk calculators for prostate cancer is recommended for determining patients’ individual risk of cancer and the subsequent need for a prostate biopsy. These tools could lead to better discrimination of patients in need of invasive diagnostic procedures and optimized allocation of health care resources Objective The goal of the research was to systematically review available literature on the performance of current prostate cancer risk calculators in healthy populations by comparing the relative impact of individual items on different cohorts and on the models’ overall performance. Methods We performed a systematic review of available prostate cancer risk calculators targeted at healthy populations. We included studies published from January 2000 to March 2021 in English, Spanish, French, Portuguese, or German. Two reviewers independently decided for or against inclusion based on abstracts. A third reviewer intervened in case of disagreements. From the selected titles, we extracted information regarding the purpose of the manuscript, analyzed calculators, population for which it was calibrated, included risk factors, and the model’s overall accuracy. Results We included a total of 18 calculators from 53 different manuscripts. The most commonly analyzed ones were the Prostate Cancer Prevention Trial (PCPT) and European Randomized Study on Prostate Cancer (ERSPC) risk calculators developed from North American and European cohorts, respectively. Both calculators provided high diagnostic ability of aggressive prostate cancer (AUC as high as 0.798 for PCPT and 0.91 for ERSPC). We found 9 calculators developed from scratch for specific populations that reached a diagnostic ability as high as 0.938. The most commonly included risk factors in the calculators were age, prostate specific antigen levels, and digital rectal examination findings. Additional calculators included race and detailed personal and family history. Conclusions Both the PCPR and ERSPC risk calculators have been successfully adapted for cohorts other than the ones they were originally created for with no loss of diagnostic ability. Furthermore, designing calculators from scratch considering each population’s sociocultural differences has resulted in risk tools that can be well adapted to be valid in more patients. The best risk calculator for prostate cancer will be that which has been calibrated for its intended population and can be easily reproduced and implemented. Trial Registration PROSPERO CRD42021242110; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=242110
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Affiliation(s)
- Antonio Bandala-Jacques
- Centro de Investigación en Prevención, Instituto Nacional de Cancerología, Mexico City, Mexico.,Centro de Investigación en Salud Poblacional, Instituto Nacional de Salud Pública, Mexico City, Mexico
| | | | - Fernanda Pérez-Hurtado
- Centro de Investigación en Prevención, Instituto Nacional de Cancerología, Mexico City, Mexico
| | | | - Nancy Reynoso-Noverón
- Centro de Investigación en Prevención, Instituto Nacional de Cancerología, Mexico City, Mexico
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9
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Garrido MM, Bernardino RM, Marta JC, Holdenrieder S, Guimarães JT. Tumour markers of prostate cancer: The post-PSA era. Ann Clin Biochem 2021; 59:46-58. [PMID: 34463154 DOI: 10.1177/00045632211041890] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
Although PSA-based prostate cancer (PCa) screening had a positive impact in reducing PCa mortality, it also led to overdiagnosis, overtreatment and to a significant number of unnecessary biopsies. In the post-PSA era, new biomarkers have emerged that can complement the information given by PSA, towards a better cancer diagnostic specificity, and also allow a better estimate of the aggressiveness of the disease and its clinical outcome. That means those markers have the potential to assist the clinician in the decision-making processes, such as whether or not to perform a biopsy, and to make the best treatment choice among the new therapeutic options available, including active surveillance (AS) in lower risk disease. In this article, we will review several of those more recent diagnostic markers (4Kscore®, [-2]proPSA and Prostate Health Index (PHI), SelectMDx®, ConfirmMDx®, Progensa® Prostate Cancer Antigen 3, Mi-Prostate Score, ExoDx™ Prostate Test, the Stockholm-3 test and ERSPC risk calculators) and prognostic markers (OncotypeDX® Genomic Prostate Score, Prolaris®, Decipher® and ProMark®). We will also address some new liquid biopsy approaches - circulating tumour cells and cell-free DNA (cfDNA) - with a potential role in metastatic castration-resistant PCa and will briefly give some future perspectives, mostly outlooking epigenetic markers.
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Affiliation(s)
- Manuel M Garrido
- Department of Clinical Pathology, 90463Centro Hospitalar Universitário de Lisboa Central, Lisbon, Portugal.,Department of Laboratory Medicine, 37811Faculdade de Medicina da Universidade de Lisboa, Lisbon, Portugal
| | - Rui M Bernardino
- Department of Urology, 90463Centro Hospitalar Universitário de Lisboa central, Lisbon, Portugal
| | - José C Marta
- Department of Clinical Pathology, 90463Centro Hospitalar Universitário de Lisboa Central, Lisbon, Portugal
| | - Stefan Holdenrieder
- Institute of Laboratory Medicine, Munich Biomarker Research Center, 14924Deutsches Herzzentrum München, Technische Universität München, Munich, Germany
| | - João T Guimarães
- Department of Clinical Pathology, Centro Hospitalar Universitário de São João, Porto, Portugal.,Department of Biomedicine, Faculdade de Medicina da Universidade do Porto, Porto, Portugal.,EPIUnit, Instituto de Saúde Pública, Universidade do Porto, Porto, Portugal
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10
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Optimized Identification of High-Grade Prostate Cancer by Combining Different PSA Molecular Forms and PSA Density in a Deep Learning Model. Diagnostics (Basel) 2021; 11:diagnostics11020335. [PMID: 33670632 PMCID: PMC7922417 DOI: 10.3390/diagnostics11020335] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2021] [Revised: 02/10/2021] [Accepted: 02/15/2021] [Indexed: 01/21/2023] Open
Abstract
After skin cancer, prostate cancer (PC) is the most common cancer among men. The gold standard for PC diagnosis is based on the PSA (prostate-specific antigen) test. Based on this preliminary screening, the physician decides whether to proceed with further tests, typically prostate biopsy, to confirm cancer and evaluate its aggressiveness. Nevertheless, the specificity of the PSA test is suboptimal and, as a result, about 75% of men who undergo a prostate biopsy do not have cancer even if they have elevated PSA levels. Overdiagnosis leads to unnecessary overtreatment of prostate cancer with undesirable side effects, such as incontinence, erectile dysfunction, infections, and pain. Here, we used artificial neuronal networks to develop models that can diagnose PC efficiently. The model receives as an input a panel of 4 clinical variables (total PSA, free PSA, p2PSA, and PSA density) plus age. The output of the model is an estimate of the Gleason score of the patient. After training on a dataset of 190 samples and optimization of the variables, the model achieved values of sensitivity as high as 86% and 89% specificity. The efficiency of the method can be improved even further by training the model on larger datasets.
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11
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Aladwani M, Lophatananon A, Ollier W, Muir K. Prediction models for prostate cancer to be used in the primary care setting: a systematic review. BMJ Open 2020; 10:e034661. [PMID: 32690501 PMCID: PMC7371149 DOI: 10.1136/bmjopen-2019-034661] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Abstract
OBJECTIVE To identify risk prediction models for prostate cancer (PCa) that can be used in the primary care and community health settings. DESIGN Systematic review. DATA SOURCES MEDLINE and Embase databases combined from inception and up to the end of January 2019. ELIGIBILITY Studies were included based on satisfying all the following criteria: (i) presenting an evaluation of PCa risk at initial biopsy in patients with no history of PCa, (ii) studies not incorporating an invasive clinical assessment or expensive biomarker/genetic tests, (iii) inclusion of at least two variables with prostate-specific antigen (PSA) being one of them, and (iv) studies reporting a measure of predictive performance. The quality of the studies and risk of bias was assessed by using the Prediction model Risk Of Bias ASsessment Tool (PROBAST). DATA EXTRACTION AND SYNTHESIS Relevant information extracted for each model included: the year of publication, source of data, type of model, number of patients, country, age, PSA range, mean/median PSA, other variables included in the model, number of biopsy cores to assess outcomes, study endpoint(s), cancer detection, model validation and model performance. RESULTS An initial search yielded 109 potential studies, of which five met the set criteria. Four studies were cohort-based and one was a case-control study. PCa detection rate was between 20.6% and 55.8%. Area under the curve (AUC) was reported in four studies and ranged from 0.65 to 0.75. All models showed significant improvement in predicting PCa compared with being based on PSA alone. The difference in AUC between extended models and PSA alone was between 0.06 and 0.21. CONCLUSION Only a few PCa risk prediction models have the potential to be readily used in the primary healthcare or community health setting. Further studies are needed to investigate other potential variables that could be integrated into models to improve their clinical utility for PCa testing in a community setting.
