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Schmit S, Malshy K, Ochsner A, Golijanin B, Tucci C, Braunagel T, Golijanin D, Pareek G, Hyams E. Lower urinary tract symptoms in elderly men: Considerations for prostate cancer testing. Prostate 2024; 84:1290-1300. [PMID: 39051612 DOI: 10.1002/pros.24772] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/29/2024] [Revised: 06/24/2024] [Accepted: 07/15/2024] [Indexed: 07/27/2024]
Abstract
PURPOSE Both lower urinary tract symptoms (LUTS) and prostate cancer (PCa) are common in elderly men. While LUTS are generally due to a benign etiology, they may provoke an evaluation with prostate-specific antigen (PSA), which can lead to a cascade of further testing and possible overdiagnosis in patients with competing risks. There is limited patient and provider understanding of the relationship between LUTS and PCa risk, and a lack of clarity in how to evaluate these men to balance appropriate diagnosis of aggressive PCa with avoidance of overdiagnosis. METHODS A literature review was performed using keywords to query the electronic database PubMed. All articles published before November 2023 were screened by title and abstract for articles relevant to our subject. RESULTS Epidemiological studies suggest that LUTS and PCa are largely independent in elderly men. The best available tools to assess PCa risk include PSA permutations, novel biomarkers, and imaging, but there are limitations in older men based on lack of validation in the elderly and unclear applicability of traditional definitions of "clinically significant" disease. We present a three-tiered approach to evaluating these patients. CONCLUSION Elderly men commonly have LUTS as well as a high likelihood of indolent PCa. A systematic and shared decision-making-based approach can help to balance objectives of appropriate detection of phenotypically dangerous disease and avoidance of over-testing and overdiagnosis.
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Affiliation(s)
- Stephen Schmit
- The Minimally Invasive Urology Institute at The Miriam Hospital, Division of Urology, Warren Alpert Medical School of Brown University, Providence, RI, USA, Warren Alpert Medical School of Brown University, Providence, Rhode Island, USA
| | - Kamil Malshy
- The Minimally Invasive Urology Institute at The Miriam Hospital, Division of Urology, Warren Alpert Medical School of Brown University, Providence, RI, USA, Warren Alpert Medical School of Brown University, Providence, Rhode Island, USA
| | - Anna Ochsner
- The Minimally Invasive Urology Institute at The Miriam Hospital, Division of Urology, Warren Alpert Medical School of Brown University, Providence, RI, USA, Warren Alpert Medical School of Brown University, Providence, Rhode Island, USA
| | - Borivoj Golijanin
- The Minimally Invasive Urology Institute at The Miriam Hospital, Division of Urology, Warren Alpert Medical School of Brown University, Providence, RI, USA, Warren Alpert Medical School of Brown University, Providence, Rhode Island, USA
| | - Christopher Tucci
- The Minimally Invasive Urology Institute at The Miriam Hospital, Division of Urology, Warren Alpert Medical School of Brown University, Providence, RI, USA, Warren Alpert Medical School of Brown University, Providence, Rhode Island, USA
| | - Taylor Braunagel
- The Minimally Invasive Urology Institute at The Miriam Hospital, Division of Urology, Warren Alpert Medical School of Brown University, Providence, RI, USA, Warren Alpert Medical School of Brown University, Providence, Rhode Island, USA
| | - Dragan Golijanin
- The Minimally Invasive Urology Institute at The Miriam Hospital, Division of Urology, Warren Alpert Medical School of Brown University, Providence, RI, USA, Warren Alpert Medical School of Brown University, Providence, Rhode Island, USA
| | - Gyan Pareek
- The Minimally Invasive Urology Institute at The Miriam Hospital, Division of Urology, Warren Alpert Medical School of Brown University, Providence, RI, USA, Warren Alpert Medical School of Brown University, Providence, Rhode Island, USA
| | - Elias Hyams
- The Minimally Invasive Urology Institute at The Miriam Hospital, Division of Urology, Warren Alpert Medical School of Brown University, Providence, RI, USA, Warren Alpert Medical School of Brown University, Providence, Rhode Island, USA
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Leni R, Vertosick EA, van den Bergh RC, Soeterik TF, Heetman JG, van Melick HH, Roscigno M, La Croce G, Da Pozzo LF, Olivier J, Zattoni F, Facco M, Dal Moro F, Chiu PK, Wu X, Heidegger I, Giannini G, Bianchi L, Lampariello L, Quarta L, Salonia A, Montorsi F, Briganti A, Capitanio U, Carlsson SV, Vickers AJ, Gandaglia G. Oncologic Outcomes of Incidental Versus Biopsy-diagnosed Grade Group 1 Prostate Cancer: A Multi-institutional Study. EUR UROL SUPPL 2024; 68:10-17. [PMID: 39257622 PMCID: PMC11382210 DOI: 10.1016/j.euros.2024.08.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/05/2024] [Indexed: 09/12/2024] Open
Abstract
Background and objective Patients diagnosed with grade group (GG) 1 prostate cancer (PCa) following treatment for benign disease ("incidental" PCa) are typically managed with active surveillance (AS). It is not known how their outcomes compare with those observed in patients diagnosed with GG1 on biopsy. We aimed at determining whether long-term oncologic outcomes of AS for patients with GG1 PCa differ according to the type of diagnosis: incidental versus biopsy detected. Methods A retrospective, multi-institutional analysis of PCa patients with GG1 on AS at eight institutions was conducted. Competing risk analyses estimated the incidence of metastases, PCa mortality, and conversion to treatment. As a secondary analysis, we estimated the risk of GG ≥2 on the first follow-up biopsy according to the type of initial diagnosis. Key findings and limitations A total of 213 versus 1900 patients with incidental versus biopsy-diagnosed GG1 were identified. Patients with incidental cancers were followed with repeated biopsies and multiparametric magnetic resonance imaging less frequently than those diagnosed on biopsy. The 10-yr incidence of treatment was 22% for incidental cancers versus 53% for biopsy (subdistribution hazard ratio [sHR] 0.34, 95% confidence interval [CI] 0.26-0.46, p < 0.001). Distant metastases developed in one patient with incidental cancer versus 17 diagnosed on biopsy and were diagnosed with molecular imaging in 13 (72%) patients. The 10-yr incidence of metastases was 0.8% for patients with incidental PCa and 2% for those diagnosed on biopsy (sHR 0.35, 95% CI 0.05-2.54, p = 0.3). The risk of GG ≥2 on the first follow-up biopsy was low if the initial diagnosis was incidental (7% vs 22%, p < 0.001). Conclusions and clinical implications Patients with GG1 incidental PCa should be evaluated further to exclude aggressive disease, preferably with a biopsy. If no cancer is found on biopsy, then they should receive the same follow-up of a patient with a negative biopsy. Further research should confirm whether imaging and biopsies can be avoided if postoperative prostate-specific antigen is low (<1-2 ng/ml). Patient summary We compared the outcomes of patients with low-grade prostate cancer on active surveillance according to the type of their initial diagnosis. Patients who have low-grade cancer diagnosed on a procedure to relieve urinary symptoms (incidental prostate cancer) are followed less intensively and undergo curative-intended treatment less frequently. We also found that patients with incidental prostate cancer are more likely to have no cancer on their first follow-up biopsy than patients who have low-grade cancer initially diagnosed on a biopsy. These patients have a more favorable prognosis than their biopsy-detected counterparts and should be managed the same way as patients with negative biopsies if they undergo a subsequent biopsy that shows no cancer.
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Affiliation(s)
- Riccardo Leni
- Division of Experimental Oncology, Department of Urology, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Vita-Salute San Raffaele University, Milan, Italy
- Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Emily A. Vertosick
- Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Roderick C.N. van den Bergh
- Department of Urology, St. Antonius Ziekenhuis, Nieuwegein, The Netherlands
- Department of Urology, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Timo F.W. Soeterik
- Department of Urology, St. Antonius Ziekenhuis, Nieuwegein, The Netherlands
- Department of Radiation Oncology, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Joris G. Heetman
- Department of Urology, St. Antonius Ziekenhuis, Nieuwegein, The Netherlands
| | | | - Marco Roscigno
- Department of Urology, ASST Papa Giovanni XXIII, Bergamo, Italy
- University of Milano-Bicocca, Milan, Italy
| | - Giovanni La Croce
- Department of Urology, ASST Papa Giovanni XXIII, Bergamo, Italy
- University of Milano-Bicocca, Milan, Italy
| | - Luigi F. Da Pozzo
- Department of Urology, ASST Papa Giovanni XXIII, Bergamo, Italy
- University of Milano-Bicocca, Milan, Italy
| | | | - Fabio Zattoni
- Department of Surgery, Oncology and Gastroenterology, Urology Clinic, University of Padua, Padua, Italy
| | - Matteo Facco
- Department of Surgery, Oncology and Gastroenterology, Urology Clinic, University of Padua, Padua, Italy
| | - Fabrizio Dal Moro
- Department of Surgery, Oncology and Gastroenterology, Urology Clinic, University of Padua, Padua, Italy
| | - Peter K.F. Chiu
- Division of Urology, Department of Surgery, SH Ho Urology Centre, The Chinese University of Hong Kong, Hong Kong, Hong Kong
| | - Xiaobo Wu
- Division of Urology, Department of Surgery, SH Ho Urology Centre, The Chinese University of Hong Kong, Hong Kong, Hong Kong
| | - Isabel Heidegger
- Department of Urology, Medical University Innsbruck, Innsbruck, Austria
| | - Giulia Giannini
- Department of Urology, Medical University Innsbruck, Innsbruck, Austria
| | - Lorenzo Bianchi
- Division of Urology, IRCCS Azienda Ospedaliero-Universitaria di Bologna, University of Bologna, Bologna, Italy
| | - Luca Lampariello
- Division of Urology, IRCCS Azienda Ospedaliero-Universitaria di Bologna, University of Bologna, Bologna, Italy
| | - Leonardo Quarta
- Division of Experimental Oncology, Department of Urology, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Vita-Salute San Raffaele University, Milan, Italy
| | - Andrea Salonia
- Division of Experimental Oncology, Department of Urology, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Vita-Salute San Raffaele University, Milan, Italy
| | - Francesco Montorsi
- Division of Experimental Oncology, Department of Urology, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Vita-Salute San Raffaele University, Milan, Italy
| | - Alberto Briganti
- Division of Experimental Oncology, Department of Urology, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Vita-Salute San Raffaele University, Milan, Italy
| | - Umberto Capitanio
- Division of Experimental Oncology, Department of Urology, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Vita-Salute San Raffaele University, Milan, Italy
| | - Sigrid V. Carlsson
- Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Urology Service, Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Department of Urology, Sahlgrenska Academy at Gothenburg University, Gothenburg, Sweden
- Department of Translational Medicine, Division of Urological Cancers, Medical Faculty, Lund University, Lund, Sweden
| | - Andrew J. Vickers
- Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Giorgio Gandaglia
- Division of Experimental Oncology, Department of Urology, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Vita-Salute San Raffaele University, Milan, Italy
| | - EAU-YAU Prostate Cancer Working Group
- Division of Experimental Oncology, Department of Urology, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Vita-Salute San Raffaele University, Milan, Italy
- Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Department of Urology, St. Antonius Ziekenhuis, Nieuwegein, The Netherlands
- Department of Urology, Erasmus University Medical Center, Rotterdam, The Netherlands
- Department of Radiation Oncology, University Medical Center Utrecht, Utrecht, The Netherlands
- Department of Urology, ASST Papa Giovanni XXIII, Bergamo, Italy
- University of Milano-Bicocca, Milan, Italy
- Department of Urology, Lille University, Lille, France
- Department of Surgery, Oncology and Gastroenterology, Urology Clinic, University of Padua, Padua, Italy
- Division of Urology, Department of Surgery, SH Ho Urology Centre, The Chinese University of Hong Kong, Hong Kong, Hong Kong
- Department of Urology, Medical University Innsbruck, Innsbruck, Austria
- Division of Urology, IRCCS Azienda Ospedaliero-Universitaria di Bologna, University of Bologna, Bologna, Italy
- Urology Service, Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Department of Urology, Sahlgrenska Academy at Gothenburg University, Gothenburg, Sweden
- Department of Translational Medicine, Division of Urological Cancers, Medical Faculty, Lund University, Lund, Sweden
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Palmisano F, Lorusso V, Legnani R, Martorello V, Nedbal C, Tramanzoli P, Marchesotti F, Ferraro S, Talso M, Granata AM, Sighinolfi MC, Rocco B, Gregori A. Analysis of the Performance and Accuracy of a PSA and PSA Ratio-Based Nomogram to Predict the Probability of Prostate Cancer in a Cohort of Patients with PIRADS 3 Findings at Multiparametric Magnetic Resonance Imaging. Cancers (Basel) 2024; 16:3084. [PMID: 39272942 PMCID: PMC11394649 DOI: 10.3390/cancers16173084] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2024] [Revised: 08/29/2024] [Accepted: 09/03/2024] [Indexed: 09/15/2024] Open
Abstract
BACKGROUND PIRADS score 3 represents a challenge in prostate cancer (PCa) detection with MRI. Our study aimed to evaluate the application of a nomogram on a cohort of patients with PIRADS 3. METHODS We analyzed 286 patients undergoing fusion prostate biopsy from January 2020 to February 2024. Only PIRADS 3 patients were included. Two nomograms, previously developed and based on clinical variables such as age, total PSA (specifically 2-10 ng/mL) and PSA ratio were applied to estimate the probability (Nomograms A and B) for PCa Grade Group (GG) > 3 and GG < 3. RESULTS Out of the 70 patients available for analysis, 14/70 patients (20%) had PCa, 4/14 were GG 1 (28.6%), 1/14 were GG 2 (7.1%), 5/14 were GG 3 (35.8%), 2/14 were GG 4 (14.3%) and 2/14 were GG 5 (14.3%). The median probability of PCa GG > 3 and GG < 3 was 5% and 33%, respectively. A significant difference (p = 0.033) was found between patients with negative versus positive biopsy for Nomogram B. There was a significant difference (p = 0.029) for Nomogram B comparing patients with GG < 3 and GG > 3. Using a cut-off of 40% for Nomogram B, sensitivity and specificity were 70% and 80%, respectively. CONCLUSIONS This cohort has a low probability of harboring PCa especially ISUP > 3. Nomogram B has good accuracy for discriminating patients with PCa from those with negative biopsy.