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Affiliation(s)
- Mohammad Aladwani
- Division of Population Health, Health Services Research and Primary Care School of Health Sciences Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK
| | - Artitaya Lophatananon
- Division of Population Health, Health Services Research and Primary Care School of Health Sciences Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK
| | - William Ollier
- Division of Population Health, Health Services Research and Primary Care School of Health Sciences Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK
- School of Healthcare Science, Manchester Metropolitan University Faculty of Science and Engineering, Manchester, UK
| | - Kenneth Muir
- Division of Population Health, Health Services Research and Primary Care School of Health Sciences Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK
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Püllen L, Radtke JP, Wiesenfarth M, Roobol MJ, Verbeek JF, Wetter A, Guberina N, Pandey A, Hüttenbrink C, Tschirdewahn S, Pahernik S, Hadaschik BA, Distler FA. External validation of novel magnetic resonance imaging-based models for prostate cancer prediction. BJU Int 2019; 125:407-416. [DOI: 10.1111/bju.14958] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Lukas Püllen
- Department of Urology; University Hospital Essen; Nordrhein-Westfalen Germany
| | - Jan P. Radtke
- Department of Urology; University Hospital Essen; Nordrhein-Westfalen Germany
- Department of Radiology; German Cancer Research Centre (DKFZ); Heidelberg Germany
| | - Manuel Wiesenfarth
- Division of Biostatistics; German Cancer Research Centre (DKFZ); Heidelberg Germany
| | - Monique J. Roobol
- Department of Urology; Erasmus University Medical Centre; Rotterdam The Netherlands
| | - Jan F.M. Verbeek
- Department of Urology; Erasmus University Medical Centre; Rotterdam The Netherlands
| | - Axel Wetter
- Department of Radiology; University Hospital Essen; Nordrhein-Westfalen Germany
| | - Nika Guberina
- Department of Radiology; University Hospital Essen; Nordrhein-Westfalen Germany
| | - Abhishek Pandey
- Department of Urology; Paracelsus Medical University Nuremberg; Nürnberg Germany
| | - Clemens Hüttenbrink
- Department of Urology; Paracelsus Medical University Nuremberg; Nürnberg Germany
| | | | - Sascha Pahernik
- Department of Urology; Paracelsus Medical University Nuremberg; Nürnberg Germany
| | - Boris A. Hadaschik
- Department of Urology; University Hospital Essen; Nordrhein-Westfalen Germany
| | - Florian A. Distler
- Department of Urology; Paracelsus Medical University Nuremberg; Nürnberg Germany
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13
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Validating the European randomised study for screening of prostate cancer (ERSPC) risk calculator in a contemporary South African cohort. World J Urol 2019; 38:1711-1718. [PMID: 31522234 DOI: 10.1007/s00345-019-02947-9] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2019] [Accepted: 09/03/2019] [Indexed: 10/26/2022] Open
Abstract
INTRODUCTION Numerous prostate cancer predictive tools have been developed to help with decision-making in men needing prostate biopsy. However, they have been modelled and validated almost exclusively in Caucasian cohorts, hence limiting their use in other population groups. The aim of this study was to assess the validity of the ERSPC risk calculator in a South African cohort. METHODS Patients who have had a transrectal ultrasound (TRUS)-guided prostate biopsy at Groote Schuur Hospital from January 2008 to August 2017 were reviewed. Predictor variables were entered into the ERSPC risk calculator and results were compared with prostate biopsy pathology results. Predictive accuracy of the ERSPC risk calculator for these patients was derived using receiver operator characteristics (ROC) Area under the curve and is expressed as a percentage. RESULTS 516 prostate biopsy sessions in 475 different men were analysed. The predictive accuracy of the ERSPC risk calculator was better than a PSA/DRE strategy for the presence of cancer-0.738 (95% CI 0.695-0.781) vs 0.686 (95% CI 0.639-0.732), and for significant PCa-0.833 (95% CI 0.789-0.876) vs 0.793 (95% CI 0.741-0.846). This translated into 50 less biopsies when compared to a PSA > 4/abnormal DRE strategy. Use of the ERSPC RC would have missed eight non-significant cancers [Significant cancer being defined as having a tumour stage T2b (> 1/2 lobe involved with prostate cancer) and/or a Gleason Score equal to or greater than 7]. CONCLUSION Our results confirm the validity of the ERSPC RC in a South African cohort. Application of this calculator to the wider South African population would allow better selection of patients for prostate biopsy and spare a significant number its adverse consequences.
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Alberts AR, Roobol MJ, Verbeek JFM, Schoots IG, Chiu PK, Osses DF, Tijsterman JD, Beerlage HP, Mannaerts CK, Schimmöller L, Albers P, Arsov C. Prediction of High-grade Prostate Cancer Following Multiparametric Magnetic Resonance Imaging: Improving the Rotterdam European Randomized Study of Screening for Prostate Cancer Risk Calculators. Eur Urol 2018; 75:310-318. [PMID: 30082150 DOI: 10.1016/j.eururo.2018.07.031] [Citation(s) in RCA: 147] [Impact Index Per Article: 21.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2018] [Accepted: 07/20/2018] [Indexed: 12/26/2022]
Abstract
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.
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Affiliation(s)
- Arnout R Alberts
- Department of Urology, Erasmus University Medical Center, Rotterdam, The Netherlands.
| | - Monique J Roobol
- Department of Urology, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Jan F M Verbeek
- Department of Urology, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Ivo G Schoots
- Department of Radiology and Nuclear Medicine, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Peter K Chiu
- Department of Urology, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Daniël F Osses
- Department of Urology, Erasmus University Medical Center, Rotterdam, The Netherlands; Department of Radiology and Nuclear Medicine, Erasmus University Medical Center, Rotterdam, The Netherlands
| | | | - Harrie P Beerlage
- Department of Urology, Jeroen Bosch Hospital, Den Bosch, The Netherlands
| | | | - Lars Schimmöller
- Department of Diagnostic and Interventional Radiology, Medical Faculty, University of Düsseldorf, Düsseldorf, Germany
| | - Peter Albers
- Department of Urology, Medical Faculty, University of Düsseldorf, Düsseldorf, Germany
| | - Christian Arsov
- Department of Urology, Medical Faculty, University of Düsseldorf, Düsseldorf, Germany
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15
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De Nunzio C, Lombardo R, Tema G, Alkhatatbeh H, Gandaglia G, Briganti A, Tubaro A. External validation of Chun, PCPT, ERSPC, Kawakami, and Karakiewicz nomograms in the prediction of prostate cancer: A single center cohort-study. Urol Oncol 2018; 36:364.e1-364.e7. [DOI: 10.1016/j.urolonc.2018.05.010] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2018] [Revised: 04/01/2018] [Accepted: 05/08/2018] [Indexed: 12/27/2022]
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16
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Osses DF, Alberts AR, Bausch GCF, Roobol MJ. Multivariable risk-based patient selection for prostate biopsy in a primary health care setting: referral rate and biopsy results from a urology outpatient clinic. Transl Androl Urol 2018; 7:27-33. [PMID: 29594017 PMCID: PMC5861274 DOI: 10.21037/tau.2017.12.11] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022] Open
Abstract
Background According to their guidelines, Dutch general practitioners (GPs) refer men with prostate-specific antigen (PSA) level ≥3.0 ng/mL to the urologist for risk-based patient selection for prostate biopsy using the Rotterdam Prostate Cancer Risk Calculator (RPCRC). Use of the RPCRC in primary care could optimize the diagnostic pathway even further by reducing unnecessary referrals. To investigate this, we calculated the risk and assessed the rate of men referred to the urologist with PSA level ≥3.0 ng/mL by implementing the RPCRC in a primary health care setting. Methods In January 2014, an exploratory study was initiated in collaboration with the primary health care facility of the GP laboratory in Rotterdam. GPs were given the possibility to refer men with a suspicion of prostate cancer (PCa) or a screening wish to this primary care facility (STAR-SHL) where further assessment was performed by specially trained personnel. Risk-based advice on referral to the urologist was given to the GP on the basis of the RPCRC results. If requested, advice on the treatment of lower urinary tract symptoms (LUTS) was provided. All men signed informed consent. Results Between January 2014 and September 2017, a total of 243 men, median age 64 [interquartile range (IQR), 57-70] years were referred for a consultation at the primary care facility. Of the 108 men with PSA level ≥3.0 ng/mL and a referral related to PCa, GPs were advised to refer 58 men to the urologist (54%). Of the men with available follow-up (FU) data [n=187, median FU, 16 (IQR, 9-25) months] 54 men were considered high-risk (i.e., had an elevated risk of PCa as calculated by the RPCRC). Of these men, 51 (94%) were actually referred to secondary care by their GP, and so far 38 men underwent biopsy. PCa was detected in 30 men [47% had Gleason score (GS) ≥3+4 PCa], translating to an overall positive predictive value (PPV) of 79%. Within the available FU time, 2 out of 38 (5%) men with PSA level ≥3.0 ng/mL which were considered low-risk have been diagnosed with GS 3+3 PCa. Conclusions Risk-stratification with the RPCRC in a primary health care setting could prevent almost half of referrals of men with PSA level ≥3.0 ng/mL to the urologist. In more than three-quarters of men referred for prostate biopsy, the suspicion of PCa was confirmed and almost half of men had clinically significant PCa (GS ≥3+4 PCa). These data show a huge potential for multivariable risk-stratification in primary care.
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Affiliation(s)
- Daniël F Osses
- Department of Urology, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Arnout R Alberts
- Department of Urology, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Gonny C F Bausch
- STAR-SHL Medical Diagnostic Center, GP laboratory, Rotterdam, The Netherlands
| | - Monique J Roobol
- Department of Urology, Erasmus University Medical Center, Rotterdam, The Netherlands
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17
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Rendon RA, Mason RJ, Marzouk K, Finelli A, Saad F, So A, Violette P, Breau RH. Recommandations de l'Association des urologues du Canada sur le dépistage et le diagnostic précoce du cancer de la prostate. Can Urol Assoc J 2017; 11:298-309. [PMID: 29381452 DOI: 10.5489/cuaj.4888] [Citation(s) in RCA: 46] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
Affiliation(s)
- Ricardo A Rendon
- Département d'urologie, Université Dalhousie, Halifax, N.-É., Canada
| | - Ross J Mason
- Département d'urologie, Clinique Mayo, Rochester, Minn., États-Unis
| | - Karim Marzouk
- Division d'urologie, Centre de cancérologie Memorial Sloan Kettering, New York, NY, États-Unis
| | - Antonio Finelli
- Division d'urologie, Université de Toronto, Toronto, Ont., Canada
| | - Fred Saad
- Département de chirurgie (urologie), Université de Montréal, Montréal, Qc, Canada
| | - Alan So
- Département des sciences urologiques, Université de la Colombie-Britannique, Vancouver, C.-B., Canada
| | - Phillipe Violette
- Département de chirurgie, Université Western, London, Ont., Canada.,Départements de chirurgie et de méthodologie de recherche en santé, Données et répercussions, Université McMaster, Hamilton, Ont., Canada
| | - Rodney H Breau
- Division d'urologie, Université d'Ottawa, Ottawa, Ont., Canada
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18
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Pereira-Azevedo N, Braga I, Verbeek JF, Osório L, Cavadas V, Fraga A, Carrasquinho E, Cardoso de Oliveira E, Nieboer D, Roobol MJ. Prospective evaluation on the effect of interobserver variability of digital rectal examination on the performance of the Rotterdam Prostate Cancer Risk Calculator. Int J Urol 2017; 24:826-832. [PMID: 28901582 DOI: 10.1111/iju.13442] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2017] [Accepted: 08/02/2017] [Indexed: 11/29/2022]
Abstract
OBJECTIVES To assess the level of agreement between digital rectal examination findings of two urologists and its effect on risk prediction using the digital rectal examination-based Rotterdam Prostate Cancer Risk Calculator. METHODS The study sample consisted of a prospective cohort of asymptomatic unscreened men with prostate-specific antigen ≤50.0 ng/mL and transrectal ultrasound volume ≤110 mL who underwent transrectal ultrasound-guided prostate biopsy. Both urologists' digital rectal examination findings were graded normal or abnormal (nodularity and/or induration), and volume classified as 25, 40 or 60 mL, according to the risk calculator algorithm. Interrater agreement analysis using Cohen's kappa (κ) statistic was carried out to determine consistency of digital rectal examination outcome and volume assessment. Receiver operating characteristic curve analysis and calibration plots were constructed to determine the effect of interrater differences. Decision curve analysis was applied to evaluate the clinical usefulness of the model. RESULTS Of the 241 men included in the study, 41% (n = 98) had prostate cancer (81 were clinically significant, i.e. Gleason ≥3 + 4). There was substantial agreement in the digital rectal examination (abnormal/normal; κ = 0.78; P < 0.001) and volume estimation (κ = 0.79; P < 0.001). Receiver operating characteristic analyses showed good discrimination (0.75-0.78) and were comparable for both urologists. In the high-risk cohort, at a probability threshold of 25%, the risk calculator reduced the prostate biopsy rate by 9%, without missing cancers. CONCLUSIONS Slight differences in digital rectal examination findings seem to have very limited impact on the performance of the Rotterdam Prostate Cancer Risk Calculator. Therefore, this can be considered a useful prostate biopsy outcome prediction tool.