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Affiliation(s)
- Franco Palmisano
- Department of Urology, ASST Fatebenefratelli-Sacco Hospital, 20157 Milan, Italy
| | - Vito Lorusso
- Department of Urology, ASST Fatebenefratelli-Sacco Hospital, 20157 Milan, Italy
| | - Rebecca Legnani
- Department of Urology, ASST Fatebenefratelli-Sacco Hospital, 20157 Milan, Italy
| | - Vincenzo Martorello
- Department of Urology, ASST Fatebenefratelli-Sacco Hospital, 20157 Milan, Italy
| | - Carlotta Nedbal
- Department of Urology, ASST Fatebenefratelli-Sacco Hospital, 20157 Milan, Italy
| | - Pietro Tramanzoli
- Department of Urology, ASST Fatebenefratelli-Sacco Hospital, 20157 Milan, Italy
| | | | - Simona Ferraro
- Pediatric Department, Buzzi Children's Hospital, 20154 Milan, Italy
| | - Michele Talso
- Department of Urology, ASST Fatebenefratelli-Sacco Hospital, 20157 Milan, Italy
| | | | | | - Bernardo Rocco
- Department of Urology, ASST Santi Paolo e Carlo, University of Milan, 20142 Milan, Italy
- University of Milan, 20122 Milan, Italy
| | - Andrea Gregori
- Department of Urology, ASST Fatebenefratelli-Sacco Hospital, 20157 Milan, Italy
- University of Milan, 20122 Milan, Italy
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Lacson R, Haj-Mirzaian A, Burk K, Glazer DI, Naik S, Khorasani R, Kibel AS. A Model for Predicting Clinically Significant Prostate Cancer Using Prostate MRI and Risk Factors. J Am Coll Radiol 2024; 21:1419-1427. [PMID: 38719106 DOI: 10.1016/j.jacr.2024.02.035] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2024] [Revised: 02/16/2024] [Accepted: 02/22/2024] [Indexed: 06/10/2024]
Abstract
PURPOSE The aim of this study was to develop and validate a predictive model for clinically significant prostate cancer (csPCa) using prostate MRI and patient risk factors. METHODS In total, 960 men who underwent MRI from 2015 to 2019 and biopsy either 6 months before or 6 months after MRI were identified. Men diagnosed with csPCa were identified, and csPCa risk was modeled using known patient factors (age, race, and prostate-specific antigen [PSA] level) and prostate MRI findings (location, Prostate Imaging Reporting and Data System score, extraprostatic extension, dominant lesion size, and PSA density). csPCa was defined as Gleason score sum ≥ 7. Using a derivation cohort, a multivariable logistic regression model and a point-based scoring system were developed to predict csPCa. Discrimination and calibration were assessed in a separate independent validation cohort. RESULTS Among 960 MRI reports, 552 (57.5%) were from men diagnosed with csPCa. Using the derivation cohort (n = 632), variables that predicted csPCa were Prostate Imaging Reporting and Data System scores of 4 and 5, the presence of extraprostatic extension, and elevated PSA density. Evaluation using the validation cohort (n = 328) resulted in an area under the curve of 0.77, with adequate calibration (Hosmer-Lemeshow P = .58). At a risk threshold of >2 points, the model identified csPCa with sensitivity of 98.4% and negative predictive value of 78.6% but prevented only 4.3% potential biopsies (0-2 points; 14 of 328). At a higher threshold of >5 points, the model identified csPCa with sensitivity of 89.5% and negative predictive value of 70.1% and avoided 20.4% of biopsies (0-5 points; 67 of 328). CONCLUSIONS The point-based model reported here can potentially identify a vast majority of men at risk for csPCa, while avoiding biopsy in about 1 in 5 men with elevated PSA levels.
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Affiliation(s)
- Ronilda Lacson
- Department of Radiology, Brigham and Women's Hospital, Boston, Massachusetts; Harvard Medical School, Boston, Massachusetts; Associate Director, Center for Evidence-Based Imaging, Brigham and Women's Hospital, Boston, Massachusetts.
| | - Arya Haj-Mirzaian
- Department of Radiology, Brigham and Women's Hospital, Boston, Massachusetts; Harvard Medical School, Boston, Massachusetts
| | - Kristine Burk
- Department of Radiology, Brigham and Women's Hospital, Boston, Massachusetts; Harvard Medical School, Boston, Massachusetts; Quality and Patient Safety Officer, Mass General Brigham, Boston, Massachusetts
| | - Daniel I Glazer
- Department of Radiology, Brigham and Women's Hospital, Boston, Massachusetts; Harvard Medical School, Boston, Massachusetts; Medical Director of CT and Director, Cross-Sectional Interventional Radiology, Department of Radiology, Brigham and Women's Hospital, Boston, Massachusetts
| | - Sachin Naik
- Department of Radiology, Brigham and Women's Hospital, Boston, Massachusetts; Harvard Medical School, Boston, Massachusetts
| | - Ramin Khorasani
- Department of Radiology, Brigham and Women's Hospital, Boston, Massachusetts; Harvard Medical School, Boston, Massachusetts; Vice Chair, Radiology Quality and Safety, Mass General Brigham, Boston, Massachusetts; and Vice Chair of Radiology, Distinguished Chair, Medical Informatics, and Director, Center for Evidence-Based Imaging, Brigham and Women's Hospital, Boston, Massachusetts
| | - Adam S Kibel
- Harvard Medical School, Boston, Massachusetts; Department of Surgery and Chair, Department of Urology, Brigham and Women's Hospital, Boston, Massachusetts
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Şahin B, Çetin S, Sözen S, Aslan G, Çelik S, Türkeri L. A novel nomogram to predict clinically significant prostate cancer in MR assisted lesion biopsies: Turkish urooncology association nomogram. Urol Oncol 2024; 42:288.e17-288.e25. [PMID: 38782675 DOI: 10.1016/j.urolonc.2024.04.015] [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: 02/07/2024] [Revised: 04/10/2024] [Accepted: 04/14/2024] [Indexed: 05/25/2024]
Abstract
OBJECTIVE This study aimed to develop a novel nomogram to predict clinically significant prostate cancer in patients undergoing multi-parametric prostate MRI-assisted lesion biopsies, addressing the challenges in deciding on biopsy for patients with PI-RADS 3 lesions and follow-up strategies for patients with negative PI-RADS 4 or 5 lesions. MATERIALS AND METHODS A retrospective case-control study was conducted using the Turkish Urooncology Association Databases (UROCaD). The final dataset included 2428 lesion biopsy data. Univariate analysis, logistic regression, and validation were performed, with 1942 and 486 lesion biopsy data in the training and validation datasets, respectively. RESULTS Age, initial total PSA value, PSA density, prostate volume, lesion length, DRE findings, and PI-RADS score were significantly different between benign or non-significant cancer and clinically significant prostate cancer groups. The developed nomogram incorporated PSA density, age, PI-RADS score, lesion length, and DRE findings. The mean area under the curve for the 6-fold cross-validation was 0.836, while the area under the curve values for the training and validation datasets were 0.827 and 0.861, respectively. The nomogram demonstrated a sensitivity of 75.6% and a specificity of 74.8% at a cut-off score of 24.9, with positive and negative predictive values of 42.2% and 92.6%, respectively. CONCLUSION The TUA nomogram, based on PSA density, age, PI-RADS score, lesion length, and DRE findings, provides a reliable and accurate prediction tool for detecting clinically significant prostate cancer in patients undergoing multi-parametric prostate MRI-assisted lesion (fusion) biopsies, potentially improving patient management and reducing unnecessary biopsies.
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Affiliation(s)
- Bahadır Şahin
- Urology Department, Marmara University School of Medicine, İstanbul, Turkey.
| | - Serhat Çetin
- Urology Department, Gazi University School of Medicine, Ankara, Turkey
| | - Sinan Sözen
- Urology Department, Gazi University School of Medicine, Ankara, Turkey
| | - Güven Aslan
- Urology Department, Dokuz Eylül University School of Medicine, İzmir, Turkey
| | - Serdar Çelik
- Urology Department, University of Health Sciences Turkey, Izmir Faculty of Medicine, Izmir City Hospital, İzmir, Turkey
| | - Levent Türkeri
- Urology Department, Acıbadem University School of Medicine, İstanbul, Turkey
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Jiang S, Lu F, Chen J, Jiao Y, Qiu Q, Nian X, Qu M, Wang Y, Li M, Liu F, Gao X. UPCARE: Urinary Extracellular Vesicles-Derived Prostate Cancer Assessment for Risk Evaluation. J Extracell Vesicles 2024; 13:e12491. [PMID: 39175282 PMCID: PMC11341834 DOI: 10.1002/jev2.12491] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2024] [Revised: 06/12/2024] [Accepted: 07/01/2024] [Indexed: 08/24/2024] Open
Abstract
In the quest for efficient tumor diagnosis via liquid biopsy, extracellular vesicles (EVs) have shown promise as a source of potential biomarkers. This study addresses the gap in biomarker efficacy for predicting clinically significant prostate cancer (csPCa) between the Western and Chinese populations. We developed a urinary extracellular vesicles-based prostate score (EPS) model, utilizing the EXODUS technique for EV isolation from 598 patients and incorporating gene expressions of FOXA1, PCA3, and KLK3. Our findings reveal that the EPS model surpasses prostate-specific antigen (PSA) testing in diagnostic accuracy within a training cohort of 234 patients, achieving an area under the curve (AUC) of 0.730 compared to 0.659 for PSA (p = 0.018). Similarly, in a validation cohort of 101 men, the EPS model achieved an AUC of 0.749, which was significantly better than PSA's 0.577 (p < 0.001). Our model has demonstrated a potential reduction in unnecessary prostate biopsies by 26%, with only a 3% miss rate for csPCa cases, indicating its effectiveness in the Chinese population.
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Affiliation(s)
- Shaoqin Jiang
- Department of UrologyFujian Union Hospital, Fujian Medical UniversityFuzhouFujianChina
| | - Feiting Lu
- Shenzhen Huixin Lifetechnologies Co., Ltd.Longhua, ShenzhenGuangdongChina
| | - Jiadi Chen
- Department of Clinical LaboratoryFujian Union Hospital, Fujian Medical UniversityFuzhouFujianChina
| | - Yingzhen Jiao
- Shenzhen Huixin Lifetechnologies Co., Ltd.Longhua, ShenzhenGuangdongChina
| | - Qingqing Qiu
- Shenzhen Huixin Lifetechnologies Co., Ltd.Longhua, ShenzhenGuangdongChina
| | - Xinwen Nian
- Department of UrologyChanghai HospitalShanghaiChina
| | - Min Qu
- Department of UrologyChanghai HospitalShanghaiChina
| | - Yan Wang
- Department of UrologyChanghai HospitalShanghaiChina
| | - Mengqiang Li
- Department of UrologyFujian Union Hospital, Fujian Medical UniversityFuzhouFujianChina
| | - Fei Liu
- Department of MedicineBrigham and Women's Hospital, Harvard Medical SchoolBostonMassachusettsUSA
| | - Xu Gao
- Department of UrologyChanghai HospitalShanghaiChina
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7
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van Harten MJ, Roobol MJ, van Leeuwen PJ, Willemse PPM, van den Bergh RCN. Evolution of European prostate cancer screening protocols and summary of ongoing trials. BJU Int 2024; 134:31-42. [PMID: 38469728 DOI: 10.1111/bju.16311] [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] [Indexed: 03/13/2024]
Abstract
Population-based organised repeated screening for prostate cancer has been found to reduce disease-specific mortality, but with substantial overdiagnosis leading to overtreatment. Although only very few countries have implemented a screening programme on a national level, individual prostate-specific antigen (PSA) testing is common. This opportunistic testing may have little favourable impact, while stressing the side-effects. The classic early detection protocols as were state-of-the-art in the 1990s applied a PSA and digital rectal examination threshold for sextant systematic prostate biopsy, with a fixed interval for re-testing, and limited indication for expectant management. In the three decades since these trials were started, different important improvements have become available in the cascade of screening, indication for biopsy, and treatment. The main developed aspects include: better identification of individuals at risk (using early/baseline PSA, family history, and/or genetic profile), individualised re-testing interval, optimised and individualised starting and stopping age, with gradual invitation at a fixed age rather than invitation of a wider range of age groups, risk stratification for biopsy (using PSA density, risk calculator, magnetic resonance imaging, serum and urine biomarkers, or combinations/sequences), targeted biopsy, transperineal biopsy approach, active surveillance for low-risk prostate cancer, and improved staging of disease. All these developments are suggested to decrease the side-effects of screening, while at least maintaining the advantages, but Level 1 evidence is lacking. The knowledge gained and new developments on early detection are being tested in different prospective screening trials throughout Europe. In addition, the European Union-funded PRostate cancer Awareness and Initiative for Screening in the European Union (PRAISE-U) project will compare and evaluate different screening pilots throughout Europe. Implementation and sustainability will also be addressed. Modern screening approaches may reduce the burden of the second most frequent cause of cancer-related death in European males, while minimising side-effects. Also, less efficacious opportunistic early detection may be indirectly reduced.
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Affiliation(s)
- Meike J van Harten
- Cancer Center, Department of Urology, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Monique J Roobol
- Cancer Institute, Erasmus University Medical Centre, Rotterdam, The Netherlands
| | | | - Peter-Paul M Willemse
- Cancer Center, Department of Urology, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Roderick C N van den Bergh
- Cancer Institute, Erasmus University Medical Centre, Rotterdam, The Netherlands
- St Antonius Hospital, Utrecht, The Netherlands
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8
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Hyndman ME, Paproski RJ, Kinnaird A, Fairey A, Marks L, Pavlovich CP, Fletcher SA, Zachoval R, Adamcova V, Stejskal J, Aprikian A, Wallis CJD, Pink D, Vasquez C, Beatty PH, Lewis JD. Development of an effective predictive screening tool for prostate cancer using the ClarityDX machine learning platform. NPJ Digit Med 2024; 7:163. [PMID: 38902526 PMCID: PMC11190196 DOI: 10.1038/s41746-024-01167-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2024] [Accepted: 06/12/2024] [Indexed: 06/22/2024] Open
Abstract
The current prostate cancer (PCa) screen test, prostate-specific antigen (PSA), has a high sensitivity for PCa but low specificity for high-risk, clinically significant PCa (csPCa), resulting in overdiagnosis and overtreatment of non-csPCa. Early identification of csPCa while avoiding unnecessary biopsies in men with non-csPCa is challenging. We built an optimized machine learning platform (ClarityDX) and showed its utility in generating models predicting csPCa. Integrating the ClarityDX platform with blood-based biomarkers for clinically significant PCa and clinical biomarker data from a 3448-patient cohort, we developed a test to stratify patients' risk of csPCa; called ClarityDX Prostate. When predicting high risk cancer in the validation cohort, ClarityDX Prostate showed 95% sensitivity, 35% specificity, 54% positive predictive value, and 91% negative predictive value, at a ≥ 25% threshold. Using ClarityDX Prostate at this threshold could avoid up to 35% of unnecessary prostate biopsies. ClarityDX Prostate showed higher accuracy for predicting the risk of csPCa than PSA alone and the tested model-based risk calculators. Using this test as a reflex test in men with elevated PSA levels may help patients and their healthcare providers decide if a prostate biopsy is necessary.
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Affiliation(s)
- M Eric Hyndman
- Department of Surgical Oncology, University of Calgary, Prostate Cancer Centre, Calgary, T2P 1P9, AB, Canada
- Nanostics Inc., 4550 10230 Jasper Avenue, Edmonton, T5J 4P6, AB, Canada
| | - Robert J Paproski
- Nanostics Inc., 4550 10230 Jasper Avenue, Edmonton, T5J 4P6, AB, Canada
| | - Adam Kinnaird
- Division of Urology, Department of Surgery, University of Alberta, Kipnes Urology Centre, Edmonton, T6G 1Z1, AB, Canada
- Department of Oncology, University of Alberta, Edmonton, T6G 2E1, AB, Canada
| | - Adrian Fairey
- Nanostics Inc., 4550 10230 Jasper Avenue, Edmonton, T5J 4P6, AB, Canada
- Division of Urology, Department of Surgery, University of Alberta, Kipnes Urology Centre, Edmonton, T6G 1Z1, AB, Canada
| | - Leonard Marks
- UCLA Health, Westwood Urology 200 Medical Plaza, Suite 140, Los Angeles, CA, 90095, USA
| | - Christian P Pavlovich
- James Buchanan Brady Urological Institute, Johns Hopkins University School of Medicine, Baltimore, 21287, MD, USA
| | - Sean A Fletcher
- James Buchanan Brady Urological Institute, Johns Hopkins University School of Medicine, Baltimore, 21287, MD, USA
| | - Roman Zachoval
- Department of Urology, 3rd Faculty of Medicine of Charles University and Thomayer University Hospital, Prague, Czech Republic
| | - Vanda Adamcova
- Department of Urology, 3rd Faculty of Medicine of Charles University and Thomayer University Hospital, Prague, Czech Republic
| | - Jiri Stejskal
- Department of Urology, 3rd Faculty of Medicine of Charles University and Thomayer University Hospital, Prague, Czech Republic
| | - Armen Aprikian
- Nanostics Inc., 4550 10230 Jasper Avenue, Edmonton, T5J 4P6, AB, Canada
- Department of Surgery, McGill University, Montreal, H3G 2M1, QC, Canada
| | - Christopher J D Wallis
- Division of Urology, Department of Surgery, University of Toronto, Toronto, M5T 1P5, ON, Canada
- Division of Urology, Department of Surgery, Mount Sinai Hospital, Toronto, M5G 1X5, ON, Canada
- Department of Surgical Oncology, University Health Network, Toronto, ON, Canada
| | - Desmond Pink
- Nanostics Inc., 4550 10230 Jasper Avenue, Edmonton, T5J 4P6, AB, Canada
| | - Catalina Vasquez
- Nanostics Inc., 4550 10230 Jasper Avenue, Edmonton, T5J 4P6, AB, Canada
| | - Perrin H Beatty
- Nanostics Inc., 4550 10230 Jasper Avenue, Edmonton, T5J 4P6, AB, Canada
| | - John D Lewis
- Nanostics Inc., 4550 10230 Jasper Avenue, Edmonton, T5J 4P6, AB, Canada.
- Department of Oncology, University of Alberta, Edmonton, T6G 2E1, AB, Canada.
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9
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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: 0] [Impact Index Per Article: 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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10
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Lee KM, Nelson TJ, Bryant A, Teerlink CC, Gulati R, Pagadala MS, Tcheandjieu C, Pridgen KM, DuVall SL, Yamoah K, Vassy JL, Seibert TM, Hauger RL, Rose BS, Lynch JA. Genetic risk and likelihood of prostate cancer detection on first biopsy by ancestry. J Natl Cancer Inst 2024; 116:753-757. [PMID: 38212986 PMCID: PMC11077300 DOI: 10.1093/jnci/djae002] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2023] [Revised: 11/03/2023] [Accepted: 12/23/2023] [Indexed: 01/13/2024] Open
Abstract
Despite differences in prostate cancer risk across ancestry groups, relative performance of prostate cancer genetic risks scores (GRS) for positive biopsy prediction in different ancestry groups is unknown. This cross-sectional retrospective analysis examines the association between a polygenic hazard score (PHS290) and risk of prostate cancer diagnosis upon first biopsy in male veterans using 2-sided tests. Our analysis included 36 717 veterans (10 297 of African ancestry). Unadjusted rates of positive first prostate biopsy increased with higher genetic risk (low risk: 34%, high risk: 58%; P < .001). Among men of African ancestry, higher genetic risk was associated with increased prostate cancer detection on first biopsy (odds ratio = 2.18, 95% confidence interval = 1.93 to 2.47), but the effect was stronger among men of European descent (odds ratio = 3.89, 95% confidence interval = 3.62 to 4.18). These findings suggest that incorporating genetic risk into prediction models could better personalize biopsy decisions, although further study is needed to achieve equitable genetic risk stratification among ancestry groups.
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Affiliation(s)
- Kyung Min Lee
- VA Informatics and Computing Infrastructure, VA Salt Lake City Health Care System, Salt Lake City, UT, USA
| | - Tyler J Nelson
- VA Informatics and Computing Infrastructure, VA Salt Lake City Health Care System, Salt Lake City, UT, USA
| | - Alex Bryant
- Department of Radiation Oncology, Veterans Affairs Ann Arbor Healthcare System, Ann Arbor, MI, USA
- Department of Radiation Oncology, University of Michigan, Ann Arbor, MI, USA
| | - Craig C Teerlink
- VA Informatics and Computing Infrastructure, VA Salt Lake City Health Care System, Salt Lake City, UT, USA
- Department of Internal Medicine, School of Medicine, University of Utah, Salt Lake City, UT, USA
| | - Roman Gulati
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, Washington, USA
| | - Meghana S Pagadala
- VA San Diego Healthcare System, San Diego, CA, USA
- Medical Scientist Training Program, University of California San Diego, La Jolla, CA, USA
- Biomedical Science Program, University of California San Diego, La Jolla, CA, USA
| | - Catherine Tcheandjieu
- VA Palo Alto Health Care System, Palo Alto, CA, USA
- Gladstone Institute of Data Science and Biotechnology, Gladstone Institutes, San Francisco, CA, USA
- Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA, USA
| | - Kathryn M Pridgen
- VA Informatics and Computing Infrastructure, VA Salt Lake City Health Care System, Salt Lake City, UT, USA
- Department of Internal Medicine, School of Medicine, University of Utah, Salt Lake City, UT, USA
| | - Scott L DuVall
- VA Informatics and Computing Infrastructure, VA Salt Lake City Health Care System, Salt Lake City, UT, USA
- Department of Internal Medicine, School of Medicine, University of Utah, Salt Lake City, UT, USA
| | - Kosj Yamoah
- Department of Radiation Oncology, H. Lee Moffitt Cancer Center, Tampa, FL, USA
- James A. Haley Veterans’ Hospital, Tampa, FL, USA
| | - Jason L Vassy
- Section of General Internal Medicine, VA Boston Healthcare System, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Department of Medicine, Brigham and Women’s Hospital, Boston, MA, USA
| | - Tyler M Seibert
- VA San Diego Healthcare System, San Diego, CA, USA
- Department of Radiation Medicine and Applied Sciences, University of California, San Diego, La Jolla, CA, USA
- Department of Radiology, University of California San Diego, La Jolla, CA, USA
- Department of Bioengineering, University of California San Diego, La Jolla, CA, USA
| | - Richard L Hauger
- VA San Diego Healthcare System, San Diego, CA, USA
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, CA, USA
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - Brent S Rose
- VA San Diego Healthcare System, San Diego, CA, USA
- Department of Radiation Medicine and Applied Sciences, University of California, San Diego, La Jolla, CA, USA
| | - Julie A Lynch
- VA Informatics and Computing Infrastructure, VA Salt Lake City Health Care System, Salt Lake City, UT, USA
- Department of Internal Medicine, School of Medicine, University of Utah, Salt Lake City, UT, USA
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11
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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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12
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Fiedorowicz JG, Merranko JA, Goldstein TR, Hower H, Iyengar S, Hafeman DM, Hunt JI, Strober M, Keller MB, Goldstein BI, Diler RS, Siddiqi S, Birmaher B. Validation of a youth suicide risk calculator in an adult sample with bipolar disorder. J Affect Disord 2024; 347:278-284. [PMID: 38007103 PMCID: PMC11022308 DOI: 10.1016/j.jad.2023.11.066] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/09/2023] [Revised: 11/08/2023] [Accepted: 11/18/2023] [Indexed: 11/27/2023]
Abstract
BACKGROUND Bipolar disorder (BD) conveys the highest risk of suicide of all mental disorders. We sought to externally validate a risk calculator (RC) of suicide attempts developed in youth with BD from the Course and Outcome of Bipolar Youth (COBY) study in an adult sample. METHODS A prospective cohort of adults with BD from the National Institute of Mental Health Collaborative Depression Study (CDS; N = 427; mean (+/- SD) age at intake (36 +/- 13 years)) was secondarily analyzed to validate the COBY RC for one-year risk of suicide attempts/deaths. Nine of the ten predictor variables from the COBY RC were available in the CDS and used: age, age of mood disorder onset, first and second (partial) degree family history of suicide, history of psychotic symptoms, substance use disorder, prior suicide attempt, socioeconomic status, and non-suicidal self-injury (prospectively, incompletely at baseline). RESULTS Over a mean (SD) follow-up of 19 (10) years, 29 % of the CDS sample attempted suicide. The RC predicted suicide attempts/deaths over one-year follow-up with an area under the receiver operating characteristic curve (AUC) of 0.78 (95 % CI 0.75-0.80). The RC performed slightly better in those with a younger age of mood disorder onset. LIMITATIONS Clinical samples may limit generalizability; the RC does not assess more acute suicide risk. CONCLUSIONS One-year risk of suicide attempts/deaths can be predicted with acceptable accuracy in youth and adults with BD, comparable to commonly used RCs to predict cardiovascular risk. This RC may help identify higher-risk individuals with BD for personalized treatment and research. https://cobysuicideattemptsrc.shinyapps.io/Shiny.
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Affiliation(s)
- Jess G Fiedorowicz
- Departments of Psychiatry and Epidemiology, The University of Ottawa, 75 Laurier Ave. East, Ottawa, ON K1N 6N5, Canada.
| | - John A Merranko
- Department of Psychiatry, Western Psychiatric Hospital, University of Pittsburgh School of Medicine, 3811 O'Hara St., Pittsburgh, PA 15213, USA
| | - Tina R Goldstein
- Department of Psychiatry, Western Psychiatric Hospital, University of Pittsburgh School of Medicine, 3811 O'Hara St., Pittsburgh, PA 15213, USA
| | - Heather Hower
- Department of Psychiatry and Human Behavior, Warren Alpert Medical School of Brown University, Box G-BH, Providence, RI 02912, USA; Department of Health Services, Policy, and Practice, Brown University School of Public Health, 121 South Main Street, Providence, RI 02903, USA; Department of Psychiatry, University of California San Diego, 4510 Executive Drive, Suite 315, San Diego, CA 92121, USA
| | - Satish Iyengar
- Department of Statistics, University of Pittsburgh, 230 S. Bouquet St., Pittsburgh, PA 15213, USA
| | - Danella M Hafeman
- Department of Psychiatry, Western Psychiatric Hospital, University of Pittsburgh School of Medicine, 3811 O'Hara St., Pittsburgh, PA 15213, USA
| | - Jeffrey I Hunt
- Department of Psychiatry and Human Behavior, Warren Alpert Medical School of Brown University, Box G-BH, Providence, RI 02912, USA; Department of Psychiatry, Bradley Hospital, 1011 Veterans Memorial Parkway, East Providence, RI 02915, USA
| | - Michael Strober
- Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Martin B Keller
- Department of Psychiatry and Human Behavior, Warren Alpert Medical School of Brown University, Box G-BH, Providence, RI 02912, USA; Department of Psychiatry, University of Miami, 1120 NW 14(th) St., Miami, FL 33136, USA
| | - Benjamin I Goldstein
- Department of Psychiatry, CAMH, University of Toronto Faculty of Medicine, 2075 Bayview Ave., FG-53, Toronto, ON M4N-3M5, Canada
| | - Rasim S Diler
- Department of Psychiatry, Western Psychiatric Hospital, University of Pittsburgh School of Medicine, 3811 O'Hara St., Pittsburgh, PA 15213, USA
| | - Sara Siddiqi
- Departments of Psychiatry and Epidemiology, The University of Ottawa, 75 Laurier Ave. East, Ottawa, ON K1N 6N5, Canada
| | - Boris Birmaher
- Department of Psychiatry, Western Psychiatric Hospital, University of Pittsburgh School of Medicine, 3811 O'Hara St., Pittsburgh, PA 15213, USA
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13
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Vickers AJ, Lilja H. Eight Misconceptions about Prostate-Specific Antigen. Clin Chem 2024; 70:13-16. [PMID: 38175588 DOI: 10.1093/clinchem/hvad138] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2023] [Accepted: 07/03/2023] [Indexed: 01/05/2024]
Affiliation(s)
- Andrew J Vickers
- Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, United States
| | - Hans Lilja
- Departments of Pathology and Laboratory Medicine, Surgery, and Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, United States
- Department of Translational Medicine, Lund University, Malmö, Sweden
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14
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Bhasin S, Travison TG, Pencina KM, O’Leary M, Cunningham GR, Lincoff AM, Nissen SE, Lucia MS, Preston MA, Khera M, Khan N, Snabes MC, Li X, Tangen CM, Buhr KA, Thompson IM. Prostate Safety Events During Testosterone Replacement Therapy in Men With Hypogonadism: A Randomized Clinical Trial. JAMA Netw Open 2023; 6:e2348692. [PMID: 38150256 PMCID: PMC10753401 DOI: 10.1001/jamanetworkopen.2023.48692] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/01/2023] [Accepted: 11/06/2023] [Indexed: 12/28/2023] Open
Abstract
Importance The effect of testosterone replacement therapy (TRT) on the risk of prostate cancer and other adverse prostate events is unknown. Objective To compare the effect of TRT vs placebo on the incidences of high-grade prostate cancers (Gleason score ≥4 + 3), any prostate cancer, acute urinary retention, invasive prostate procedures, and pharmacologic treatment for lower urinary tract symptoms in men with hypogonadism. Design, Setting, and Participants This placebo-controlled, double-blind randomized clinical trial enrolled 5246 men (aged 45-80 years) from 316 US trial sites who had 2 testosterone concentrations less than 300 ng/dL, hypogonadal symptoms, and cardiovascular disease (CVD) or increased CVD risk. Men with prostate-specific antigen (PSA) concentrations greater than 3.0 ng/mL and International Prostate Symptom Score (IPSS) greater than 19 were excluded. Enrollment took place between May 23, 2018, and February 1, 2022, and end-of-study visits were conducted between May 31, 2022, and January 19, 2023. Intervention Participants were randomized, with stratification for prior CVD, to topical 1.62% testosterone gel or placebo. Main Outcomes and Measures The primary prostate safety end point was the incidence of adjudicated high-grade prostate cancer. Secondary end points included incidence of any adjudicated prostate cancer, acute urinary retention, invasive prostate surgical procedure, prostate biopsy, and new pharmacologic treatment. Intervention effect was analyzed using a discrete-time proportional hazards model. Results A total of 5204 men (mean [SD] age, 63.3 [7.9] years) were analyzed. At baseline, the mean (SD) PSA concentration was 0.92 (0.67) ng/mL, and the mean (SD) IPSS was 7.1 (5.6). The mean (SD) treatment duration as 21.8 (14.2) months in the TRT group and 21.6 (14.0) months in the placebo group. During 14 304 person-years of follow-up, the incidence of high-grade prostate cancer (5 of 2596 [0.19%] in the TRT group vs 3 of 2602 [0.12%] in the placebo group; hazard ratio, 1.62; 95% CI, 0.39-6.77; P = .51) did not differ significantly between groups; the incidences of any prostate cancer, acute urinary retention, invasive surgical procedures, prostate biopsy, and new pharmacologic treatment also did not differ significantly. Change in IPSS did not differ between groups. The PSA concentrations increased more in testosterone-treated than placebo-treated men. Conclusions and Relevance In a population of middle-aged and older men with hypogonadism, carefully evaluated to exclude those at high risk of prostate cancer, the incidences of high-grade or any prostate cancer and other prostate events were low and did not differ significantly between testosterone- and placebo-treated men. The study's findings may facilitate a more informed appraisal of the potential risks of TRT. Trial Registration ClinicalTrials.gov Identifier: NCT03518034.
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Affiliation(s)
- Shalender Bhasin
- Research Program in Men’s Health: Aging and Metabolism, Boston Claude D. Pepper Older Americans Independence Center, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts
| | - Thomas G. Travison
- Marcus Institute for Aging Research, Hebrew Senior Life, Division of Gerontology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts
| | - Karol M. Pencina
- Research Program in Men’s Health: Aging and Metabolism, Boston Claude D. Pepper Older Americans Independence Center, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts
| | - Michael O’Leary
- Research Program in Men’s Health: Aging and Metabolism, Boston Claude D. Pepper Older Americans Independence Center, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts
| | | | - A. Michael Lincoff
- Cleveland Clinic Coordinating Center for Clinical Research (C5Research), Department of Cardiovascular Medicine, Cleveland Clinic, Cleveland, Ohio
| | - Steven E. Nissen
- Cleveland Clinic Coordinating Center for Clinical Research (C5Research), Department of Cardiovascular Medicine, Cleveland Clinic, Cleveland, Ohio
| | | | - Mark A. Preston
- Division of Urology, Brigham and Women’s Hospital, Boston, Massachusetts
| | | | | | | | - Xue Li
- AbbVie Inc, North Chicago, Illinois
| | | | - Kevin A. Buhr
- Statistical Data Analysis Center, Department of Biostatistics and Medical Informatics, University of Wisconsin, Madison
| | - Ian M. Thompson
- CHRISTUS Santa Rosa Health System and The University of Texas Health Science Center, San Antonio
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15
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Tao W, Wang BY, Luo L, Li Q, Meng ZA, Xia TL, Deng WM, Yang M, Zhou J, Zhang X, Gao X, Li LY, He YD. A urine extracellular vesicle lncRNA classifier for high-grade prostate cancer and increased risk of progression: A multi-center study. Cell Rep Med 2023; 4:101240. [PMID: 37852185 PMCID: PMC10591064 DOI: 10.1016/j.xcrm.2023.101240] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2023] [Revised: 07/03/2023] [Accepted: 09/21/2023] [Indexed: 10/20/2023]
Abstract
To construct a urine extracellular vesicle long non-coding RNA (lncRNA) classifier that can detect high-grade prostate cancer (PCa) of grade group 2 or greater and estimate the risk of progression during active surveillance, we identify high-grade PCa-specific lncRNAs by combined analyses of cohorts from TAHSY, TCGA, and the GEO database. We develop and validate a 3-lncRNA diagnostic model (Clnc, being made of AC015987.1, CTD-2589M5.4, RP11-363E6.3) that can detect high-grade PCa. Clnc shows higher accuracy than prostate cancer antigen 3 (PCA3), multiparametric magnetic resonance imaging (mpMRI), and two risk calculators (Prostate Cancer Prevention Trial [PCPT]-RC 2.0 and European Randomized Study of Screening for Prostate Cancer [ERSPC]-RC) in the training cohort (n = 350), two independent cohorts (n = 232; n = 251), and TCGA cohort (n = 499). In the prospective active surveillance cohort (n = 182), Clnc at diagnosis remains a powerful independent predictor for overall active surveillance progression. Thus, Clnc is a potential biomarker for high-grade PCa and can also serve as a biomarker for improved selection of candidates for active surveillance.