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Affiliation(s)
- Nuno Pereira-Azevedo
- Department of Urology, Erasmus University Medical Center, Rotterdam, the Netherlands.,Urology Department, Porto Hospital Centre, Porto, Portugal
| | - Isaac Braga
- Urology Department, Porto Hospital Centre, Porto, Portugal.,Life and Health Sciences Research Institute, School of Health Sciences, University of Minho and ICVS/3B's, Braga/Guimarães, Portugal
| | - Jan Fm Verbeek
- Department of Urology, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - Luís Osório
- Urology Department, Porto Hospital Centre, Porto, Portugal
| | - Vítor Cavadas
- Urology Department, Porto Hospital Centre, Porto, Portugal
| | - Avelino Fraga
- Urology Department, Porto Hospital Centre, Porto, Portugal
| | | | | | - Daan Nieboer
- Department of Urology, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - Monique J Roobol
- Department of Urology, Erasmus University Medical Center, Rotterdam, the Netherlands
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19
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Alberts AR, Schoots IG, Bokhorst LP, Drost FJH, van Leenders GJ, Krestin GP, Dwarkasing RS, Barentsz JO, Schröder FH, Bangma CH, Roobol MJ. Characteristics of Prostate Cancer Found at Fifth Screening in the European Randomized Study of Screening for Prostate Cancer Rotterdam: Can We Selectively Detect High-grade Prostate Cancer with Upfront Multivariable Risk Stratification and Magnetic Resonance Imaging? Eur Urol 2017. [PMID: 28647216 DOI: 10.1016/j.eururo.2017.06.019] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
Abstract
BACKGROUND The harm of screening (unnecessary biopsies and overdiagnosis) generally outweighs the benefit of reducing prostate cancer (PCa) mortality in men aged ≥70 yr. Patient selection for biopsy using risk stratification and magnetic resonance imaging (MRI) may improve this benefit-to-harm ratio. OBJECTIVE To assess the potential of a risk-based strategy including MRI to selectively identify men aged ≥70 yr with high-grade PCa. DESIGN, SETTING, AND PARTICIPANTS Three hundred and thirty-seven men with prostate-specific antigen ≥3.0 ng/ml at a fifth screening (71-75 yr) in the European Randomized study of Screening for Prostate Cancer Rotterdam were biopsied. One hundred and seventy-nine men received six-core transrectal ultrasound biopsy (TRUS-Bx), while 158 men received MRI, 12-core TRUS-Bx, and fusion TBx in case of Prostate Imaging Reporting and Data System ≥3 lesions. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS The primary outcome was the overall, low-grade (Gleason Score 3+3) and high-grade (Gleason Score ≥ 3+4) PCa rate. Secondary outcome was the low- and high-grade PCa rate detected by six-core TRUS-Bx, 12-core TRUS-Bx, and MRI ± TBx. Tertiary outcome was the reduction of biopsies and low-grade PCa detection by upfront risk stratification with the Rotterdam Prostate Cancer Risk Calculator 4. RESULTS AND LIMITATIONS Fifty-five percent of men were previously biopsied. The overall, low-grade, and high-grade PCa rates in biopsy naïve men were 48%, 27%, and 22%, respectively. In previously biopsied men these PCa rates were 25%, 20%, and 5%. Sextant TRUS-Bx, 12-core TRUS-Bx, and MRI ± TBx had a similar high-grade PCa rate (11%, 12%, and 11%) but a significantly different low-grade PCa rate (17%, 28%, and 7%). Rotterdam Prostate Cancer Risk Calculator 4-based stratification combined with 12-core TRUS-Bx ± MRI-TBx would have avoided 65% of biopsies and 68% of low-grade PCa while detecting an equal percentage of high-grade PCa (83%) compared with a TRUS-Bx all men approach (79%). CONCLUSIONS After four repeated screens and ≥1 previous biopsies in half of men, a significant proportion of men aged ≥70 yr still harbor high-grade PCa. Upfront risk stratification and the combination of MRI and TRUS-Bx would have avoided two-thirds of biopsies and low-grade PCa diagnoses in our cohort, while maintaining the high-grade PCa detection of a TRUS-Bx all men approach. Further studies are needed to verify these results. PATIENT SUMMARY Prostate cancer screening reduces mortality but is accompanied by unnecessary biopsies and overdiagnosis of nonaggressive tumors, especially in repeatedly screened elderly men. To tackle these drawbacks screening should consist of an upfront risk-assessment followed by magnetic resonance imaging and transrectal ultrasound-guided biopsy.
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Affiliation(s)
- Arnout R Alberts
- Department of Urology, Erasmus University Medical Center, Rotterdam, The Netherlands.
| | - Ivo G Schoots
- Department of Radiology and Nuclear Medicine, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Leonard P Bokhorst
- Department of Urology, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Frank-Jan H Drost
- Department of Urology, Erasmus University Medical Center, Rotterdam, The Netherlands; Department of Radiology and Nuclear Medicine, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Geert J van Leenders
- Department of Pathology, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Gabriel P Krestin
- Department of Radiology and Nuclear Medicine, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Roy S Dwarkasing
- Department of Radiology and Nuclear Medicine, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Jelle O Barentsz
- Department of Radiology, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Fritz H Schröder
- Department of Urology, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Chris H Bangma
- Department of Urology, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Monique J Roobol
- Department of Urology, Erasmus University Medical Center, Rotterdam, The Netherlands
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20
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Maruf M, Fascelli M, George AK, Siddiqui MM, Kongnyuy M, DiBianco JM, Muthigi A, Valayil S, Sidana A, Frye TP, Kilchevsky A, Choyke PL, Turkbey B, Wood BJ, Pinto PA. The prostate cancer prevention trial risk calculator 2.0 performs equally for standard biopsy and MRI/US fusion-guided biopsy. Prostate Cancer Prostatic Dis 2017; 20:179-185. [PMID: 28220802 DOI: 10.1038/pcan.2016.46] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2016] [Revised: 08/02/2016] [Accepted: 08/12/2016] [Indexed: 01/19/2023]
Abstract
BACKGROUND The Prostate Cancer Prevention Trial Risk Calculator 2.0 (PCPTRC) is a widely used risk-based calculator used to assess a man's risk of prostate cancer (PCa) before biopsy. This risk calculator was created from data of a patient cohort undergoing a 6-core sextant biopsy, and subsequently validated in men undergoing 12-core systematic biopsy (SBx). The accuracy of the PCPTRC has not been studied in patients undergoing magnetic resonance imaging/ultrasound (MRI/US) fusion-guided biopsy (FBx). We sought to assess the performance of the PCPTRC for straitifying PCa risk in a FBx cohort. METHODS A review of a prospective cohort undergoing MRI and FBx/SBx was conducted. Data from consecutive FBx/SBx were collected between August 2007 and February 2014, and PCPTRC scores using the PCPTRC2.0R-code were calculated. The risk of positive biopsy and high-grade cancer (Gleason ⩾7) on biopsy was calculated and compared with overall and high-grade cancer detection rates (CDRs). Receiver operating characteristic curves were generated and the areas under the curves (AUCs) were compared using DeLong's test. RESULTS Of 595 men included in the study, PCa was detected in 39% (232) by SBx compared with 48% (287) on combined FBx/SBx biopsy. The PCPTRC AUCs for the CDR were similar (P=0.70) for SBx (0.69) and combined biopsy (0.70). For high-grade disease, AUCs for SBx (0.71) and combined biopsy (0.70) were slightly higher, but were not statistically different (P=0.55). CONCLUSIONS In an MRI-screened population of men undergoing FBx, PCPTRC continues to represent a practical method of accurately stratifying PCa risk.
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Affiliation(s)
- M Maruf
- Center for Cancer Research, National Cancer Institute, National Institutes of Health, Urologic Oncology Branch, Bethesda, MD, USA
| | - M Fascelli
- Center for Cancer Research, National Cancer Institute, National Institutes of Health, Urologic Oncology Branch, Bethesda, MD, USA
| | - A K George
- Center for Cancer Research, National Cancer Institute, National Institutes of Health, Urologic Oncology Branch, Bethesda, MD, USA
| | - M M Siddiqui
- Division of Urology, Department of Surgery, University of Maryland School of Medicine, Baltimore, MD, USA
| | - M Kongnyuy
- Center for Cancer Research, National Cancer Institute, National Institutes of Health, Urologic Oncology Branch, Bethesda, MD, USA
| | - J M DiBianco
- Center for Cancer Research, National Cancer Institute, National Institutes of Health, Urologic Oncology Branch, Bethesda, MD, USA
| | - A Muthigi
- Center for Cancer Research, National Cancer Institute, National Institutes of Health, Urologic Oncology Branch, Bethesda, MD, USA
| | - S Valayil
- Center for Cancer Research, National Cancer Institute, National Institutes of Health, Urologic Oncology Branch, Bethesda, MD, USA
| | - A Sidana
- Center for Cancer Research, National Cancer Institute, National Institutes of Health, Urologic Oncology Branch, Bethesda, MD, USA
| | - T P Frye
- Center for Cancer Research, National Cancer Institute, National Institutes of Health, Urologic Oncology Branch, Bethesda, MD, USA
| | - A Kilchevsky
- Center for Cancer Research, National Cancer Institute, National Institutes of Health, Urologic Oncology Branch, Bethesda, MD, USA
| | - P L Choyke
- Molecular Imaging Program, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - B Turkbey
- Molecular Imaging Program, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - B J Wood
- Center for Interventional Oncology, National Cancer Institute & NIH Clinical Center, National Institutes of Health, Bethesda, MD, USA
| | - P A Pinto
- Center for Cancer Research, National Cancer Institute, National Institutes of Health, Urologic Oncology Branch, Bethesda, MD, USA
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21
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Pereira-Azevedo N, Osório L, Fraga A, Roobol MJ. Rotterdam Prostate Cancer Risk Calculator: Development and Usability Testing of the Mobile Phone App. JMIR Cancer 2017; 3:e1. [PMID: 28410180 PMCID: PMC5367845 DOI: 10.2196/cancer.6750] [Citation(s) in RCA: 31] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2016] [Revised: 11/22/2016] [Accepted: 12/19/2016] [Indexed: 12/13/2022] Open
Abstract
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.
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Affiliation(s)
- Nuno Pereira-Azevedo
- Department of Urology, Erasmus University Medical Center, Rotterdam, Netherlands.,Urology Department, Porto Hospital Centre, Porto, Portugal
| | - Luís Osório
- Urology Department, Porto Hospital Centre, Porto, Portugal
| | - Avelino Fraga
- Urology Department, Porto Hospital Centre, Porto, Portugal
| | - Monique J Roobol
- Department of Urology, Erasmus University Medical Center, Rotterdam, Netherlands
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22
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Park JY, Yoon S, Park MS, Choi H, Bae JH, Moon DG, Hong SK, Lee SE, Park C, Byun SS. Development and External Validation of the Korean Prostate Cancer Risk Calculator for High-Grade Prostate Cancer: Comparison with Two Western Risk Calculators in an Asian Cohort. PLoS One 2017; 12:e0168917. [PMID: 28046017 PMCID: PMC5207506 DOI: 10.1371/journal.pone.0168917] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2016] [Accepted: 12/08/2016] [Indexed: 11/19/2022] Open
Abstract
PURPOSE We developed the Korean Prostate Cancer Risk Calculator for High-Grade Prostate Cancer (KPCRC-HG) that predicts the probability of prostate cancer (PC) of Gleason score 7 or higher at the initial prostate biopsy in a Korean cohort (http://acl.snu.ac.kr/PCRC/RISC/). In addition, KPCRC-HG was validated and compared with internet-based Western risk calculators in a validation cohort. MATERIALS AND METHODS Using a logistic regression model, KPCRC-HG was developed based on the data from 602 previously unscreened Korean men who underwent initial prostate biopsies. Using 2,313 cases in a validation cohort, KPCRC-HG was compared with the European Randomized Study of Screening for PC Risk Calculator for high-grade cancer (ERSPCRC-HG) and the Prostate Cancer Prevention Trial Risk Calculator 2.0 for high-grade cancer (PCPTRC-HG). The predictive accuracy was assessed using the area under the receiver operating characteristic curve (AUC) and calibration plots. RESULTS PC was detected in 172 (28.6%) men, 120 (19.9%) of whom had PC of Gleason score 7 or higher. Independent predictors included prostate-specific antigen levels, digital rectal examination findings, transrectal ultrasound findings, and prostate volume. The AUC of the KPCRC-HG (0.84) was higher than that of the PCPTRC-HG (0.79, p<0.001) but not different from that of the ERSPCRC-HG (0.83) on external validation. Calibration plots also revealed better performance of KPCRC-HG and ERSPCRC-HG than that of PCPTRC-HG on external validation. At a cut-off of 5% for KPCRC-HG, 253 of the 2,313 men (11%) would not have been biopsied, and 14 of the 614 PC cases with Gleason score 7 or higher (2%) would not have been diagnosed. CONCLUSIONS KPCRC-HG is the first web-based high-grade prostate cancer prediction model in Korea. It had higher predictive accuracy than PCPTRC-HG in a Korean population and showed similar performance with ERSPCRC-HG in a Korean population. This prediction model could help avoid unnecessary biopsy and reduce overdiagnosis and overtreatment in clinical settings.
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Affiliation(s)
- Jae Young Park
- Department of Urology, Korea University College of Medicine, Seoul, Republic of Korea
- * E-mail: (SSB); (JYP)
| | - Sungroh Yoon
- Department of Electrical and Computer Engineering, Seoul National University, Seoul, Republic of Korea
| | - Man Sik Park
- Department of Statistics, College of Natural Sciences, Sungshin Women's University, Seoul, Republic of Korea
| | - Hoon Choi
- Department of Urology, Korea University Ansan Hospital, Ansan, Republic of Korea
| | - Jae Hyun Bae
- Department of Urology, Korea University College of Medicine, Seoul, Republic of Korea
| | - Du Geon Moon
- Department of Urology, Korea University College of Medicine, Seoul, Republic of Korea
| | - Sung Kyu Hong
- Department of Urology, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Sang Eun Lee
- Department of Urology, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Chanwang Park
- Anesthesia Consultants of Indianapolis, Indiana, United States of America
| | - Seok-Soo Byun
- Department of Urology, Seoul National University College of Medicine, Seoul, Republic of Korea
- * E-mail: (SSB); (JYP)
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23
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Chiu PK, Roobol MJ, Nieboer D, Teoh JY, Yuen SK, Hou SM, Yiu MK, Ng CF. Adaptation and external validation of the European randomised study of screening for prostate cancer risk calculator for the Chinese population. Prostate Cancer Prostatic Dis 2016; 20:99-104. [PMID: 27897172 DOI: 10.1038/pcan.2016.57] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2016] [Revised: 10/02/2016] [Accepted: 10/14/2016] [Indexed: 11/09/2022]
Abstract
BACKGROUND To adapt the well-performing European Randomized Study of Screening for Prostate Cancer (ERSPC) risk calculator to the Chinese setting and perform an external validation. METHODS The original ERSPC risk calculator 3 (RC3) for prostate cancer (PCa) and high-grade PCa (HGPCa) was applied to a development cohort of 3006 previously unscreened Hong Kong Chinese men with initial transrectal biopsies performed from 1997 to 2015, age 50-80 years, PSA 0.4-50 ng ml-1 and prostate volume 10-150 ml. A simple adaptation to RC3 was performed and externally validated in a cohort of 2214 Chinese men from another Hong Kong hospital. The performance of the models were presented in calibration plots, area under curve (AUC) of receiver operating characteristics (ROCs) and decision curve analyses. RESULTS PCa and HGPCa was diagnosed in 16.7% (503/3006) and 7.8% (234/3006) men in the development cohort, and 20.2% (447/2204) and 9.7% (214/2204) men in the validation cohort, respectively. The AUCs using the original RC3 model in the development cohort were 0.75 and 0.84 for PCa and HGPCa, respectively, but the calibration plots showed considerable overestimation. In the external validation of the recalibrated RC3 model, excellent calibration was observed, and discrimination was good with AUCs of 0.76 and 0.85 for PCa and HGPCa, respectively. Decision curve analyses in the validation cohort showed net clinical benefit of the recalibrated RC3 model over PSA. CONCLUSIONS A recalibrated ERSPC risk calculator for the Chinese population was developed, and it showed excellent discrimination, calibration and net clinical benefit in an external validation cohort.
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Affiliation(s)
- P K Chiu
- Division of Urology, Department of Surgery, Prince of Wales Hospital, The Chinese University of Hong Kong, Hong Kong, Hong Kong
| | - M J Roobol
- Department of Urology, Erasmus University Medical Centre, Rotterdam, The Netherlands
| | - D Nieboer
- Department of Public Health, Erasmus University Medical Centre, Rotterdam, The Netherlands
| | - J Y Teoh
- Division of Urology, Department of Surgery, Prince of Wales Hospital, The Chinese University of Hong Kong, Hong Kong, Hong Kong
| | - S K Yuen
- Division of Urology, Department of Surgery, Queen Mary Hospital, University of Hong Kong, Hong Kong, Hong Kong
| | - S M Hou
- Division of Urology, Department of Surgery, Prince of Wales Hospital, The Chinese University of Hong Kong, Hong Kong, Hong Kong
| | - M K Yiu
- Division of Urology, Department of Surgery, Queen Mary Hospital, University of Hong Kong, Hong Kong, Hong Kong
| | - C F Ng
- Division of Urology, Department of Surgery, Prince of Wales Hospital, The Chinese University of Hong Kong, Hong Kong, Hong Kong.,Department of Surgery, SH Ho Urology Centre, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, Hong Kong
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Ross T, Ahmed K, Raison N, Challacombe B, Dasgupta P. Clarifying the PSA grey zone: The management of patients with a borderline PSA. Int J Clin Pract 2016; 70:950-959. [PMID: 27672001 DOI: 10.1111/ijcp.12883] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/25/2016] [Accepted: 08/31/2016] [Indexed: 01/17/2023] Open
Abstract
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.
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Affiliation(s)
- Talisa Ross
- Guy's Hospital, King's College London, London, UK
| | - Kamran Ahmed
- Guy's Hospital, King's College London, London, UK
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25
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Gayet M, Mannaerts CK, Nieboer D, Beerlage HP, Wijkstra H, Mulders PFA, Roobol MJ. Prediction of Prostate Cancer: External Validation of the ERSPC Risk Calculator in a Contemporary Dutch Clinical Cohort. Eur Urol Focus 2016; 4:228-234. [PMID: 28753781 DOI: 10.1016/j.euf.2016.07.007] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2016] [Accepted: 07/21/2016] [Indexed: 10/21/2022]
Abstract
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.