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Affiliation(s)
- Wen Tao
- Department of Urology, The Third Affiliated Hospital, Sun Yat-sen University, Guangzhou 510630, China
| | - Bang-Yu Wang
- Department of Anesthesiology, Shanghai General Hospital, Shanghai Jiaotong University School of Medicine, Shanghai 200080, China
| | - Liang Luo
- Department of Urology, The Third Affiliated Hospital, Sun Yat-sen University, Guangzhou 510630, China
| | - Qing Li
- Food and Nutritional Sciences Programme, School of Life Sciences, The Chinese University of Hong Kong, Shatin 999077, Hong Kong
| | - Zhan-Ao Meng
- Department of Radiology, The Third Affiliated Hospital, Sun Yat-sen University, Guangzhou 510630, China
| | - Tao-Lin Xia
- Department of Urology, Foshan First Municipal People's Hospital, Sun Yat-sen University, Foshan 528000, China
| | - Wei-Ming Deng
- Department of Urology, The First Affiliated Hospital, University of South China, Hengyang 421000, China
| | - Ming Yang
- Department of Urology, Foshan Municipal Chinese Medicine Hospital, Foshan 528000, China
| | - Jing Zhou
- Department of Pathology, The Third Affiliated Hospital, Sun Yat-sen University, Guangzhou 510630, China
| | - Xin Zhang
- Department of Pathology, Foshan First Municipal People's Hospital, Sun Yat-sen University, Foshan 528000, China
| | - Xin Gao
- Department of Urology, The Third Affiliated Hospital, Sun Yat-sen University, Guangzhou 510630, China.
| | - Liao-Yuan Li
- Department of Urology, The Third Affiliated Hospital, Sun Yat-sen University, Guangzhou 510630, China.
| | - Ya-Di He
- Health Management Center, The Third Affiliated Hospital, Sun Yat-sen University, Guangzhou 510630, China.
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16
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Presti J, Alexeeff S, Avins AL. Screening for Prostate Cancer. N Engl J Med 2023; 389:93-94. [PMID: 37407016 DOI: 10.1056/nejmc2305651] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 07/07/2023]
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17
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Ferro M, Rocco B, Maggi M, Lucarelli G, Falagario UG, Del Giudice F, Crocetto F, Barone B, La Civita E, Lasorsa F, Brescia A, Catellani M, Busetto GM, Tataru OS, Terracciano D. Beyond blood biomarkers: the role of SelectMDX in clinically significant prostate cancer identification. Expert Rev Mol Diagn 2023; 23:1061-1070. [PMID: 37897252 DOI: 10.1080/14737159.2023.2277366] [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: 07/06/2023] [Accepted: 10/26/2023] [Indexed: 10/30/2023]
Abstract
INTRODUCTION New potential biomarkers to pre-intervention identification of a clinically significant prostate cancer (csPCa) will prevent overdiagnosis and overtreatment and limit quality of life impairment of PCa patients. AREAS COVERED We have developed a comprehensive review focusing our research on the increasing knowledge of the role of SelectMDX® in csPCa detection. Areas identified as clinically relevant are the ability of SelectMDX® to predict csPCa in active surveillance setting, its predictive ability when combined with multiparametric MRI and the role of SelectMDX® in the landscape of urinary biomarkers. EXPERT OPINION Several PCa biomarkers have been developed either alone or in combination with clinical variables to improve csPCa detection. SelectMDX® score includes genomic markers, age, PSA, prostate volume, and digital rectal examination. Several studies have shown consistency in the ability to improve detection of csPCa, avoidance of unnecessary prostate biopsies, helpful in decision-making for clinical benefit of PCa patients with future well designed, and impactful studies.
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Affiliation(s)
- Matteo Ferro
- Department of Urology, IEO - European Institute of Oncology, IRCCS - Istituto di Ricovero e Cura a Carattere Scientifico, via Ripamonti 435, Milan 20141, Italy
| | - Bernardo Rocco
- Unit of Urology, Department of Health Science, University of Milan, ASST Santi Paolo and Carlo, Via A. Di Rudini 8, Milan 20142, Italy
| | - Martina Maggi
- Department of Maternal Infant and Urologic Sciences, Policlinico Umberto I Hospital, Sapienza University of Rome, Piazzale Aldo Moro 5, 00185, Rome, Italy
| | - Giuseppe Lucarelli
- Urology, Andrology and Kidney Transplantation Unit, Department of Emergency and Organ Transplantation, University of Bari, Piazza Umberto I - 70121, Bari, Italy
| | - Ugo Giovanni Falagario
- Department of Urology and Organ Transplantation, University of Foggia, Via A.Gramsci 89/91, 71122 Foggia, Italy
| | - Francesco Del Giudice
- Department of Maternal Infant and Urologic Sciences, Policlinico Umberto I Hospital, Sapienza University of Rome, Piazzale Aldo Moro 5, 00185, Rome, Italy
| | - Felice Crocetto
- Department of Neurosciences and Reproductive Sciences and Odontostomatology, University of Naples Federico II, Via Pansini, 5 - 80131, Naples, Italy
| | - Biagio Barone
- Department of Surgical Sciences, Urology Unit, AORN Sant'Anna e San Sebastiano, Caserta, Via Ferdinando Palasciano, 81100 Caserta , Italy
| | - Evelina La Civita
- Department of Translational Medical Sciences, University of Naples "Federico II", Corso Umberto I 40 - 80138 Naples, Italy
| | - Francesco Lasorsa
- Urology, Andrology and Kidney Transplantation Unit, Department of Emergency and Organ Transplantation, University of Bari, Piazza Umberto I - 70121, Bari, Italy
| | - Antonio Brescia
- Department of Urology, IEO - European Institute of Oncology, IRCCS - Istituto di Ricovero e Cura a Carattere Scientifico, via Ripamonti 435, Milan 20141, Italy
| | - Michele Catellani
- Department of Urology, IEO - European Institute of Oncology, IRCCS - Istituto di Ricovero e Cura a Carattere Scientifico, via Ripamonti 435, Milan 20141, Italy
| | - Gian Maria Busetto
- Department of Urology and Organ Transplantation, University of Foggia, Via A.Gramsci 89/91, 71122 Foggia, Italy
| | - Octavian Sabin Tataru
- Department of Simulation Applied in Medicine, George Emil Palade University of Medicine, Pharmacy, Science and Technology of Târgu Mures, Gh Marinescu 35, 540142 Târgu Mures, Romania
| | - Daniela Terracciano
- Department of Translational Medical Sciences, University of Naples "Federico II", Corso Umberto I 40 - 80138 Naples, Italy
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18
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Han P, Taylor JM, Mukherjee B. Integrating Information from Existing Risk Prediction Models with No Model Details. CAN J STAT 2023; 51:355-374. [PMID: 37346757 PMCID: PMC10281716 DOI: 10.1002/cjs.11701] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2020] [Accepted: 12/16/2021] [Indexed: 11/07/2022]
Abstract
Consider the setting where (i) individual-level data are collected to build a regression model for the association between an event of interest and certain covariates, and (ii) some risk calculators predicting the risk of the event using less detailed covariates are available, possibly as algorithmic black boxes with little information available about how they were built. We propose a general empirical-likelihood-based framework to integrate the rich auxiliary information contained in the calculators into fitting the regression model, to make the estimation of regression parameters more efficient. Two methods are developed, one using working models to extract the calculator information and one making a direct use of calculator predictions without working models. Theoretical and numerical investigations show that the calculator information can substantially reduce the variance of regression parameter estimation. As an application, we study the dependence of the risk of high grade prostate cancer on both conventional risk factors and newly identified molecular biomarkers by integrating information from the Prostate Biopsy Collaborative Group (PBCG) risk calculator, which was built based on conventional risk factors alone.
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Affiliation(s)
- Peisong Han
- Department of Biostatistics, University of Michigan, Ann Arbor, Michigan, USA
| | - Jeremy M.G. Taylor
- Department of Biostatistics, University of Michigan, Ann Arbor, Michigan, USA
| | - Bhramar Mukherjee
- Department of Biostatistics, University of Michigan, Ann Arbor, Michigan, USA
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19
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Patel HD, Koehne EL, Shea SM, Fang AM, Gerena M, Gorbonos A, Quek ML, Flanigan RC, Goldberg A, Rais‐Bahrami S, Gupta GN. A prostate biopsy risk calculator based on MRI: development and comparison of the Prospective Loyola University multiparametric MRI (PLUM) and Prostate Biopsy Collaborative Group (PBCG) risk calculators. BJU Int 2023; 131:227-235. [PMID: 35733400 PMCID: PMC9772358 DOI: 10.1111/bju.15835] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/28/2023]
Abstract
OBJECTIVES To develop and validate a prostate cancer (PCa) risk calculator (RC) incorporating multiparametric magnetic resonance imaging (mpMRI) and to compare its performance with that of the Prostate Biopsy Collaborative Group (PBCG) RC. PATIENTS AND METHODS Men without a PCa diagnosis receiving mpMRI before biopsy in the Prospective Loyola University mpMRI (PLUM) Prostate Biopsy Cohort (2015-2020) were included. Data from a separate institution were used for external validation. The primary outcome was diagnosis of no cancer, grade group (GG)1 PCa, and clinically significant (cs)PCa (≥GG2). Binary logistic regression was used to explore standard clinical and mpMRI variables (prostate volume, Prostate Imaging-Reporting Data System [PI-RADS] version 2.0 lesions) with the final PLUM RC, based on a multinomial logistic regression model. Receiver-operating characteristic curve, calibration curves, and decision-curve analysis were evaluated in the training and validation cohorts. RESULTS A total of 1010 patients were included for development (N = 674 training [47.8% PCa, 30.9% csPCa], N = 336 internal validation) and 371 for external validation. The PLUM RC outperformed the PBCG RC in the training (area under the curve [AUC] 85.9% vs 66.0%; P < 0.001), internal validation (AUC 88.2% vs 67.8%; P < 0.001) and external validation (AUC 83.9% vs 69.4%; P < 0.001) cohorts for csPCa detection. The PBCG RC was prone to overprediction while the PLUM RC was well calibrated. At a threshold probability of 15%, the PLUM RC vs the PBCG RC could avoid 13.8 vs 2.7 biopsies per 100 patients without missing any csPCa. At a cost level of missing 7.5% of csPCa, the PLUM RC could have avoided 41.0% (566/1381) of biopsies compared to 19.1% (264/1381) for the PBCG RC. The PLUM RC compared favourably with the Stanford Prostate Cancer Calculator (SPCC; AUC 84.1% vs 81.1%; P = 0.002) and the MRI-European Randomized Study of Screening for Prostate Cancer (ERSPC) RC (AUC 84.5% vs 82.6%; P = 0.05). CONCLUSIONS The mpMRI-based PLUM RC significantly outperformed the PBCG RC and compared favourably with other mpMRI-based RCs. A large proportion of biopsies could be avoided using the PLUM RC in shared decision making while maintaining optimal detection of csPCa.
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Affiliation(s)
- Hiten D. Patel
- Department of UrologyLoyola University Medical CenterMaywoodILUSA
- Department of UrologyFeinberg School of Medicine, Northwestern UniversityChicagoILUSA
| | | | - Steven M. Shea
- Department of RadiologyLoyola University Medical CenterMaywoodILUSA
| | - Andrew M. Fang
- Department of UrologyUniversity of Alabama at BirminghamBirminghamALUSA
| | - Marielia Gerena
- Department of RadiologyLoyola University Medical CenterMaywoodILUSA
| | - Alex Gorbonos
- Department of UrologyLoyola University Medical CenterMaywoodILUSA
| | - Marcus L. Quek
- Department of UrologyLoyola University Medical CenterMaywoodILUSA
| | | | - Ari Goldberg
- Department of RadiologyLoyola University Medical CenterMaywoodILUSA
| | - Soroush Rais‐Bahrami
- Department of UrologyUniversity of Alabama at BirminghamBirminghamALUSA
- Department of RadiologyUniversity of Alabama at BirminghamBirminghamALUSA
- O'Neal Comprehensive Cancer CenterUniversity of Alabama at BirminghamBirminghamALUSA
| | - Gopal N. Gupta
- Department of UrologyLoyola University Medical CenterMaywoodILUSA
- Department of RadiologyLoyola University Medical CenterMaywoodILUSA
- Department of SurgeryLoyola University Medical CenterMaywoodILUSA
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20
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Harper JB, Greenberg SE, Hunt TC, Cooney KA, O’Neil BB. Initial outcomes and insights from a novel high-risk prostate cancer screening clinic. Prostate 2023; 83:151-157. [PMID: 36207779 PMCID: PMC9772159 DOI: 10.1002/pros.24447] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/31/2022] [Accepted: 09/21/2022] [Indexed: 02/05/2023]
Abstract
INTRODUCTION Guidelines for germline testing in patients with prostate cancer (PCa) are identifying family members who require additional surveillance given pathogenic variants (PVs) that confer increased PCa risk. We established an interdisciplinary clinic for cancer surveillance in high-risk individuals aimed to implement screening recommendations. This study aimed to characterize the clinical features of this cohort. PATIENTS AND METHODS The Prostate Cancer Risk Clinic (PCRC) was established for unaffected individuals with germline PVs or a strong PCa family history. PCa screening, urine labs, and questionnaires were included in the visit. Individuals with BRCA1/2 PVs underwent clinical breast exam as well. Data from the initial visit were abstracted from the medical record and questionnaires for analysis. RESULTS Thirty-five individuals with increased PCa risk were followed by the PCRC with a median age of 47 years of age. Twenty individuals (57%) had a family history of PCa, and 34 (97%) had a germline PV associated with an increased risk for developing PCa. Four individuals underwent biopsy due to care in the PCRC, with one PCa identified in an individual with TP53 PV. Median patient response scores indicated mild symptoms of an enlarged prostate (AUASS), normal erectile function (SHIM), and relatively low anxiety about developing PCa (MAX-PC). However, there were notable "outlier" scores on each questionnaire. CONCLUSIONS Individuals with prostates and BRCA1/2 PVs, among other germline PVs, can benefit from a comprehensive interdisciplinary approach to high-risk management. PCa was identified in an individual with a non-BRCA PV, emphasizing the importance and need for high-risk screening guidelines across all genes with increased risk for PCa. "Outlier" patient response scores demonstrate that some participants experienced worse symptoms or anxiety than was indicated by median scores alone.