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Affiliation(s)
- Maudy Gayet
- Department of Urology, Jeroen Bosch Hospital, 's-Hertogenbosch, The Netherlands; Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands.
| | | | - Daan Nieboer
- Department of Urology, Erasmus Medical Centre, Rotterdam, The Netherlands
| | - Harrie P Beerlage
- Department of Urology, Jeroen Bosch Hospital, 's-Hertogenbosch, The Netherlands; Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands
| | - Hessel Wijkstra
- Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands; Department of Urology, AMC University Hospital, Amsterdam, The Netherlands
| | - Peter F A Mulders
- Department of Urology, Radboudumc University Hospital, Nijmegen, The Netherlands
| | - Monique J Roobol
- Department of Urology, Erasmus Medical Centre, Rotterdam, The Netherlands
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26
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Watson MJ, George AK, Maruf M, Frye TP, Muthigi A, Kongnyuy M, Valayil SG, Pinto PA. Risk stratification of prostate cancer: integrating multiparametric MRI, nomograms and biomarkers. Future Oncol 2016; 12:2417-2430. [PMID: 27400645 DOI: 10.2217/fon-2016-0178] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Abstract
Accurate risk stratification of prostate cancer is achieved with a number of existing tools to ensure the identification of at-risk patients, characterization of disease aggressiveness, prediction of cancer burden and extrapolation of treatment outcomes for appropriate management of the disease. Statistical tables and nomograms using classic clinicopathological variables have long been the standard of care. However, the introduction of multiparametric MRI, along with fusion-guided targeted prostate biopsy and novel biomarkers, are being assimilated into clinical practice. The majority of studies to date present the outcomes of each in isolation. The current review offers a critical and objective assessment regarding the integration of multiparametric MRI and fusion-guided prostate biopsy with novel biomarkers and predictive nomograms in contemporary clinical practice.
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Affiliation(s)
- Matthew J Watson
- Urological Oncology Branch, National Cancer Institute, NIH, Bethesda, MD, USA
| | - Arvin K George
- Urological Oncology Branch, National Cancer Institute, NIH, Bethesda, MD, USA
| | - Mahir Maruf
- Urological Oncology Branch, National Cancer Institute, NIH, Bethesda, MD, USA
| | - Thomas P Frye
- Urological Oncology Branch, National Cancer Institute, NIH, Bethesda, MD, USA
| | - Akhil Muthigi
- Urological Oncology Branch, National Cancer Institute, NIH, Bethesda, MD, USA
| | - Michael Kongnyuy
- Urological Oncology Branch, National Cancer Institute, NIH, Bethesda, MD, USA
| | - Subin G Valayil
- Urological Oncology Branch, National Cancer Institute, NIH, Bethesda, MD, USA
| | - Peter A Pinto
- Urological Oncology Branch, National Cancer Institute, NIH, Bethesda, MD, USA
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27
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Poyet C, Wettstein MS, Lundon DJ, Bhindi B, Kulkarni GS, Saba K, Sulser T, Vickers AJ, Hermanns T. External Evaluation of a Novel Prostate Cancer Risk Calculator (ProstateCheck) Based on Data from the Swiss Arm of the ERSPC. J Urol 2016; 196:1402-1407. [PMID: 27188476 DOI: 10.1016/j.juro.2016.05.081] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/12/2016] [Indexed: 10/21/2022]
Abstract
PURPOSE We externally validated a novel prostate cancer risk calculator based on data from the Swiss arm of the ERSPC and assessed whether the risk calculator (ProstateCheck) is superior to the PCPT-RC and SWOP-RC in an independent Swiss cohort. MATERIALS AND METHODS Data from all men who underwent prostate biopsy at an academic tertiary care center between 2004 and 2012 were retrospectively analyzed. The probability of having any prostate cancer or high grade prostate cancer (Gleason score 7 or greater) on prostate biopsy was calculated using the ProstateCheck. Risk calculator performance was assessed using calibration and discrimination, and additionally compared with the PCPT-RC and SWOP-RC by decision curve analyses. RESULTS Of 1,615 men 401 (25%) were diagnosed with any prostate cancer and 196 (12%) with high grade prostate cancer. Our analyses of the ProstateCheck-RC revealed good calibration in the low risk range (0 to 0.4) and moderate overestimation in the higher risk range (0.4 to 1) for any and high grade prostate cancer. The AUC for the discrimination of any prostate cancer and high grade prostate cancer was 0.69 and 0.72, respectively, which was slightly but significantly higher compared to the PCPT-RC (0.66 and 0.69, respectively) and SWOP-RC (0.64 and 0.70, respectively). Decision analysis, taking into account the harms of transrectal ultrasound measurement of prostate volume, showed little benefit for ProstateCheck-RC, with properties inferior to those of the PCPT-RC and SWOP-RC. CONCLUSIONS Our independent external evaluation revealed moderate performance of the ProstateCheck-RC. Its clinical benefit is limited, and inferior to that of the PCPT-RC and SWOP-RC.
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Affiliation(s)
- Cédric Poyet
- Department of Urology, University Hospital Zürich, University of Zürich, Zürich, Switzerland
| | - Marian S Wettstein
- Department of Urology, University Hospital Zürich, University of Zürich, Zürich, Switzerland
| | - Dara J Lundon
- Department of Urology, Mater Misericordiae University Hospital, Dublin, Ireland
| | - Bimal Bhindi
- Department of Surgery, Division of Urology, University Health Network, University of Toronto, Toronto, Ontario, Canada
| | - Girish S Kulkarni
- Department of Surgery, Division of Urology, University Health Network, University of Toronto, Toronto, Ontario, Canada
| | - Karim Saba
- Department of Urology, University Hospital Zürich, University of Zürich, Zürich, Switzerland
| | - Tullio Sulser
- Department of Urology, University Hospital Zürich, University of Zürich, Zürich, Switzerland
| | - A J Vickers
- Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Thomas Hermanns
- Department of Urology, University Hospital Zürich, University of Zürich, Zürich, Switzerland.
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28
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Bokhorst LP, Steyerberg EW, Roobol MJ. Decision Support for Low-Risk Prostate Cancer. Prostate Cancer 2016. [DOI: 10.1016/b978-0-12-800077-9.00024-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
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29
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Alberts AR, Schoots IG, Bokhorst LP, van Leenders GJ, Bangma CH, Roobol MJ. Risk-based Patient Selection for Magnetic Resonance Imaging-targeted Prostate Biopsy after Negative Transrectal Ultrasound-guided Random Biopsy Avoids Unnecessary Magnetic Resonance Imaging Scans. Eur Urol 2015; 69:1129-34. [PMID: 26651990 DOI: 10.1016/j.eururo.2015.11.018] [Citation(s) in RCA: 48] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2015] [Accepted: 11/12/2015] [Indexed: 11/15/2022]
Abstract
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.
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Affiliation(s)
- Arnout R Alberts
- Department of Urology, Erasmus Medical Center, Rotterdam, The Netherlands.
| | - Ivo G Schoots
- Department of Radiology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Leonard P Bokhorst
- Department of Urology, Erasmus Medical Center, Rotterdam, The Netherlands
| | | | - Chris H Bangma
- Department of Urology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Monique J Roobol
- Department of Urology, Erasmus Medical Center, Rotterdam, The Netherlands
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30
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Poyet C, Nieboer D, Bhindi B, Kulkarni GS, Wiederkehr C, Wettstein MS, Largo R, Wild P, Sulser T, Hermanns T. Prostate cancer risk prediction using the novel versions of the European Randomised Study for Screening of Prostate Cancer (ERSPC) and Prostate Cancer Prevention Trial (PCPT) risk calculators: independent validation and comparison in a contemporary Europe. BJU Int 2015; 117:401-8. [DOI: 10.1111/bju.13314] [Citation(s) in RCA: 67] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023]
Affiliation(s)
- Cédric Poyet
- Department of Urology; University Hospital Zürich; University of Zürich; Zürich Switzerland
| | - Daan Nieboer
- Erasmus MC; University Medical Center Rotterdam; Rotterdam The Netherlands
| | - Bimal Bhindi
- Division of Urology; Department of Surgery; University Health Network; University of Toronto; Toronto ON Canada
| | - Girish S. Kulkarni
- Division of Urology; Department of Surgery; University Health Network; University of Toronto; Toronto ON Canada
| | - Caroline Wiederkehr
- Department of Urology; University Hospital Zürich; University of Zürich; Zürich Switzerland
| | - Marian S. Wettstein
- Department of Urology; University Hospital Zürich; University of Zürich; Zürich Switzerland
| | - Remo Largo
- Department of Urology; University Hospital Zürich; University of Zürich; Zürich Switzerland
| | - Peter Wild
- Institute of Surgical Pathology; University Hospital Zürich; University of Zürich; Zürich Switzerland
| | - Tullio Sulser
- Department of Urology; University Hospital Zürich; University of Zürich; Zürich Switzerland
| | - Thomas Hermanns
- Department of Urology; University Hospital Zürich; University of Zürich; Zürich Switzerland
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31
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Roumiguié M, Beauval JB, Bordier B, Filleron T, Rozet F, Ruffion A, Mottet N, Cussenot O, Malavaud B. What risk of prostate cancer led urologist to recommend prostate biopsies? Prog Urol 2015; 25:1125-31. [PMID: 26431746 DOI: 10.1016/j.purol.2015.08.007] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2015] [Revised: 08/03/2015] [Accepted: 08/04/2015] [Indexed: 10/23/2022]
Abstract
OBJECTIVE The aim of this study was to estimate the risk of prostate cancer that led urologists to perform prostate biopsies. PATIENTS AND METHODS Eight hundred and eight patients had prostate biopsies in 5 tertiary centres in 2010. Following data were collected: age, PSA, DRE, prostate volume, negative prior prostate biopsy and estimated life expectancy (> or <10 years). The risk of prostate cancer was calculated by validated nomogram of PCPT-CRC and SWOP-PRI and correlated with pathological biopsy results. RESULTS In final analysis, 625 patients were included, 568 (90.9%) had a life expectancy greater than 10 years. Prostate cancer was found in 291 (46.6%) cases. These patients were older (66.7 ± 6.8 vs 64.3 ± 5.6 years, P < 0.001), had higher PSA values (10 ± 7.9 vs 7.7 ± 4.3 ng/mL, P < 0.0001) and the prostate volume decreased (43.8 ± 19.8 vs 51.3 ± 20.7 mL, P < 0.0001) compared with healthy subjects. Digital Rectal Examination was more frequently suspicious in the group of patients with prostate cancer (43.6% vs 18.9%, P < 0.0001). Risk of prostate cancer estimated was 50.6 ± 14% for PCPT-CRC without ATCD, 56.2 ± 12.8% with PCPT-CRC ATCD and 31.2 ± 17.3% for SWOP-PRI. The likelihood of high-risk prostate cancer was 22.4 ± 16.9% with the PCPT-CRC, and 14.8 ± 18.2% with SWOP-PRI. CONCLUSION This study showed that urologists performed prostate biopsies when the risk of cancer was high.
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Affiliation(s)
- M Roumiguié
- Département d'urologie, CHU Rangueil, 1, avenue Jean-Poulhès, TSA 50032, 31059 Toulouse cedex France.
| | - J-B Beauval
- Département d'urologie, CHU Rangueil, 1, avenue Jean-Poulhès, TSA 50032, 31059 Toulouse cedex France
| | - B Bordier
- Clinique Pasteur, service d'urologie, 5, avenue de Lombez, 31300 Toulouse, France
| | - T Filleron
- Département de biostatistiques, IUCT oncopôle, Toulouse, France
| | - F Rozet
- Institut Montsouris, département d'urologie, 42, boulevard Jourdan, 75014 Paris cedex, France
| | - A Ruffion
- Département d'urologie, centre hospitalier Lyon Sud, Pierre-Bénite, France
| | - N Mottet
- Département d'urologie, hôpital Nord, 42055 Saint-Étienne cedex 2, France
| | - O Cussenot
- Département d'urologie, hôpital Tenon, CHU, AP-HP, 4, rue de la Chine, 75970 Paris cedex 20, France
| | - B Malavaud
- Département d'urologie, CHU Rangueil, 1, avenue Jean-Poulhès, TSA 50032, 31059 Toulouse cedex France; Département de biostatistiques, IUCT oncopôle, Toulouse, France
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Muir KR, Lophatananon A, Gnanapragasam V, Rees J. The Future of Prostate Cancer Risk Prediction. CURR EPIDEMIOL REP 2015. [DOI: 10.1007/s40471-015-0056-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
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Sorokin I, Mian BM. Risk calculators and updated tools to select and plan a repeat biopsy for prostate cancer detection. Asian J Androl 2015; 17:864-9. [PMID: 26112489 PMCID: PMC4814963 DOI: 10.4103/1008-682x.156859] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022] Open
Abstract
Millions of men each year are faced with a clinical suspicion of prostate cancer (PCa) but the prostate biopsy fails to detect the disease. For the urologists, how to select the appropriate candidate for repeat biopsy is a significant clinical dilemma. Traditional risk-stratification tools in this setting such as prostate-specific antigen (PSA) related markers and histopathology findings have met with limited correlation with cancer diagnosis or with significant disease. Thus, an individualized approach using predictive models such as an online risk calculator (RC) or updated biomarkers is more suitable in counseling men about their risk of harboring clinically significant prostate cancer. This review will focus on the available risk-stratification tools in the population of men with prior negative biopsies and persistent suspicion of PCa. The underlying methodology and platforms of the available tools are reviewed to better understand the development and validation of these models. The index patient is then assessed with different RCs to determine the range of heterogeneity among various RCs. This should allow the urologists to better incorporate these various risk-stratification tools into their clinical practice and improve patient counseling.
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Affiliation(s)
| | - Badar M Mian
- Department of Urology, Albany Medical College, Albany, NY, USA
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Strobl AN, Vickers AJ, Van Calster B, Steyerberg E, Leach RJ, Thompson IM, Ankerst DP. Improving patient prostate cancer risk assessment: Moving from static, globally-applied to dynamic, practice-specific risk calculators. J Biomed Inform 2015; 56:87-93. [PMID: 25989018 DOI: 10.1016/j.jbi.2015.05.001] [Citation(s) in RCA: 34] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2014] [Revised: 03/14/2015] [Accepted: 05/04/2015] [Indexed: 10/23/2022]
Abstract
Clinical risk calculators are now widely available but have generally been implemented in a static and one-size-fits-all fashion. The objective of this study was to challenge these notions and show via a case study concerning risk-based screening for prostate cancer how calculators can be dynamically and locally tailored to improve on-site patient accuracy. Yearly data from five international prostate biopsy cohorts (3 in the US, 1 in Austria, 1 in England) were used to compare 6 methods for annual risk prediction: static use of the online US-developed Prostate Cancer Prevention Trial Risk Calculator (PCPTRC); recalibration of the PCPTRC; revision of the PCPTRC; building a new model each year using logistic regression, Bayesian prior-to-posterior updating, or random forests. All methods performed similarly with respect to discrimination, except for random forests, which were worse. All methods except for random forests greatly improved calibration over the static PCPTRC in all cohorts except for Austria, where the PCPTRC had the best calibration followed closely by recalibration. The case study shows that a simple annual recalibration of a general online risk tool for prostate cancer can improve its accuracy with respect to the local patient practice at hand.
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Affiliation(s)
- Andreas N Strobl
- TU München, Department of Mathematics, Munich, Germany; HelmholtzZentrum München, Institute of Computational Biology, Munich, Germany.
| | - Andrew J Vickers
- Memorial Sloan-Kettering Cancer Center, Department of Epidemiology and Biostatistics, New York City, NY, USA
| | - Ben Van Calster
- KU Leuven, Department of Development and Regeneration, Leuven, Belgium
| | - Ewout Steyerberg
- Erasmus MC, Department of Public Health, Rotterdam, The Netherlands
| | - Robin J Leach
- University of Texas Health Science Center at San Antonio, Department of Cellular and Structural Biology, San Antonio, TX, USA; University of Texas Health Science Center at San Antonio, Department of Urology, San Antonio, TX, USA
| | - Ian M Thompson
- University of Texas Health Science Center at San Antonio, Department of Urology, San Antonio, TX, USA
| | - Donna P Ankerst
- TU München, Department of Mathematics, Munich, Germany; HelmholtzZentrum München, Institute of Computational Biology, Munich, Germany; University of Texas Health Science Center at San Antonio, Department of Urology, San Antonio, TX, USA; University of Texas Health Science Center at San Antonio, Department of Epidemiology and Biostatistics, San Antonio, TX, USA
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Louie KS, Seigneurin A, Cathcart P, Sasieni P. Do prostate cancer risk models improve the predictive accuracy of PSA screening? A meta-analysis. Ann Oncol 2015; 26:848-864. [PMID: 25403590 DOI: 10.1093/annonc/mdu525] [Citation(s) in RCA: 136] [Impact Index Per Article: 13.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2014] [Accepted: 11/04/2014] [Indexed: 02/11/2024] Open
Abstract
BACKGROUND Despite the extensive development of risk prediction models to aid patient decision-making on prostate screening, it is unknown whether these models could improve predictive accuracy of PSA testing to detect prostate cancer (PCa). The objective of this study was to perform a systematic review to identify PCa risk models and to assess the model's performance to predict PCa by conducting a meta-analysis. DESIGN A systematic literature search of Medline was conducted to identify PCa predictive risk models that used at least two variables, of which one of the variables was prostate-specific antigen (PSA) level. Model performance (discrimination and calibration) was assessed. Prediction models validated in ≥5 study populations and reported area under the curve (AUC) for prediction of any or clinically significant PCa were eligible for meta-analysis. Summary AUC and 95% CIs were calculated using a random-effects model. RESULTS The systematic review identified 127 unique PCa prediction models; however, only six models met study criteria for meta-analysis for predicting any PCa: Prostataclass, Finne, Karakiewcz, Prostate Cancer Prevention Trial (PCPT), Chun, and the European Randomized Study of Screening for Prostate Cancer Risk Calculator 3 (ERSPC RC3). Summary AUC estimates show that PCPT does not differ from PSA testing (0.66) despite performing better in studies validating both PSA and PCPT. Predictive accuracy to discriminate PCa increases with Finne (AUC = 0.74), Karakiewcz (AUC = 0.74), Chun (AUC = 0.76) and ERSPC RC3 and Prostataclass have the highest discriminative value (AUC = 0.79), which is equivalent to doubling the sensitivity of PSA testing (44% versus 21%) without loss of specificity. The discriminative accuracy of PCPT to detect clinically significant PCa was AUC = 0.71. Calibration measures of the models were poorly reported. CONCLUSIONS Risk prediction models improve the predictive accuracy of PSA testing to detect PCa. Future developments in the use of PCa risk models should evaluate its clinical effectiveness in practice.
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Affiliation(s)
- K S Louie
- Centre for Cancer Prevention, Wolfson Institute of Preventive Medicine, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK.
| | - A Seigneurin
- Centre for Cancer Prevention, Wolfson Institute of Preventive Medicine, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK; Joseph Fourier University-Grenoble 1, CNRS, TIMC-IMAG UMR 5525, Grenoble; Medical Evaluation Unit, Grenoble University Hospital, Grenoble, France
| | - P Cathcart
- Department of Urology, University College Hospital London and St Bartholomew's Hospital London and Centre for Experimental Cancer Medicine, Bart's Cancer Institute, London; The Clinical Effectiveness Unit, The Royal College of Surgeons of England, London, UK
| | - P Sasieni
- Centre for Cancer Prevention, Wolfson Institute of Preventive Medicine, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK
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Predicting prostate cancer: analysing the clinical efficacy of prostate cancer risk calculators in a referral population. Ir J Med Sci 2015; 184:701-6. [DOI: 10.1007/s11845-015-1291-8] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2015] [Accepted: 03/29/2015] [Indexed: 10/23/2022]
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Grill S, Fallah M, Leach RJ, Thompson IM, Hemminki K, Ankerst DP. A simple-to-use method incorporating genomic markers into prostate cancer risk prediction tools facilitated future validation. J Clin Epidemiol 2015; 68:563-73. [PMID: 25684153 DOI: 10.1016/j.jclinepi.2015.01.006] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2014] [Revised: 01/07/2015] [Accepted: 01/09/2015] [Indexed: 01/23/2023]
Abstract
OBJECTIVES To incorporate single-nucleotide polymorphisms (SNPs) into the Prostate Cancer Prevention Trial Risk Calculator (PCPTRC). STUDY DESIGN AND SETTING A multivariate random-effects meta-analysis of likelihood ratios (LRs) for 30 validated SNPs was performed, allowing the incorporation of linkage disequilibrium. LRs for an SNP were defined as the ratio of the probability of observing the SNP in prostate cancer cases relative to controls and estimated by published allele or genotype frequencies. LRs were multiplied by the PCPTRC prior odds of prostate cancer to provide updated posterior odds. RESULTS In the meta-analysis (prostate cancer cases/controls = 386,538/985,968), all but two of the SNPs had at least one statistically significant allele LR (P < 0.05). The two SNPs with the largest LRs were rs16901979 [LR = 1.575 for one risk allele, 2.552 for two risk alleles (homozygous)] and rs1447295 (LR = 1.307 and 1.887, respectively). CONCLUSION The substantial investment in genome-wide association studies to discover SNPs associated with prostate cancer risk and the ability to integrate these findings into the PCPTRC allows investigators to validate these observations, to determine the clinical impact, and to ultimately improve clinical practice in the early detection of the most common cancer in men.