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Affiliation(s)
- Jonathan B. Harper
- Division of Urology, Department of Surgery, Huntsman Cancer Institute, University of Utah, Salt Lake City, UT, USA
| | - Samantha E. Greenberg
- Genetic Counseling Shared Resource, Huntsman Cancer Institute, University of Utah, Salt Lake City, UT, USA
- Corresponding author: Huntsman Cancer Institute, 2000 Circle of Hope, Salt Lake City, UT 84112, USA, Tel. +1-801-213-5774; Fax: +1-801-585-5763, (S.E. Greenberg)
| | - Trevor C. Hunt
- Division of Urology, Department of Surgery, Huntsman Cancer Institute, University of Utah, Salt Lake City, UT, USA
- University of Rochester Medical Center, Department of Urology, Rochester, NY, USA
| | - Kathleen A. Cooney
- Department of Medicine, Duke University School of Medicine, and the Duke Cancer Institute, Durham, NC, USA
| | - Brock B. O’Neil
- Division of Urology, Department of Surgery, Huntsman Cancer Institute, University of Utah, Salt Lake City, UT, USA
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21
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Wang C, Yuan L, Shen D, Zhang B, Wu B, Zhang P, Xiao J, Tao T. Combination of PI-RADS score and PSAD can improve the diagnostic accuracy of prostate cancer and reduce unnecessary prostate biopsies. Front Oncol 2022; 12:1024204. [PMID: 36465344 PMCID: PMC9709422 DOI: 10.3389/fonc.2022.1024204] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2022] [Accepted: 10/20/2022] [Indexed: 09/27/2023] Open
Abstract
OBJECTIVES The purpose of this study is to evaluate the diagnostic accuracy of the clinical variables of patients with prostate cancer (PCa) and to provide a strategy to reduce unnecessary biopsies. PATIENTS AND METHODS A Chinese cohort that consists of 833 consecutive patients who underwent prostate biopsies from January 2018 to April 2022 was collected in this retrospective study. Diagnostic ability for total PCa and clinically significant PCa (csPCa) was evaluated by prostate imaging-reporting and data system (PI-RADS) score and other clinical variables. Univariate and multivariable logistic regression analyses were performed to figure out the independent predictors. Diagnostic accuracy was estimated by plotting receiver operating characteristic curves. RESULTS The results of univariate and multivariable analyses demonstrated that the PI-RADS score (P < 0.001, OR: 5.724, 95% CI: 4.517-7.253)/(P < 0.001, OR: 5.199, 95% CI: 4.039-6.488) and prostate-specific antigen density (PSAD) (P < 0.001, OR: 2.756, 95% CI: 1.560-4.870)/(P < 0.001, OR: 4.726, 95% CI: 2.661-8.396) were the independent clinical factors for predicting total PCa/csPCa. The combination of the PI-RADS score and PSAD presented the best diagnostic performance for the detection of PCa and csPCa. For the diagnostic criterion of "PI-RADS score ≥ 3 or PSAD ≥ 0.3", the sensitivity and negative predictive values were 94.0% and 93.1% for the diagnosis of total PCa and 99.2% and 99.3% for the diagnosis of csPCa, respectively. For the diagnostic criterion "PI-RADS score >3 and PSAD ≥ 0.3", the specificity and positive predictive values were 96.8% and 92.6% for the diagnosis of total PCa and 93.5% and 82.4% for the diagnosis of csPCa, respectively. CONCLUSIONS The combination of the PI-RADS score and PSAD can implement the extraordinary diagnostic performance of PCa. Many patients may safely execute active surveillance or take systematic treatment without prostate biopsies by stratification according to the PI-RADS score and the value of PSAD.
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Affiliation(s)
- Changming Wang
- Department of Urology, The First Affiliated Hospital of USTC of China, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China
| | - Lei Yuan
- Department of Radiology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China
| | - Deyun Shen
- Department of Urology, The First Affiliated Hospital of USTC of China, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China
| | - Bin Zhang
- Department of Urology, Affiliated Anhui Provincial Hospital of Anhui Medical University, Hefei, China
| | - Baorui Wu
- Department of Urology, The First Affiliated Hospital of USTC of China, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China
| | - Panrui Zhang
- Hefei National Laboratory for Physical Sciences at Microscale, The CAS Key Laboratory of Innate Immunity and Chronic Disease, School of Basic Medical Sciences, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China
| | - Jun Xiao
- Department of Urology, The First Affiliated Hospital of USTC of China, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China
- Department of Urology, Affiliated Anhui Provincial Hospital of Anhui Medical University, Hefei, China
| | - Tao Tao
- Department of Urology, The First Affiliated Hospital of USTC of China, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China
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22
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Pfeiffer RM, Chen Y, Gail MH, Ankerst DP. Accommodating population differences when validating risk prediction models. Stat Med 2022; 41:4756-4780. [PMID: 36224712 PMCID: PMC10510530 DOI: 10.1002/sim.9447] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2021] [Revised: 01/19/2022] [Accepted: 05/11/2022] [Indexed: 11/11/2022]
Abstract
Validation of risk prediction models in independent data provides a more rigorous assessment of model performance than internal assessment, for example, done by cross-validation in the data used for model development. However, several differences between the populations that gave rise to the training and the validation data can lead to seemingly poor performance of a risk model. In this paper we formalize the notions of "similarity" or "relatedness" of the training and validation data, and define reproducibility and transportability. We address the impact of different distributions of model predictors and differences in verifying the disease status or outcome on measures of calibration, accuracy and discrimination of a model. When individual level information from both the training and validation data sets is available, we propose and study weighted versions of the validation metrics that adjust for differences in the risk factor distributions and in outcome verification between the training and validation data to provide a more comprehensive assessment of model performance. We provide conditions on the risk model and the populations that gave rise to the training and validation data that ensure a model's reproducibility or transportability, and show how to check these conditions using weighted and unweighted performance measures. We illustrate the method by developing and validating a model that predicts the risk of developing prostate cancer using data from two large prostate cancer screening trials.
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Affiliation(s)
| | - Yiyao Chen
- Technical University of Munich, Garching, Germany
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23
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Van Poppel H, Albreht T, Basu P, Hogenhout R, Collen S, Roobol M. Serum PSA-based early detection of prostate cancer in Europe and globally: past, present and future. Nat Rev Urol 2022; 19:562-572. [PMID: 35974245 DOI: 10.1038/s41585-022-00638-6] [Citation(s) in RCA: 62] [Impact Index Per Article: 31.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/14/2022] [Indexed: 12/14/2022]
Abstract
In the pre-PSA-detection era, a large proportion of men were diagnosed with metastatic prostate cancer and died of the disease; after the introduction of the serum PSA test, randomized controlled prostate cancer screening trials in the USA and Europe were conducted to assess the effect of PSA screening on prostate cancer mortality. Contradictory outcomes of the trials and the accompanying overdiagnosis resulted in recommendations against prostate cancer screening by organizations such as the United States Preventive Services Task Force. These recommendations were followed by a decline in PSA testing and a rise in late-stage diagnosis and prostate cancer mortality. Re-evaluation of the randomized trials, which accounted for contamination, showed that PSA-based screening does indeed reduce prostate cancer mortality; however, the debate about whether to screen or not to screen continues because of the considerable overdiagnosis that occurs using PSA-based screening. Meanwhile, awareness among the population of prostate cancer as a potentially lethal disease stimulates opportunistic screening practices that further increase overdiagnosis without the benefit of mortality reduction. However, in the past decade, new screening tools have been developed that make the classic PSA-only-based screening an outdated strategy. With improved use of PSA, in combination with age, prostate volume and with the application of prostate cancer risk calculators, a risk-adapted strategy enables improved stratification of men with prostate cancer and avoidance of unnecessary diagnostic procedures. This combination used with advanced detection techniques (such as MRI and targeted biopsy), can reduce overdiagnosis. Moreover, new biomarkers are becoming available and will enable further improvements in risk stratification.
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Affiliation(s)
| | - Tit Albreht
- National Institute of Public Health, Ljubljana, Slovenia
- Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
| | - Partha Basu
- International Agency for Research on Cancer, Lyon, France
| | - Renée Hogenhout
- Erasmus University Medical Center, Cancer Institute, Rotterdam, Netherlands
| | - Sarah Collen
- European Association of Urology, Arnhem, Netherlands
| | - Monique Roobol
- Erasmus University Medical Center, Cancer Institute, Rotterdam, Netherlands
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24
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Neumair M, Kattan MW, Freedland SJ, Haese A, Guerrios-Rivera L, De Hoedt AM, Liss MA, Leach RJ, Boorjian SA, Cooperberg MR, Poyet C, Saba K, Herkommer K, Meissner VH, Vickers AJ, Ankerst DP. Accommodating heterogeneous missing data patterns for prostate cancer risk prediction. BMC Med Res Methodol 2022; 22:200. [PMID: 35864460 PMCID: PMC9306143 DOI: 10.1186/s12874-022-01674-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2021] [Accepted: 07/04/2022] [Indexed: 12/30/2022] Open
Abstract
BACKGROUND We compared six commonly used logistic regression methods for accommodating missing risk factor data from multiple heterogeneous cohorts, in which some cohorts do not collect some risk factors at all, and developed an online risk prediction tool that accommodates missing risk factors from the end-user. METHODS Ten North American and European cohorts from the Prostate Biopsy Collaborative Group (PBCG) were used for fitting a risk prediction tool for clinically significant prostate cancer, defined as Gleason grade group ≥ 2 on standard TRUS prostate biopsy. One large European PBCG cohort was withheld for external validation, where calibration-in-the-large (CIL), calibration curves, and area-underneath-the-receiver-operating characteristic curve (AUC) were evaluated. Ten-fold leave-one-cohort-internal validation further validated the optimal missing data approach. RESULTS Among 12,703 biopsies from 10 training cohorts, 3,597 (28%) had clinically significant prostate cancer, compared to 1,757 of 5,540 (32%) in the external validation cohort. In external validation, the available cases method that pooled individual patient data containing all risk factors input by an end-user had best CIL, under-predicting risks as percentages by 2.9% on average, and obtained an AUC of 75.7%. Imputation had the worst CIL (-13.3%). The available cases method was further validated as optimal in internal cross-validation and thus used for development of an online risk tool. For end-users of the risk tool, two risk factors were mandatory: serum prostate-specific antigen (PSA) and age, and ten were optional: digital rectal exam, prostate volume, prior negative biopsy, 5-alpha-reductase-inhibitor use, prior PSA screen, African ancestry, Hispanic ethnicity, first-degree prostate-, breast-, and second-degree prostate-cancer family history. CONCLUSION Developers of clinical risk prediction tools should optimize use of available data and sources even in the presence of high amounts of missing data and offer options for users with missing risk factors.
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Affiliation(s)
- Matthias Neumair
- grid.6936.a0000000123222966Department of Life Sciences, Technical University of Munich, Freising, Germany
| | - Michael W. Kattan
- grid.239578.20000 0001 0675 4725Department of Quantitative Health Sciences, Cleveland Clinic Foundation, Cleveland, OH USA
| | - Stephen J. Freedland
- Section of Urology, Durham Veterans Administration Health Care System, Durham, NC USA ,grid.50956.3f0000 0001 2152 9905Department of Surgery, Cedars-Sinai Medical Center, Los Angeles, CA USA
| | - Alexander Haese
- grid.13648.380000 0001 2180 3484Martini-Clinic Prostate Cancer Center, University Clinic Eppendorf, Hamburg, Germany
| | - Lourdes Guerrios-Rivera
- grid.509403.b0000 0004 0420 4000Department of Surgery, Urology Section, Veterans Affairs Caribbean Healthcare System, San Juan, Puerto Rico
| | - Amanda M. De Hoedt
- Section of Urology, Durham Veterans Administration Health Care System, Durham, NC USA
| | - Michael A. Liss
- grid.267309.90000 0001 0629 5880Department of Urology, University of Texas Health at San Antonio, San Antonio, TX USA
| | - Robin J. Leach
- grid.267309.90000 0001 0629 5880Department of Cell Systems and Anatomy, University of Texas Health at San Antonio, San Antonio, TX USA
| | - Stephen A. Boorjian
- grid.66875.3a0000 0004 0459 167XDepartment of Urology, Mayo Clinic, Rochester, MN USA
| | - Matthew R. Cooperberg
- grid.266102.10000 0001 2297 6811Departments of Urology and Epidemiology & Biostatistics, University of California San Francisco, San Francisco, CA USA
| | - Cedric Poyet
- grid.7400.30000 0004 1937 0650Department of Urology, University Hospital of Zurich, University of Zurich, Zurich, Switzerland
| | - Karim Saba
- grid.7400.30000 0004 1937 0650Department of Urology, University Hospital of Zurich, University of Zurich, Zurich, Switzerland ,grid.483344.c0000000406274213Urology Centre, Hirslanden Klinik Aarau, Aarau, Switzerland
| | - Kathleen Herkommer
- Department of Urology, University Hospital, Technical University of Munich, Munich, Germany
| | - Valentin H. Meissner
- Department of Urology, University Hospital, Technical University of Munich, Munich, Germany
| | - Andrew J. Vickers
- grid.51462.340000 0001 2171 9952Department of Epidemiology & Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY USA
| | - Donna P. Ankerst
- grid.6936.a0000000123222966Department of Life Sciences, Technical University of Munich, Freising, Germany ,grid.6936.a0000000123222966Department of Mathematics, Technical University of Munich, Boltzmannstrasse 3, Garching, Germany
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25
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Wang G, Choi KS, Teoh JYC, Lu J. Deep Cross-Output Knowledge Transfer Using Stacked-Structure Least-Squares Support Vector Machines. IEEE TRANSACTIONS ON CYBERNETICS 2022; 52:3207-3220. [PMID: 32780705 DOI: 10.1109/tcyb.2020.3008963] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
This article presents a new deep cross-output knowledge transfer approach based on least-squares support vector machines, called DCOT-LS-SVMs. Its aim is to improve the generalizability of least-squares support vector machines (LS-SVMs) while avoiding the complicated parameter tuning process that occurs in many kernel machines. The proposed approach has two significant characteristics: 1) DCOT-LS-SVMs is inspired by a stacked hierarchical architecture that combines several layer-by-layer LS-SVMs modules. The module that forms the higher layer has additional input features that consider the predictions from all previous modules and 2) cross-output knowledge transfer is used to leverage knowledge from the predictions of the previous module to improve the learning process in the current module. With this approach, the model's parameters, such as a tradeoff parameter C and a kernel width δ , can be randomly assigned to each module in order to greatly simplify the learning process. Moreover, DCOT-LS-SVMs is able to autonomously and quickly decide the extent of the cross-output knowledge transfer between adjacent modules through a fast leave-one-out cross-validation strategy. In addition, we present an imbalanced version of DCOT-LS-SVMs, called IDCOT-LS-SVMs, given that imbalanced datasets are common in real-world scenarios. The effectiveness of the proposed approaches is demonstrated through a comparison with five comparative methods on UCI datasets and with a case study on the diagnosis of prostate cancer.
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Mason RJ, Marzouk K, Finelli A, Saad F, So AI, Violette PD, Breau RH, Rendon RA. UPDATE - 2022 Canadian Urological Association recommendations on prostate cancer screening and early diagnosis Endorsement of the 2021 Cancer Care Ontario guidelines on prostate multiparametric magnetic resonance imaging. Can Urol Assoc J 2022; 16:E184-E196. [PMID: 35358414 PMCID: PMC9054332 DOI: 10.5489/cuaj.7851] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
Affiliation(s)
- Ross J. Mason
- Department of Urology, Dalhousie University, Halifax, NS, Canada
| | - Karim Marzouk
- Windsor General Hospital, Windsor, ON; and Western University, London, ON, Canada
| | - Antonio Finelli
- Division of Urology, University of Toronto, Toronto, ON, Canada
| | - Fred Saad
- Department of Surgery (Urology), University of Montreal, Montreal, QC, Canada
| | - Alan I. So
- Department of Urologic Sciences, University of British Columbia, Vancouver, BC, Canada
| | - Philippe D. Violette
- Department of Surgery, Western University, London, ON, Canada
- Departments of Surgery and Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON, Canada
| | - Rodney H. Breau
- Division of Urology, University of Ottawa, Ottawa, ON, Canada
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Hayes FJ. Monitoring of Testosterone Replacement Therapy to Optimize the Benefit-to-Risk Ratio. Endocrinol Metab Clin North Am 2022; 51:99-108. [PMID: 35216723 DOI: 10.1016/j.ecl.2021.11.013] [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] [Indexed: 11/17/2022]
Abstract
For hypogonadal men treated with testosterone, the goal is to ensure that benefits are optimized, risks are minimized, and any adverse effects are identified early and managed appropriately. This can best be achieved by careful patient selection, excluding men with contraindications and addressing any modifiable risk factors in those at increased risk. A standardized plan should be used for monitoring that includes evaluation of symptoms, side effects, adherence, and measurement of testosterone and hematocrit. Shared decision making should be used to determine whether to screen for prostate cancer and informed by age, baseline cancer risk, and patient preference.
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Affiliation(s)
- Frances J Hayes
- Reproductive Endocrine Unit, BHX5, Harvard Medical School, Massachusetts General Hospital, 55 Fruit Street, Boston, MA 02114, USA.
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Kinnaird A, Brisbane W, Kwan L, Priester A, Chuang R, Barsa DE, Delfin M, Sisk A, Margolis D, Felker E, Hu J, Marks LS. A prostate cancer risk calculator: Use of clinical and magnetic resonance imaging data to predict biopsy outcome in North American men. Can Urol Assoc J 2022; 16:E161-E166. [PMID: 34672937 PMCID: PMC8923894 DOI: 10.5489/cuaj.7380] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
Abstract
INTRODUCTION A functional tool to optimize patient selection for magnetic resonance imaging (MRI)-guided prostate biopsy (MRGB) is an unmet clinical need. We sought to develop a prostate cancer risk calculator (PCRC-MRI) that combines MRI and clinical characteristics to aid decision-making for MRGB in North American men. METHODS Two prospective registries containing 2354 consecutive men undergoing MRGB (September 2009 to April 2019) were analyzed. Patients were randomized into five groups, with one group randomly assigned to be the validation cohort against the other four groups as the discovery cohort. The primary outcome was detection of clinically significant prostate cancer (csPCa) defined as Gleason grade group ≥2. Variables included age, ethnicity, digital rectal exam (DRE), prior biopsy, prostate-specific antigen (PSA), prostate volume, PSA density, and MRI score. Odds ratios (OR) were calculated from multivariate logistic regression comparing two models: one with clinical variables only (clinical) against a second combining clinical variables with MRI data (clinical+MRI). RESULTS csPCa was present in 942 (40%) of the 2354 men available for study. The positive and negative predictive values for csPCa in the clinical+MRI model were 57% and 89%, respectively. The area under the curve of the clinical+MRI model was superior to the clinical model in discovery (0.843 vs. 0.707, p<0.0001) and validation (0.888 vs. 0.757, p<0.0001) cohorts. Use of PCRC-MRI would have avoided approximately 16 unnecessary biopsies in every 100 men. Of all variables examined, Asian ethnicity was the most protective factor (OR 0.46, 0.29-0.75) while MRI score 5 indicated greatest risk (OR15.8, 10.5-23.9). CONCLUSIONS A risk calculator (PCRC-MRI), based on a large North American cohort, is shown to improve patient selection for MRGB, especially in preventing unnecessary biopsies. This tool is available at https://www.uclahealth.org/urology/prostate-cancer-riskcalculator and may help rationalize biopsy decision-making.
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Affiliation(s)
- Adam Kinnaird
- Department of Urology, David Geffen School of Medicine, UCLA, Los Angeles, CA, United States
- Division of Urology, Department of Surgery, University of Alberta, Edmonton, AB, Canada
| | - Wayne Brisbane
- Department of Urology, David Geffen School of Medicine, UCLA, Los Angeles, CA, United States
| | - Lorna Kwan
- Department of Urology, David Geffen School of Medicine, UCLA, Los Angeles, CA, United States
| | - Alan Priester
- Department of Bioengineering, UCLA, Los Angeles, CA, United States
| | - Ryan Chuang
- Department of Urology, David Geffen School of Medicine, UCLA, Los Angeles, CA, United States
| | - Danielle E. Barsa
- Department of Urology, David Geffen School of Medicine, UCLA, Los Angeles, CA, United States
| | - Merdie Delfin
- Department of Urology, David Geffen School of Medicine, UCLA, Los Angeles, CA, United States
| | - Anthony Sisk
- Department of Pathology & Laboratory Medicine, UCLA, Los Angeles, CA, United States
| | - Daniel Margolis
- Department of Radiology, Weill Cornell Medical College, New York, NY, United States
| | - Ely Felker
- Department of Radiological Sciences, UCLA, Los Angeles, CA, United States
| | - Jim Hu
- Department of Urology, Weill Cornell Medical College, New York, NY, United States
| | - Leonard S. Marks
- Department of Urology, David Geffen School of Medicine, UCLA, Los Angeles, CA, United States
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Jethwani DL, Sivamoorthy LL, Toh CC, Malek R. Predicting the diagnosis of prostate cancer with a scoring system based on novel biomarkers. BMC Urol 2022; 22:13. [PMID: 35109827 PMCID: PMC8808971 DOI: 10.1186/s12894-022-00956-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2021] [Accepted: 01/12/2022] [Indexed: 01/04/2023] Open
Abstract
Objective To predict prostate cancer using novel biomarker ratios and create a predictive scoring system. Materials and methods Data of a total of 703 patients who consulted Urology Department of Selayang Hospital between January 2013 and December 2017 and underwent prostate biopsy were screened retrospectively. Prostate specific antigen (PSA) levels, prostate volumes (PV), neutrophil and lymphocyte counts, neutrophil-to-lymphocyte ratio (NLR), Prostate specific antigen density (PSAD) and histopathology were evaluated. Results Ages ranged from 43 to 89 years, divided into 2 groups as per biopsy results; positive for prostate cancer (n = 290, 41.3%) and negative for malignancy (n = 413; 58.7%). Intergroup comparative evaluations were performed. Independent variables with p < 0.001 in the univariate analysis were age, DRE, PV, NLR, PSAD. A scoring system was modelled using NLR < 0.9, PSAD > 0.4, Age > 70 and DRE. A score of 2 or more predicted prostate cancer with a Sensitivity of 83.8% and Specificity of 86.4%. Conclusions NLR is shown to be good predictor for prostate cancer its usage in this scoring system affords more disease specificity as compared to PSA alone.
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Affiliation(s)
| | | | - Charng Chee Toh
- Department of Urology, Hospital Selayang, Batu Caves, Selangor, Malaysia
| | - Rohan Malek
- Department of Urology, Hospital Selayang, Batu Caves, Selangor, Malaysia
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Fang AM, Rais-Bahrami S. Magnetic resonance imaging-based risk calculators optimize selection for prostate biopsy among biopsy-naive men. Cancer 2022; 128:25-27. [PMID: 34427940 DOI: 10.1002/cncr.33872] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2021] [Accepted: 08/05/2021] [Indexed: 11/08/2022]
Affiliation(s)
- Andrew M Fang
- Department of Urology, University of Alabama at Birmingham, Birmingham, Alabama
| | - Soroush Rais-Bahrami
- Department of Urology, University of Alabama at Birmingham, Birmingham, Alabama.,Department of Radiology, University of Alabama at Birmingham, Birmingham, Alabama.,O'Neal Comprehensive Cancer Center, University of Alabama at Birmingham, Birmingham, Alabama
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Personalized 5-Year Prostate Cancer Risk Prediction Model in Korea Based on Nationwide Representative Data. J Pers Med 2021; 12:jpm12010002. [PMID: 35055319 PMCID: PMC8780119 DOI: 10.3390/jpm12010002] [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: 11/03/2021] [Revised: 12/09/2021] [Accepted: 12/16/2021] [Indexed: 11/16/2022] Open
Abstract
Prostate cancer is the fourth most common cause of cancer in men in Korea, and there has been a rapid increase in cases. In the present study, we constructed a risk prediction model for prostate cancer using representative data from Korea. Participants who completed health examinations in 2009, based on the Korean National Health Insurance database, were eligible for the present study. The crude and adjusted risks were explored with backward selection using the Cox proportional hazards model to identify possible risk variables. Risk scores were assigned based on the adjusted hazard ratios, and the standardized points for each risk factor were proportional to the β-coefficient. Model discrimination was assessed using the concordance statistic (c-statistic), and calibration ability was assessed by plotting the mean predicted probability against the mean observed probability of prostate cancer. Among the candidate predictors, age, smoking intensity, body mass index, regular exercise, presence of type 2 diabetes mellitus, and hypertension were included. Our risk prediction model showed good discrimination (c-statistic: 0.826, 95% confidence interval: 0.821-0.832). The relationship between model predictions and actual prostate cancer development showed good correlation in the calibration plot. Our prediction model for individualized prostate cancer risk in Korean men showed good performance. Using easily accessible and modifiable risk factors, this model can help individuals make decisions regarding prostate cancer screening.
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Fiedorowicz JG, Merranko JA, Iyengar S, Hower H, Gill MK, Yen S, Goldstein TR, Strober M, Hafeman D, Keller MB, Goldstein BI, Diler RS, Hunt JI, Birmaher BB. Validation of the youth mood recurrences risk calculator in an adult sample with bipolar disorder. J Affect Disord 2021; 295:1482-1488. [PMID: 34563392 DOI: 10.1016/j.jad.2021.09.037] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/04/2021] [Revised: 08/12/2021] [Accepted: 09/12/2021] [Indexed: 10/20/2022]
Abstract
BACKGROUND The ability to predict an individual's risk of mood episode recurrence can facilitate personalized medicine in bipolar disorder (BD). We sought to externally validate, in an adult sample, a risk calculator of mood episode recurrence developed in youth/young adults with BD from the Course and Outcome of Bipolar Youth (COBY) study. METHODS Adult participants from the National Institute of Mental Health Collaborative Depression Study (CDS; N=258; mean(SD) age=35.5(12.0) years; mean follow-up=24.9 years) were utilized as a sample to validate the youth COBY risk calculator for onset of depressive, manic, or any mood episodes. RESULTS In this older validation sample, the risk calculator predicted recurrence of any episode over 1, 2, 3, or 5-year follow-up intervals, with Area Under the Curves (AUCs) approximating 0.77. The AUC for prediction of depressive episodes was about 0.81 for each of the time windows, which was higher than for manic or hypomanic episodes (AUC=0.72). While the risk calculator was well-calibrated across the range of risk scores, it systematically underestimated risk in the CDS sample by about 20%. The length of current remission was a highly significant predictor of recurrence risk in the CDS sample. LIMITATIONS Predominantly self-reported White samples may limit generalizability; the risk calculator does not assess more proximal risk (e.g., 1 month). CONCLUSIONS Risk of mood episode recurrence can be predicted with good accuracy in youth and adults with BD in remission. The risk calculators may help identify higher risk BD subgroups for treatment and research.
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Affiliation(s)
- Jess G Fiedorowicz
- The Ottawa Hospital, Ottawa Hospital Research Institute, Department of Psychiatry, School of Public Health and Epidemiology, Brain and Mind Research Institute, University of Ottawa, 75 Laurier Ave. East, Ottawa, ON K1N 6N5, Canada.
| | - John A Merranko
- Department of Psychiatry, Western Psychiatric Hospital, School of Medicine, University of Pittsburgh, 3811 O'Hara St., Pittsburgh, PA 15213, USA
| | - Satish Iyengar
- Department of Statistics, University of Pittsburgh, 230 S. Bouquet St., Pittsburgh, PA 15213, USA
| | - Heather Hower
- Department of Psychiatry and Human Behavior, Warren Alpert Medical School of Brown University, Box G-BH, Providence, RI 02912, USA; Department of Health Services, Policy and Practice, Brown University School of Public Health, 121 South Main Street, Providence, RI 02903, USA; Department of Psychiatry, University of California San Diego, 4510 Executive Drive, Suite 315, San Diego, CA 92121, USA
| | - Mary Kay Gill
- Department of Psychiatry, Western Psychiatric Hospital, School of Medicine, University of Pittsburgh, 3811 O'Hara St., Pittsburgh, PA 15213, USA
| | - Shirley Yen
- Departments of Psychiatry, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA 02115, USA
| | - Tina R Goldstein
- Department of Psychiatry, Western Psychiatric Hospital, School of Medicine, University of Pittsburgh, 3811 O'Hara St., Pittsburgh, PA 15213, USA
| | - Michael Strober
- Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Danella Hafeman
- Department of Psychiatry, Western Psychiatric Hospital, School of Medicine, University of Pittsburgh, 3811 O'Hara St., Pittsburgh, PA 15213, USA
| | - Martin B Keller
- Department of Psychiatry and Human Behavior, Warren Alpert Medical School of Brown University, Box G-BH, Providence, RI 02912, USA; Department of Psychiatry, University of Miami, 1120 NW 14th St., Miami, FL 33136, USA
| | - Benjamin I Goldstein
- Department of Psychiatry, Sunnybrook Health Sciences Centre, University of Toronto Faculty of Medicine, 2075 Bayview Ave., FG-53, Toronto, ON M4N 3M5, Canada
| | - Rasim S Diler
- Department of Psychiatry, Western Psychiatric Hospital, School of Medicine, University of Pittsburgh, 3811 O'Hara St., Pittsburgh, PA 15213, USA
| | - Jeffrey I Hunt
- Department of Psychiatry and Human Behavior, Warren Alpert Medical School of Brown University, Box G-BH, Providence, RI 02912, USA; Department of Psychiatry, Bradley Hospital, 1011 Veterans Memorial Parkway, East Providence, RI 02915, USA
| | - Boris B Birmaher
- Department of Psychiatry, Western Psychiatric Hospital, School of Medicine, University of Pittsburgh, 3811 O'Hara St., Pittsburgh, PA 15213, USA
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Yıldızhan M, Balcı M, Eroğlu U, Asil E, Coser S, Özercan AY, Köseoğlu B, Güzel O, Asfuroğlu A, Tuncel A. An analysis of three different prostate cancer risk calculators applied prior to prostate biopsy: A Turkish cohort validation study. Andrologia 2021; 54:e14329. [PMID: 34837424 DOI: 10.1111/and.14329] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2021] [Revised: 11/13/2021] [Accepted: 11/14/2021] [Indexed: 10/19/2022] Open
Abstract
The study aimed to investigate the best-performing of three risk calculators (RCs) for the Turkish population in predicting cancer-free status and high-risk prostate cancer (PCa) in patients undergoing transrectal ultrasound-guided prostate biopsy. The electronic medical records of 527 patients who underwent prostate biopsy for the first time due to PSA of 0.3-50 ng/dl and/or cancer suspicion at digital rectal examination (DRE) between January 2017 and December 2020 were retrieved retrospectively. The predictive power of the RCs in the biopsy and the surgical cohort was calculated by two urologists using European Randomised Study of Screening for Prostate Cancer (ERSPC) RC, the North American Prostate Cancer Prevention Trial-RC (PCPT-RC), and the Prostate Biopsy Collaborative Group (PBCG)-RC. All three RCs were successful in predicting PCa and high-risk disease at ROC analysis (p < 0.0001). Of these three nomograms, PBCG-RC outperformed PCPT-RC 2.0 and ERSPC-RH in predicting benign pathology outcomes at biopsy. A better performance of PBCG-RC was also observed in terms of prediction of high-risk disease at biopsy. Using any of the available RCs prior to biopsy is of greater assistance to prostate-specific antigen and DRE than examination alone. The study results show that PBCG-RC performed before biopsy has a higher predictive power than the other two RCs.