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Affiliation(s)
- Sonja Grill
- Department of Life Sciences of the Technical University Munich, Liesel-Beckmann-Str. 2, 85354 Freising, Germany.
| | - Mahdi Fallah
- Division of Molecular Genetic Epidemiology, German Cancer Research Centre, Im Neuenheimer Feld 580, Im Technologiepark, 69120 Heidelberg, Germany
| | - Robin J Leach
- Department of Urology of the University of Texas Health Science Center at San Antonio, 7703 Floyd Curl Drive, San Antonio, TX, 78229, USA; Department of Cellular and Structural Biology of the University of Texas Health Science Center at San Antonio, 7703 Floyd Curl Drive, San Antonio, TX 78229, USA
| | - Ian M Thompson
- Department of Urology of the University of Texas Health Science Center at San Antonio, 7703 Floyd Curl Drive, San Antonio, TX, 78229, USA
| | - Kari Hemminki
- Division of Molecular Genetic Epidemiology, German Cancer Research Centre, Im Neuenheimer Feld 580, Im Technologiepark, 69120 Heidelberg, Germany; Center for Primary Health Care Research, Lund University, Box 117, 221 00 LUND, Sweden
| | - Donna P Ankerst
- Department of Life Sciences of the Technical University Munich, Liesel-Beckmann-Str. 2, 85354 Freising, Germany; Department of Urology of the University of Texas Health Science Center at San Antonio, 7703 Floyd Curl Drive, San Antonio, TX, 78229, USA; Department of Mathematics of the Technical University Munich, Boltzmannstr. 3, 85748 Garching b. München, Germany; Department of Epidemiology and Biostatistics of the University of Texas Health Science Center at San Antonio, 7703 Floyd Curl Drive, San Antonio, TX 78229, USA
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Grill S, Fallah M, Leach RJ, Thompson IM, Freedland S, Hemminki K, Ankerst DP. Incorporation of detailed family history from the Swedish Family Cancer Database into the PCPT risk calculator. J Urol 2014; 193:460-5. [PMID: 25242395 DOI: 10.1016/j.juro.2014.09.018] [Citation(s) in RCA: 21] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/08/2014] [Indexed: 11/17/2022]
Abstract
PURPOSE A detailed family history provides an inexpensive alternative to genetic profiling for individual risk assessment. We updated the PCPT Risk Calculator to include detailed family histories. MATERIALS AND METHODS The study included 55,168 prostate cancer cases and 638,218 controls from the Swedish Family Cancer Database who were 55 years old or older in 1999 and had at least 1 male first-degree relative 40 years old or older and 1 female first-degree relative 30 years old or older. Likelihood ratios, calculated as the ratio of risk of observing a specific family history pattern in a prostate cancer case compared to a control, were used to update the PCPT Risk Calculator. RESULTS Having at least 1 relative with prostate cancer increased the risk of prostate cancer. The likelihood ratio was 1.63 for 1 first-degree relative 60 years old or older at diagnosis (10.1% of cancer cases vs 6.2% of controls), 2.47 if the relative was younger than 60 years (1.5% vs 0.6%), 3.46 for 2 or more relatives 60 years old or older (1.2% vs 0.3%) and 5.68 for 2 or more relatives younger than 60 years (0.05% vs 0.009%). Among men with no diagnosed first-degree relatives the likelihood ratio was 1.09 for 1 or more second-degree relatives diagnosed with prostate cancer (12.7% vs 11.7%). Additional first-degree relatives with breast cancer, or first-degree or second-degree relatives with prostate cancer compounded these risks. CONCLUSIONS A detailed family history is an independent predictor of prostate cancer compared to commonly used risk factors. It should be incorporated into decision making for biopsy. Compared with other costly biomarkers it is inexpensive and universally available.
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Affiliation(s)
- Sonja Grill
- Departments of Life Sciences and Mathematics, Technical University Munich, Munich, Germany
| | - Mahdi Fallah
- Section of Surgery, Durham Veterans Affairs Hospital and Department of Surgery (Urology) and Pathology, Duke University, Durham, North Carolina
| | - Robin J Leach
- Department of Urology, University of Texas Health Science Center at San Antonio, San Antonio, Texas; Department of Cellular and Structural Biology, University of Texas Health Science Center at San Antonio, San Antonio, Texas
| | - Ian M Thompson
- Department of Urology, University of Texas Health Science Center at San Antonio, San Antonio, Texas
| | - Stephen Freedland
- Section of Surgery, Durham Veterans Affairs Hospital and Department of Surgery (Urology) and Pathology, Duke University, Durham, North Carolina
| | - Kari Hemminki
- Division of Molecular Genetic Epidemiology, German Cancer Research Centre, Heidelberg, Germany; Center for Primary Health Care Research, Lund University, Malmö, Sweden
| | - Donna P Ankerst
- Departments of Life Sciences and Mathematics, Technical University Munich, Munich, Germany; Department of Urology, University of Texas Health Science Center at San Antonio, San Antonio, Texas; Department of Epidemiology and Biostatistics, University of Texas Health Science Center at San Antonio, San Antonio, Texas.
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Prostate cancer risk assessment tools in an unscreened population. World J Urol 2014; 33:827-32. [PMID: 25091862 DOI: 10.1007/s00345-014-1365-7] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2014] [Accepted: 07/08/2014] [Indexed: 10/24/2022] Open
Abstract
OBJECTIVE To compare the prostate cancer prevention trial risk calculator (PCPT-RC) and European randomized study of screening for prostate cancer risk calculator (ERSPC-RC) in a unique unscreened population from the West of Ireland. PATIENTS AND METHODS Data was prospectively recorded for all 556 consecutive men who underwent prostate biopsy at our institution as part of the Rapid Access Prostate Assessment Clinic program in Ireland. The estimated probabilities of detecting prostate cancer and high-grade disease were calculated using the PCPT and ERSPC risk calculators. For each calculator the discriminative ability, calibration and clinical utility was assessed. RESULTS Prostate cancer was detected in 49% and high-grade prostate cancer in 34% of men. Receiver operating characteristic curve analysis demonstrated that the PCPT-RCs outperformed the ERSPC-RCs for the prediction of prostate cancer areas underneath the ROC curve (AUC 0.628 vs. 0.588, p = 0.0034) and for the prediction of high-grade prostate cancer (AUC 0.792 vs. 0.690, p = 0.0029). Both risk calculators generally over-predicted the risk of prostate cancer and high-grade disease across a wide range of predicted probabilities. Decision curve analysis suggested greater net benefit using the PCPT-RCs in this population. CONCLUSIONS Multivariable nomograms can further aid patient counselling for early prostate cancer detection. In unscreened men from Western Ireland, the PCPT-RCs provided better discrimination for overall prostate cancer and high-grade disease compared to the ERSPC-RC. However, both tools overpredicted the risk of cancer detection on biopsy, and it is possible that a different set of predictive variables may be more useful in this population.
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Bhindi B, Locke J, Alibhai SMH, Kulkarni GS, Margel DS, Hamilton RJ, Finelli A, Trachtenberg J, Zlotta AR, Toi A, Hersey KM, Evans A, van der Kwast TH, Fleshner NE. Dissecting the association between metabolic syndrome and prostate cancer risk: analysis of a large clinical cohort. Eur Urol 2014; 67:64-70. [PMID: 24568896 DOI: 10.1016/j.eururo.2014.01.040] [Citation(s) in RCA: 83] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2013] [Accepted: 01/31/2014] [Indexed: 01/09/2023]
Abstract
BACKGROUND A biologic rationale exists for the association between metabolic syndrome (MetS) and prostate cancer (PCa). However, epidemiologic studies have been conflicting. OBJECTIVE To evaluate the association between MetS and the odds of PCa diagnosis in men referred for biopsy. DESIGN, SETTING, AND PARTICIPANTS Patients without prior PCa diagnosis undergoing prostate biopsy were identified from a large prostate biopsy cohort (in Toronto, Canada). The definition of MetS was based on the most recent interim joint consensus definition, requiring any three of five components (obesity, elevated blood pressure, diabetes or impaired fasting glucose, low high-density lipoprotein-cholesterol, and hypertriglyceridemia). Both the individual components of MetS and the cumulative number of MetS components were evaluated. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS The outcomes were PCa detection overall, clinically significant PCa (CSPC; defined as any Gleason pattern ≥ 4, >50% involvement of a single biopsy core, or more than one of three total number of cores involved), and intermediate- or high-grade PCa (I-HGPC; Gleason 7-10). Tests for trend and multivariable logistic regression analyses were performed. RESULTS AND LIMITATIONS Of 2235 patients, 494 (22.1%) had MetS. No individual MetS component was independently associated with PCa. However, increasing number of MetS components was associated with higher PCa grade (p<0.001), as well as progressively higher odds of PCa outcomes (three or more; ie, MetS) compared with no MetS components: Odds ratios were 1.54 for PCa overall (95% confidence interval [CI], 1.17-2.04; p=0.002), 1.56 for CSPC (95% CI, 1.17-2.08; p=0.002), and 1.56 for I-HGPC (95% CI, 1.16-2.10; p=0.003) in multivariable analyses. The main limitation is the retrospective design. CONCLUSIONS Although the individual MetS components are not independently associated with PCa outcomes, MetS is significantly associated with higher odds of PCa diagnosis, CSPC, and I-HGPC. There is a biologic gradient between the number of MetS components and the risk of PCa, as well as cancer grade. PATIENT SUMMARY Metabolic syndrome is a collection of metabolic abnormalities that increases one's risk for heart disease. Our study shows that an increasing degree of metabolic abnormality is also associated with an increased risk of diagnosis of overall and aggressive prostate cancer.