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Affiliation(s)
| | - Melih Balcı
- Department of Urology, Ankara City Hospital, Ankara, Turkey
| | - Unsal Eroğlu
- Department of Urology, Ankara City Hospital, Ankara, Turkey
| | - Erem Asil
- Department of Urology, Ankara City Hospital, Ankara, Turkey
| | - Seref Coser
- Department of Urology, Ankara City Hospital, Ankara, Turkey
| | | | - Burak Köseoğlu
- Department of Urology, Ankara City Hospital, Ankara, Turkey
| | - Ozer Güzel
- Department of Urology, Ankara City Hospital, Ankara, Turkey
| | - Ahmet Asfuroğlu
- Department of Urology, Ankara Etimesgut State Hospital, Ankara, Turkey
| | - Altuğ Tuncel
- Department of Urology affiliated with Ankara City Hospital, Faculty of Medicine, University of Health Sciences, Ankara, Turkey
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Chang EK, Gadzinski AJ, Nyame YA. Blood and urine biomarkers in prostate cancer: Are we ready for reflex testing in men with an elevated prostate-specific antigen? Asian J Urol 2021; 8:343-353. [PMID: 34765442 PMCID: PMC8566358 DOI: 10.1016/j.ajur.2021.06.003] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2021] [Revised: 05/17/2021] [Accepted: 05/26/2021] [Indexed: 10/28/2022] Open
Abstract
Objective There is no consensus on the role of biomarkers in determining the utility of prostate biopsy in men with elevated prostate-specific antigen (PSA). There are numerous biomarkers such as prostate health index, 4Kscore, prostate cancer antigen 3, ExoDX, SelectMDx, and Mi-Prostate Score that may be useful in this decision-making process. However, it is unclear whether any of these tests are accurate and cost-effective enough to warrant being a widespread reflex test following an elevated PSA. Our goal was to report on the clinical utility of these blood and urine biomarkers in prostate cancer screening. Methods We performed a systematic review of studies published between January 2000 and October 2020 to report the available parameters and cost-effectiveness of the aforementioned diagnostic tests. We focus on the negative predictive value, the area under the curve, and the decision curve analysis in comparing reflexive tests due to their relevance in evaluating diagnostic screening tests. Results Overall, the biomarkers are roughly equivalent in predictive accuracy. Each test has additional clinical utility to the current diagnostic standard of care, but the added benefit is not substantial to justify using the test reflexively after an elevated PSA. Conclusions Our findings suggest these biomarkers should not be used in binary fashion and should be understood in the context of pre-existing risk predictors, patient's ethnicity, cost of the test, patient life-expectancy, and patient goals. There are more recent diagnostic tools such as multi-parametric magnetic resonance imaging, polygenic single-nucleotide panels, IsoPSA, and miR Sentinel tests that are promising in the realm of prostate cancer screening and need to be investigated further to be considered a consensus reflexive test in the setting of prostate cancer screening.
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Affiliation(s)
- Edward K Chang
- Department of Urology, University of Washington Medical Center, Seattle, WA, USA
| | - Adam J Gadzinski
- Department of Urology, University of Washington Medical Center, Seattle, WA, USA
| | - Yaw A Nyame
- Department of Urology, University of Washington Medical Center, Seattle, WA, USA.,Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
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Sheikh MT, Chen MH, Gelfond JA, Ibrahim JG. A Power Prior Approach for Leveraging External Longitudinal and Competing Risks Survival Data Within the Joint Modeling Framework. STATISTICS IN BIOSCIENCES 2021. [DOI: 10.1007/s12561-021-09330-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
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Eyrich NW, Wei JT, Niknafs YS, Siddiqui J, Ellimoottil C, Salami SS, Palapattu GS, Mehra R, Kunju LP, Tomlins SA, Chinnaiyan AM, Morgan TM, Tosoian JJ. Association of MyProstateScore (MPS) with prostate cancer grade in the radical prostatectomy specimen. Urol Oncol 2021; 40:4.e1-4.e7. [PMID: 34753659 DOI: 10.1016/j.urolonc.2021.09.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2021] [Revised: 09/02/2021] [Accepted: 09/19/2021] [Indexed: 11/28/2022]
Abstract
BACKGROUND To evaluate the association between urinary MyProstateScore (MPS) and pathologic grade group (GG) at surgery in men diagnosed with GG1 prostate cancer (PCa) on biopsy. METHODS Using an institutional biospecimen protocol, we identified men with GG1 PCa on biopsy and PSA ≤10 ng/ml who underwent radical prostatectomy (RP) at the University of Michigan. MPS was retrospectively calculated using prospectively collected, post-DRE urine samples. The primary outcome was upgrading on RP pathology, defined as GG ≥ 2. The associations of MPS, PSA, and PSA density (PSAD) with upgrading were assessed on univariable logistic regression, and the predictive accuracy of each marker was estimated by the area under the receiver operating characteristic curve (AUC). RESULTS There were 52 men with urinary specimens available that met study criteria, based on biopsy Gleason Grade and specimen collection. At RP, 17 men (33%) had GG1 cancer and 35 (67%) had GG ≥ 2 cancer. Preoperative MPS was significantly higher in patients with GG ≥ 2 cancer at surgery (median 37.8 [IQR, 22.2-52.4]) as compared to GG1 (19.3 [IQR, 9.2-29.4]; P = 0.001). On univariable logistic regression, increasing MPS values were significantly associated with upgrading (odds ratio 1.07 per one-unit MPS increase, 95% confidence interval 1.02-1.12, P = 0.004), while PSA and PSAD were not significantly associated with upgrading. Similarly, the discriminative ability of the MPS model (AUC 0.78) for upgrading at RP was higher compared to models based on PSA (AUC 0.52) and PSAD (AUC 0.62). CONCLUSIONS In men diagnosed with GG1 PCa who underwent surgery, MPS was significantly associated with RP cancer grade. In this limited cohort of men, these findings suggest that MPS could help identify patients with undetected high-grade cancer. Additional studies are needed to better characterize this association.
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Affiliation(s)
- Nicholas W Eyrich
- Department of Urology, University of Michigan, Ann Arbor, MI; Department of Urology, Emory University School of Medicine, Atlanta, GA
| | - John T Wei
- Department of Urology, University of Michigan, Ann Arbor, MI; Dow Division of Health Services Research, University of Michigan, Ann Arbor, MI
| | - Yashar S Niknafs
- Michigan Center for Translational Pathology, University of Michigan, Ann Arbor, MI
| | - Javed Siddiqui
- Department of Urology, University of Michigan, Ann Arbor, MI; Michigan Center for Translational Pathology, University of Michigan, Ann Arbor, MI
| | - Chad Ellimoottil
- Department of Urology, University of Michigan, Ann Arbor, MI; Institute for Healthcare Policy and Innovation, University of Michigan, Ann Arbor, MI
| | - Simpa S Salami
- Department of Urology, University of Michigan, Ann Arbor, MI; Michigan Center for Translational Pathology, University of Michigan, Ann Arbor, MI; Rogel Cancer Center, University of Michigan, Ann Arbor, MI
| | - Ganesh S Palapattu
- Department of Urology, University of Michigan, Ann Arbor, MI; Rogel Cancer Center, University of Michigan, Ann Arbor, MI
| | - Rohit Mehra
- Michigan Center for Translational Pathology, University of Michigan, Ann Arbor, MI; Department of Pathology, University of Michigan, Ann Arbor, MI
| | - Lakshmi P Kunju
- Michigan Center for Translational Pathology, University of Michigan, Ann Arbor, MI; Department of Pathology, University of Michigan, Ann Arbor, MI
| | - Scott A Tomlins
- Department of Urology, University of Michigan, Ann Arbor, MI; Michigan Center for Translational Pathology, University of Michigan, Ann Arbor, MI; Rogel Cancer Center, University of Michigan, Ann Arbor, MI
| | - Arul M Chinnaiyan
- Department of Urology, University of Michigan, Ann Arbor, MI; Michigan Center for Translational Pathology, University of Michigan, Ann Arbor, MI; Rogel Cancer Center, University of Michigan, Ann Arbor, MI; Department of Pathology, University of Michigan, Ann Arbor, MI; Howard Hughes Medical Institute, University of Michigan, Ann Arbor, MI
| | - Todd M Morgan
- Department of Urology, University of Michigan, Ann Arbor, MI; Rogel Cancer Center, University of Michigan, Ann Arbor, MI
| | - Jeffrey J Tosoian
- Department of Urology, University of Michigan, Ann Arbor, MI; Michigan Center for Translational Pathology, University of Michigan, Ann Arbor, MI; Rogel Cancer Center, University of Michigan, Ann Arbor, MI; Department of Urology, Vanderbilt University Medical Center, Nashville, TN; Vanderbilt-Ingram Cancer Center, Nashville, TN.
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Setia S, Jackson J, Cendo D, Gorin MA, Allaway M, Vourganti S. Assessing the diagnostic performance of systematic freehand PrecisionPoint transperineal prostate biopsy: Comparison of observed outcomes to PBCG nomogram predictions. Urol Oncol 2021; 40:4.e9-4.e17. [PMID: 34688533 DOI: 10.1016/j.urolonc.2021.08.029] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2021] [Revised: 08/08/2021] [Accepted: 08/30/2021] [Indexed: 11/30/2022]
Abstract
OBJECTIVE We assessed the diagnostic performance of freehand systematic transperineal biopsy (fTPb) by using the Prostate Biopsy Collaborative Group (PBCG) nomogram, which is a contemporary update to the PCPT nomogram. METHODS From 1/2012 to 12/2018, fTPb was performed on consecutive men with clinical suspicion of prostate cancer. Patients included in this study had no previous diagnosis of prostate cancer, PSA between 2.5 ng/ml and 20 ng/ml, and underwent at least 12 core biopsies. In addition, those men who underwent pre-biopsy multiparametric magnetic resonance imaging of the prostate were considered separately from those without prebiopsy imaging. Biopsies were performed by a single urologist who developed the needle guidance device used in the procedure. Clinical and pathological data were collected retrospectively. We compared observed biopsy outcomes with those predicted by PBCG nomogram utilizing chi-square statistical analysis. RESULTS Systematic fTPb (without pre-biopsy MRI) was performed in 301 men (median age 67, mean PSA 6.9 ng/mL). These men had a median of 20 biopsy cores. Clinically significant cancer (ISUP 2 or greater) was found in 33.9% of men. In men without pre-biopsy MRI, using PBCG Nomogram, we found no significant difference between the expected and observed number of clinically significant cancer (96 vs. 102; P = 0.09). An additional 73 men (median age 67, mean PSA 7.8 ng/ml) underwent pre-biopsy MRI imaging. The addition of MRI targets to systematic sampling resulted in a median of 25 cores. Clinically significant cancer was found in 49.3%. Using the PBCG Nomogram, in the men with pre-biopsy MRI we found clinically significant cancer in significantly more men than was expected by PBCG nomogram predictions (36 vs. 20; P = <0.01). There were no biopsy-related infectious complications. CONCLUSION The fTPb technique is a promising method to sample the prostate which provides cancer detection that is comparable to that expected from systematic TRUS biopsy. We found that pre-biopsy mpMRI resulted in greater than expected detection of clinically significant cancer when utilizing this technique.
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Affiliation(s)
- Shaan Setia
- Rush University Medical Center, Department of Urology, Chicago, Illinois
| | - Jamaal Jackson
- Rush University Medical Center, Department of Urology, Chicago, Illinois
| | | | - Michael A Gorin
- Urology Associates and UPMC Western Maryland, Cumberland, MD, USA; Department of Urology, University of Pittsburgh School of Medicine, Pittsburgh, PA
| | - Matthew Allaway
- Urology Associates and UPMC Western Maryland, Cumberland, MD, USA
| | - Srinivas Vourganti
- Rush University Medical Center, Department of Urology, Chicago, Illinois.
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Ghosh D, Sabel MS. A Weighted Sample Framework to Incorporate External Calculators for Risk Modeling. STATISTICS IN BIOSCIENCES 2021. [DOI: 10.1007/s12561-021-09325-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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Stojadinovic M, Milicevic B, Jankovic S. Improved predictive performance of prostate biopsy collaborative group risk calculator when based on automated machine learning. Comput Biol Med 2021; 138:104903. [PMID: 34598066 DOI: 10.1016/j.compbiomed.2021.104903] [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] [Received: 07/27/2021] [Revised: 09/05/2021] [Accepted: 09/23/2021] [Indexed: 01/29/2023]
Abstract
BACKGROUND The Prostate Biopsy Collaborative Group risk calculator (PBCG RC) has a moderate discriminatory capability. This study aimed to create automated machine learning (AutoML) PBCG RC for predicting the probability of any-grade and high-grade prostate cancer (PCa). METHODS This retrospective, single-center study was carried out using the database with 832 patients who were subject to transrectal ultrasound-guided prostate biopsy with prostate-specific antigen (PSA) values from 2 to 50 ng/ml. Information about PBCG RC predictors was gathered for all patients. We used H2O, as an open-source platform for AutoML, where the set of 20 base learning algorithms were trained. The AutoML PBCG RC was compared in terms of discrimination, calibration, and clinical utility with the original PBCG RC. RESULTS PCa was detected in 341 (41%) men, and 159 (19.1%) of them had high-grade PCa. Our AutoML models demonstrated better discriminative ability than the original PBCG RC for detection of PCa (area under the curve [AUC]: 0.703 vs 0.628; P = 0.023) and high-grade PCa (AUC: 0.990 vs 0.717; P < 0.001). The decision curve analyses showed that AutoML models performed better. For high-grade PCa the PSA was the most important feature. CONCLUSIONS We applied ensemble techniques to create a freely available online PCa risk tool based on PBCG RC predictors and AutoML algorithms. The AutoML models drastically improved original model performance and the predictions of high-grade PCa were nearly perfect. However, new models should be used with a reserve, because external validation has not been performed yet.
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Affiliation(s)
- Miroslav Stojadinovic
- Clinical Centre "Kragujevac", Clinic of Urology and Nephrology, Department of Urology, Kragujevac, Serbia; University of Kragujevac, Faculty of Medical Sciences, Kragujevac, Serbia.
| | - Bogdan Milicevic
- Bioengineering Research and Development Center BioIRC Kragujevac, Kragujevac, Serbia; Faculty of Engineering, University of Kragujevac, Kragujevac, Serbia
| | - Slobodan Jankovic
- University of Kragujevac, Faculty of Medical Sciences, Pharmacology and Toxicology Department, Kragujevac, Serbia
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Margolis E, Brown G, Partin A, Carter B, McKiernan J, Tutrone R, Torkler P, Fischer C, Tadigotla V, Noerholm M, Donovan MJ, Skog J. Predicting high-grade prostate cancer at initial biopsy: clinical performance of the ExoDx (EPI) Prostate Intelliscore test in three independent prospective studies. Prostate Cancer Prostatic Dis 2021; 25:296-301. [PMID: 34593984 PMCID: PMC9184274 DOI: 10.1038/s41391-021-00456-8] [Citation(s) in RCA: 35] [Impact Index Per Article: 11.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2021] [Revised: 08/21/2021] [Accepted: 09/09/2021] [Indexed: 12/24/2022]
Abstract
Background The ability to discriminate indolent from clinically significant prostate cancer (PC) at the initial biopsy remains a challenge. The ExoDx Prostate (IntelliScore) (EPI) test is a noninvasive liquid biopsy that quantifies three RNA targets in urine exosomes. The EPI test stratifies patients for risk of high-grade prostate cancer (HGPC; ≥ Grade Group 2 [GG] PC) in men ≥ 50 years with equivocal prostate-specific antigen (PSA) (2–10 ng/mL). Here, we present a pooled meta-analysis from three independent prospective-validation studies in men presenting for initial biopsy decision. Methods Pooled data from two prospective multi-site validation studies and the control arm of a clinical utility study were analyzed. Performance was evaluated using the area under the receiver-operating characteristic curve (AUC), negative predictive value (NPV), positive predictive value (PPV), sensitivity, and specificity for discriminating ≥ GG2 from GG1 and benign pathology. Results The combined cohort (n = 1212) of initial-biopsy subjects had a median age of 63 years and median PSA of 5.2 ng/mL. The EPI AUC (0.70) was superior to PSA (0.56), Prostate Cancer Prevention Trial Risk Calculator (PCPT-RC) (0.62), and The European Randomized Study of Screening for Prostate Cancer (ERSPC) (0.59), (all p-values <0.001) for discriminating GG2 from GG1 and benign histology. The validated cutoff of 15.6 would avoid 23% of all prostate biopsies and 30% of “unnecessary” (benign or Gleason 6/GG1) biopsies, with an NPV of 90%. Conclusions EPI is a noninvasive, easy-to-use, urine exosome–RNA assay that has been validated across 3 independent prospective multicenter clinical trials with 1212 subjects. The test can discriminate high-grade (≥GG2) from low-grade (GG1) cancer and benign disease. EPI effectively guides the biopsy-decision process independent of PSA and other standard-of-care factors.