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Affiliation(s)
- Bimal Bhindi
- Division of Urology, Department of Surgery, University Health Network, University of Toronto, Toronto, Ontario, Canada.
| | - Jennifer Locke
- Division of Urology, Department of Surgery, University of British Columbia, Vancouver, British Columbia, Canada
| | - Shabbir M H Alibhai
- Department of Medicine, University Health Network, University of Toronto, Toronto, Ontario, Canada
| | - Girish S Kulkarni
- Division of Urology, Department of Surgery, University Health Network, University of Toronto, Toronto, Ontario, Canada; Institute for Clinical Evaluative Sciences, University of Toronto, Ontario, Canada
| | - David S Margel
- Division of Urology and Davidoff Cancer Center, Rabin Medical Center, Petah Tikva, Israel
| | - Robert J Hamilton
- Division of Urology, Department of Surgery, University Health Network, University of Toronto, Toronto, Ontario, Canada
| | - Antonio Finelli
- Division of Urology, Department of Surgery, University Health Network, University of Toronto, Toronto, Ontario, Canada
| | - John Trachtenberg
- Division of Urology, Department of Surgery, University Health Network, University of Toronto, Toronto, Ontario, Canada
| | - Alexandre R Zlotta
- Division of Urology, Department of Surgery, University Health Network, University of Toronto, Toronto, Ontario, Canada
| | - Ants Toi
- Department of Medical Imaging, University Health Network, University of Toronto, Toronto, Ontario, Canada
| | - Karen M Hersey
- Division of Urology, Department of Surgery, University Health Network, University of Toronto, Toronto, Ontario, Canada
| | - Andrew Evans
- Department of Pathology, University Health Network, University of Toronto, Toronto, Ontario, Canada
| | | | - Neil E Fleshner
- Division of Urology, Department of Surgery, University Health Network, University of Toronto, Toronto, Ontario, Canada
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Abstract
The purpose of this review is to identify clinical risk factors for prostate cancer and to assess the utility and limitations of our current tools for prostate cancer screening. Prostate-specific antigen is the single most important factor for identifying men at increased risk of prostate cancer but is best assessed in the context of other clinical factors; increasing age, race, and family history are well-established risk factors for the diagnosis of prostate cancer. In addition to clinical risk calculators, novel tools such as multiparametric imaging, serum or urinary biomarkers, and genetic profiling show promise in improving prostate cancer diagnosis and characterization. Optimal use of existing and future tools will help alleviate the problems of overdiagnosis and overtreatment of low-risk prostate cancer without reversing the substantial mortality declines that have been achieved in the screening era.
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Early Detection, PSA Screening, and Management of Overdiagnosis. Hematol Oncol Clin North Am 2013; 27:1091-110, vii. [DOI: 10.1016/j.hoc.2013.08.002] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
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Zhu X, Roobol MJ, Steyerberg EW. Reply from Authors re: Noel W. Clarke. Coming Up for Air: Follow-up and Risk Stratification After Negative Prostate Cancer Screening. Eur Urol 2013;63:634–5. Eur Urol 2013. [DOI: 10.1016/j.eururo.2012.08.068] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/27/2022]
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Ukimura O, Coleman JA, de la Taille A, Emberton M, Epstein JI, Freedland SJ, Giannarini G, Kibel AS, Montironi R, Ploussard G, Roobol MJ, Scattoni V, Jones JS. Contemporary Role of Systematic Prostate Biopsies: Indications, Techniques, and Implications for Patient Care. Eur Urol 2013; 63:214-30. [PMID: 23021971 DOI: 10.1016/j.eururo.2012.09.033] [Citation(s) in RCA: 168] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2012] [Accepted: 09/14/2012] [Indexed: 02/06/2023]
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Bokhorst LP, Zhu X, Bul M, Bangma CH, Schröder FH, Roobol MJ. Positive predictive value of prostate biopsy indicated by prostate-specific-antigen-based prostate cancer screening: trends over time in a European randomized trial*. BJU Int 2012; 110:1654-60. [PMID: 23043563 DOI: 10.1111/j.1464-410x.2012.11481.x] [Citation(s) in RCA: 30] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
UNLABELLED Study Type--Diagnosis (validating cohort) Level of Evidence 1b. What's known on the subject? and What does the study add? The European Randomized study of Screening for Prostate Cancer (ERSPC) showed a reduction in prostate cancer mortality of 21% for PSA-based screening at a median follow-up of 11 years. In the ERSPC, men are screened at 4-year intervals. A prostate biopsy is recommended for men with a PSA level ≥ 3.0 ng/mL. The study shows that the positive predictive value (PPV) of a prostate biopsy indicated by PSA-based screening remains equal throughout consecutive screening rounds in men without a previous biopsy. In men who have previously had a benign biopsy, the PPV drops considerably, but 20% of the cancers detected still show aggressive characteristics. OBJECTIVE • To assess the positive predictive value (PPV) of prostate biopsy, indicated by a prostate-specific antigen (PSA) threshold of ≥ 3.0 ng/mL, over time, in the Rotterdam section of the European Randomized study of Screening for Prostate Cancer (ERSPC). PATIENTS AND METHODS • In the Rotterdam section of the ERSPC, a total of 42,376 participants, aged 55-74 years, identified from population registries were randomly assigned to a screening or control arm. • For the ERSPC men undergo PSA screening at 4-year intervals. A total of three screening rounds were evaluated; therefore, only men aged 55-69 years at the first screening were eligible for the present study. RESULTS • PPVs for men without previous biopsy remained equal throughout the three subsequent screenings (25.5, 22.3 and 24.8% respectively). • Conversely, PPVs for men with a previous negative biopsy dropped significantly (12.0 and 15.2% at the second and third screening, respectively). • Additionally, in men with and without previous biopsy, the percentage of aggressive prostate cancers (clinical stage >T2b, Gleason score ≥ 7) decreased after the first round of screening from 44.4 to 23.8% in the second (P < 0.001) and 18.6% in the third round (P < 0.001). • Repeat biopsies accounted for 24.6% of all biopsies, but yielded only 8.6% of all aggressive cancers. CONCLUSIONS • In consecutive screening rounds the PPV of PSA-based screening remains equal in previously unbiopsied men. • In men with a previous negative biopsy the PPV drops considerably, but 20% of cancers detected still show aggressive characteristics. • Individualized screening algorithms should incorporate previous biopsy status in the decision to perform a repeat biopsy with the aim of further reducing unnecessary biopsies.
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Affiliation(s)
- Leonard P Bokhorst
- Department of Urology, Erasmus University Medical Center, Rotterdam, The Netherlands.
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Bangma C. [-2]pro-prostate specific antigen as an aid in prostate biopsy. J Urol 2012; 188:1070-1. [PMID: 22901580 DOI: 10.1016/j.juro.2012.07.057] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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van Vugt HA, Kranse R, Steyerberg EW, van der Poel HG, Busstra M, Kil P, Oomens EH, de Jong IJ, Bangma CH, Roobol MJ. Prospective validation of a risk calculator which calculates the probability of a positive prostate biopsy in a contemporary clinical cohort. Eur J Cancer 2012; 48:1809-15. [DOI: 10.1016/j.ejca.2012.02.002] [Citation(s) in RCA: 33] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2011] [Revised: 02/01/2012] [Accepted: 02/09/2012] [Indexed: 11/26/2022]
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A Calculator for Prostate Cancer Risk 4 Years After an Initially Negative Screen: Findings from ERSPC Rotterdam. Eur Urol 2012; 63:627-33. [PMID: 22841675 DOI: 10.1016/j.eururo.2012.07.029] [Citation(s) in RCA: 32] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2012] [Accepted: 07/12/2012] [Indexed: 11/22/2022]
Abstract
BACKGROUND Inconclusive test results often occur after prostate-specific antigen (PSA)-based screening for prostate cancer (PCa), leading to uncertainty on whether, how, and when to repeat testing. OBJECTIVE To develop and validate a prediction tool for the risk of PCa 4 yr after an initially negative screen. DESIGN, SETTING, AND PARTICIPANTS We analyzed data from 15 791 screen-negative men aged 55-70 yr at the initial screening round of the Rotterdam section of the European Randomized Study of Screening for Prostate Cancer. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS Follow-up and repeat screening at 4 yr showed either no PCa, low-risk PCa, or potentially high-risk PCa (defined as clinical stage >T2b and/or biopsy Gleason score ≥ 7 and/or PSA ≥ 10.0 ng/ml). A multinomial logistic regression analysis included initial screening data on age, PSA, digital rectal examination (DRE), family history, prostate volume, and having had a previous negative biopsy. The 4-yr risk predictions were validated with additional follow-up data up to 8 yr after initial screening. RESULTS AND LIMITATIONS Positive family history and, especially, PSA level predicted PCa, whereas a previous negative biopsy or a large prostate volume reduced the likelihood of future PCa. The risk of having PCa 4 yr after an initially negative screen was 3.6% (interquartile range: 1.0-4.7%). Additional 8-yr follow-up data confirmed these predictions. Although data were based on sextant biopsies and a strict protocol-based biopsy indication, we suggest that men with a low predicted 4-yr risk (eg, ≤ 1.0%) could be rescreened at longer intervals or not at all, depending on competing risks, while men with an elevated 4-yr risk (eg, ≥ 5%) might benefit from immediate retesting. These findings need to be validated externally. CONCLUSIONS This 4-yr future risk calculator, based on age, PSA, DRE, family history, prostate volume, and previous biopsy status, may be a promising tool for reducing uncertainty, unnecessary testing, and overdiagnosis of PCa.
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Loeb S, van den Heuvel S, Zhu X, Bangma CH, Schroder FH, Roobol MJ. Reply from Authors re: Alexandre R. Zlotta, Robert K. Nam. To Biopsy or Not to Biopsy—Thou Shall Think Twice. Eur Urol 2012;61:1115–7. Eur Urol 2012. [DOI: 10.1016/j.eururo.2012.02.056] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/28/2022]
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Roobol MJ, Bangma CH, Loeb S. Prostate-specific antigen screening can be beneficial to younger and at-risk men. CMAJ 2012; 185:47-51. [PMID: 22566532 DOI: 10.1503/cmaj.111962] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/02/2023] Open
Affiliation(s)
- Monique J Roobol
- Department of Urology, Erasmus University Medical Centre, Rotterdam, the Netherlands.
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