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Affiliation(s)
| | | | | | | | | | | | | | | | | | - Mikkel Noerholm
- Exosome Diagnostics, a Bio-techne brand, Martinsried, Germany
| | | | - Johan Skog
- Exosome Diagnostics, a Bio-techne brand, Waltham, MA, USA
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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: 3] [Impact Index Per Article: 1.0] [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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Xu B, Li G, Kong C, Chen M, Hu B, Jiang Q, Li N, Zhou L. A multicenter retrospective study on evaluation of predicative factors for positive biopsy of prostate cancer in real-world setting. Curr Med Res Opin 2021; 37:1617-1625. [PMID: 34192993 DOI: 10.1080/03007995.2021.1949270] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
Abstract
OBJECTIVE This study aimed to evaluate the predictors for positive biopsy in prostate cancer (PCa) patients and develop a risk-stratification score model for positive biopsy rate in patients with prostate specific antigen (PSA) in the gray zone. METHODS In this retrospective, multicenter, real-world study, Chinese patients receiving prostate biopsy for the first time were included. The study evaluated the positive biopsy rate, predictors for positive biopsy and a risk prediction model for PSA 4-10 ng/mL PCa was developed. The univariate and multivariate logistic regression analyses were used to identify the risk factors. RESULTS A total of 2426 patients were included in the study. The biopsy positive rate was 47.57%, 25.77%, and 60.57% among overall patients, total PSA (t-PSA) 4-10 ng/mL patients, and PSA > 10 ng/mL patients respectively. Elderly age 60-74, ≥75, multi parametric magnetic resonance imaging (MP-MRI), pre-operative PSA > 10 and PSA density (PSAD) significantly increased the positive rate in overall population, and elderly age, MP-MRI, positive digital rectal examination and f-PSA were significant predictors for positive biopsy in PSA 4-10 ng/mL population. A risk prediction model for positive biopsy rate in patients with PSA in the gray zone was developed. Area under curve (AUC) was associated with low accuracy for all the variables used such as tPSA (0.53), PSAD (0.57), frequency of puncture (0.53) and MP-MRI (0.64) in prediction of biopsy positive rate. CONCLUSION Our study evaluated the significant predicative factors for positive biopsy and the PCa risk prediction model developed might help Clinicians to avoid unnecessary biopsy in patients with PSA in gray zone.
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Affiliation(s)
- Ben Xu
- Department of Urology, Peking University First Hospital, Institute of Urology, Peking University, National Urological Cancer Center, Beijing, China
| | - Gonghui Li
- Department of Urology, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Chuize Kong
- Department of Urology, First hospital of China Medical University, Shenyang, China
| | - Ming Chen
- Department of Urology, Affiliated Zhongda Hospital of Southeast University, Nanjing, China
| | - Bin Hu
- Department of Urology, Liaoning Cancer Hospital and Institute, Cancer Hospital of China Medical University, Shenyang, China
| | - Qing Jiang
- Department of Urology, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Ningchen Li
- Department of Urology, Peking University Shougang Hospital, Peking University Health Science Center, Beijing, China
| | - Liqun Zhou
- Department of Urology, Peking University First Hospital, Institute of Urology, Peking University, National Urological Cancer Center, Beijing, China
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Van Poppel H, Hogenhout R, Albers P, van den Bergh RCN, Barentsz JO, Roobol MJ. A European Model for an Organised Risk-stratified Early Detection Programme for Prostate Cancer. Eur Urol Oncol 2021; 4:731-739. [PMID: 34364829 DOI: 10.1016/j.euo.2021.06.006] [Citation(s) in RCA: 51] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2021] [Revised: 06/10/2021] [Accepted: 06/23/2021] [Indexed: 11/16/2022]
Abstract
CONTEXT Overdiagnosis as the argument to stop prostate cancer (PCa) screening is less valid since the introduction of new technologies such as risk calculators (RCs) and magnetic resonance imaging (MRI). These new technologies result in fewer unnecessary biopsy procedures and fewer cases of both overdiagnosis and underdetection. Therefore, we can now adequately respond to the growing and urgent need for a structured risk assessment to detect PCa early. OBJECTIVE To provide expert discussion on the existing evidence for a previously published risk-stratified strategy regarding an organised population-based early detection programme for PCa. EVIDENCE ACQUISITION The proposed algorithm for early detection of PCa emerged from expert consensus by the authors based on available evidence derived from a nonsystematic review of the current literature using Medline/PubMed, Cochrane Library database, ClinicalTrials.gov, ISRCTN Registry, and the European Association of Urology guidelines on PCa. EVIDENCE SYNTHESIS Although not confirmed by the highest level of evidence, current literature and guidelines point towards an algorithm for early detection of PCa that starts with risk-based prostate-specific antigen (PSA) testing, followed by multivariable risk stratification with RCs. All men who are classified to be at intermediate and high risk are then offered prostate MRI. The combined data from RCs and MRI results can be used to select men for prostate biopsy. Low-risk men return to a risk-based safety net that includes individualised PSA-interval tests and, if necessary, repeated MRI. Depending on local availability, the use of the different risk stratification tools may be adapted. CONCLUSIONS We present a risk-stratified algorithm for an organised population-based early detection programme for clinically significant PCa. Although the proposed strategy has not yet been analysed prospectively, it exploits and may even improve the most important available benefits of "PSA-only" screening studies, while at the same time reduces unnecessary biopsies and overdiagnosis by using new risk stratification tools. PATIENT SUMMARY This paper presents a personalised strategy that enables selective early detection of prostate cancer by combining prostate-specific antigen (interval) testing' prediction models (risk calculators), and magnetic resonance imaging scans. This will likely lead to reduced prostate cancer-related morbidity and mortality, while reducing the need for prostate biopsy and limiting overdiagnosis.
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Affiliation(s)
- Hendrik Van Poppel
- Department of Development and Regeneration, University Hospital KU Leuven, Leuven, Belgium.
| | - Renée Hogenhout
- Department of Urology, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Peter Albers
- Department of Urology, Heinrich-Heine University Medical Faculty, Düsseldorf, Germany; Division of Personalized Early Detection of Prostate Cancer, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | | | - Jelle O Barentsz
- Department of Medical Imaging, Radboudumc, Nijmegen, The Netherlands
| | - Monique J Roobol
- Department of Urology, Erasmus University Medical Center, Rotterdam, The Netherlands
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A 25-year perspective on evaluation and understanding of biomarkers in urologic cancers. Urol Oncol 2021; 39:602-617. [PMID: 34315659 DOI: 10.1016/j.urolonc.2021.06.010] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2021] [Accepted: 06/17/2021] [Indexed: 12/15/2022]
Abstract
The past 25 years have witnessed an explosion of investigative attempts to identify clinically useful biomarkers which can have meaningful impacts for patients with urologic cancers. However, in spite of the enormous amount of research aiming to identify markers with the hope of impacting patient care, only a handful have proven to have true clinical utility. Improvements in targeted imaging, pan-omics evaluation, and genetic sequencing at the tissue and single-cell levels have yielded many potential targets for continued biomarker investigation. This article, as one in this series for the 25th Anniversary Issue of Urologic Oncology: Seminars and Original Investigations, serves to give a perspective on our progress and failures over the past quarter-century in our highest volume urologic cancers: prostate, bladder, and kidney cancers.
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He YD, Tao W, He T, Wang BY, Tang XM, Zhang LM, Wu ZQ, Deng WM, Zhang LX, Shao CK, Zhou J, Rong LM, Gao X, Li LY. A urine extracellular vesicle circRNA classifier for detection of high-grade prostate cancer in patients with prostate-specific antigen 2-10 ng/mL at initial biopsy. Mol Cancer 2021; 20:96. [PMID: 34301266 PMCID: PMC8299620 DOI: 10.1186/s12943-021-01388-6] [Citation(s) in RCA: 38] [Impact Index Per Article: 12.7] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2021] [Accepted: 06/25/2021] [Indexed: 02/07/2023] Open
Abstract
The aim of this study was to identify a urine extracellular vesicle circular RNA (circRNA) classifier that could detect high-grade prostate cancer (PCa) of Grade Group (GG) 2 or greater. For this purpose, we used RNA sequencing to identify candidate circRNAs from urinary extracellular vesicles from 11 patients with high-grade PCa and 11 case-matched patients with benign prostatic hyperplasia. Using ddPCR in a training cohort (n = 263), we built a urine extracellular vesicle circRNA classifier (Ccirc, containing circPDLIM5, circSCAF8, circPLXDC2, circSCAMP1, and circCCNT2), which was evaluated in two independent cohorts (n = 497, n = 505). Ccirc showed higher accuracy than two standard of care risk calculators (RCs) (PCPT-RC 2.0 and ERSPC-RC) in both the training cohort and the validation cohorts. In all three cohorts, this novel urine extracellular vesicle circRNA classifier plus RCs was statistically more predictive than RCs alone for predicting ≥ GG2 PCa. This assay, which does not require precollection digital rectal examination nor special handling, is repeatable, noninvasive, and can be easily implemented as part of the basic clinical workflow.
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Affiliation(s)
- Ya-Di He
- Centre of Physical Examination, The Third Affiliated Hospital, Sun Yat-Sen University, Guangzhou, 510630, China
| | - Wen Tao
- Department of Urology, The Third Affiliated Hospital, Sun Yat-Sen University, Tianhe Road 600, Guangzhou, 510630, China
| | - Tao He
- Department of Urology, The Third Affiliated Hospital, Sun Yat-Sen University, Tianhe Road 600, Guangzhou, 510630, China
| | - Bang-Yu Wang
- Breast Surgery, The Third Affiliated Hospital, Sun Yat-Sen University, Guangzhou, 510630, China
| | - Xiu-Mei Tang
- Centre of Physical Examination, The Third Affiliated Hospital, Sun Yat-Sen University, Guangzhou, 510630, China
| | - Liang-Ming Zhang
- Department of Spine Surgery, The Third Affiliated Hospital, Sun Yat-Sen University, Guangzhou, 510630, China
| | - Zhen-Quan Wu
- Department of Urology, Foshan First Municipal People's Hospital, Sun Yat-Sen University, Foshan, 528000, China
| | - Wei-Ming Deng
- Department of Urology, The First Affiliated Hospital, University of South China, Hengyang, 421000, China
| | - Ling-Xiao Zhang
- Department of Urology, The First Affiliated Hospital, Hainan Medical College, Haikou, 570102, China
| | - Chun-Kui Shao
- Department of Pathology, The Third Affiliated Hospital, Sun Yat-Sen University, Guangzhou, 510630, China
| | - Jing Zhou
- Department of Pathology, The Third Affiliated Hospital, Sun Yat-Sen University, Guangzhou, 510630, China
| | - Li-Min Rong
- Department of Spine Surgery, The Third Affiliated Hospital, Sun Yat-Sen University, Guangzhou, 510630, China
| | - Xin Gao
- Department of Urology, The Third Affiliated Hospital, Sun Yat-Sen University, Tianhe Road 600, Guangzhou, 510630, China
| | - Liao-Yuan Li
- Department of Urology, The Third Affiliated Hospital, Sun Yat-Sen University, Tianhe Road 600, Guangzhou, 510630, China.
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Patel HD, Doshi CP, Koehne EL, Hart S, Van Kuiken M, Quek ML, Flanigan RC, Gupta GN. African American Men have Increased Risk of Prostate Cancer Detection Despite Similar Rates of Anterior Prostatic Lesions and PI-RADS Grade on Multiparametric Magnetic Resonance Imaging. Urology 2021; 163:132-137. [PMID: 34302832 DOI: 10.1016/j.urology.2021.07.005] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2021] [Revised: 06/21/2021] [Accepted: 07/08/2021] [Indexed: 01/17/2023]
Abstract
OBJECTIVE To determine whether the frequency of anterior prostate lesions (APL) on multiparametric magnetic resonance imaging (mpMRI) prior to biopsy differed between African American (AA) and non-AA men and evaluate implications of race and tumor location for prostate cancer (PCa) detection. METHODS Patients from the Prospective Loyola University mpMRI (PLUM) Prostate Biopsy Cohort (January 2015-December 2020) without prior diagnosis of PCa were evaluated for APLs by race. Multivariable logistic regression models evaluated predictors of APLs and associations of APLs and race with detection of any PCa (grade group 1+) and clinically significant PCa (csPCa; grade group 2+). Additional stratified and propensity score matched analyses were conducted. RESULTS Of 1,239 men included, 190 (15.3%) were AA and 302 (24.4%) had at least one APL with no differences by race on multivariable analysis. While men with APLs were twice as likely to harbor PCa or csPCa, the unadjusted proportion of targeted biopsy-confirmed APL PCa (12.6% vs 12.0%) or csPCa (8.4% vs 8.9%) were similar for AA and non-AA men. AA men had higher risk of prostate cancer on targeted cores (OR 1.66 (95%CI 1.06 - 2.61), P = 0.026) which was independent of lesion location or PI-RADS. CONCLUSION AA men were found to have similar rates of APLs on mpMRI to non-AA men indicating access to mpMRI may mitigate some of the historical racial disparity based on lesion location. AA men have increased risk of PCa detection compared to non-AA men independent of anterior location or lesion grade on mpMRI reinforcing the importance of identifying genetic, biologic, and socioeconomic drivers.
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Affiliation(s)
- Hiten D Patel
- Department of Urology, Loyola University Medical Center, Maywood, Illinois.
| | - Chirag P Doshi
- Department of Urology, Loyola University Medical Center, Maywood, Illinois
| | - Elizabeth L Koehne
- Department of Urology, Loyola University Medical Center, Maywood, Illinois
| | | | - Michelle Van Kuiken
- Department of Urology, University of California San Francisco, San Francisco, California
| | - Marcus L Quek
- Department of Urology, Loyola University Medical Center, Maywood, Illinois
| | - Robert C Flanigan
- Department of Urology, Loyola University Medical Center, Maywood, Illinois
| | - Gopal N Gupta
- Department of Urology, Loyola University Medical Center, Maywood, Illinois; Department of Surgery, Loyola University Medical Center, Maywood, Illinois; Department of Radiology, Loyola University Medical Center, Maywood, Illinois
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Amaya-Fragoso E, García-Pérez CM. Improving prostate biopsy decision making in Mexican patients: Still a major public health concern. Urol Oncol 2021; 39:831.e11-831.e18. [PMID: 34193378 DOI: 10.1016/j.urolonc.2021.05.022] [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] [Received: 01/25/2021] [Revised: 05/10/2021] [Accepted: 05/20/2021] [Indexed: 11/15/2022]
Abstract
BACKGROUND Prostate cancer screening has reduced its mortality in 21%. However, this has also led to an increased number of biopsies in order to establish the diagnosis, many of them unnecessary. Current screening guidelines prioritize use of prostatic magnetic resonance and new biomarkers to reduce unnecessary biopsies, however, their implementation in developing countries screening programs is mainly limited by its costs. OBJECTIVE We aimed to evaluate Prostate Biopsy Risk Collaborative Group (PBCG) and Prostate Cancer Prevention Trial Risk Calculator (PCPTRC) 2.0 predictions accuracy in Mexican patients in order to guide prostate biopsy decision making and reduce unnecessary biopsies. MATERIALS AND METHODS We retrospectively analyzed patients between 55 and 90 years old who underwent prostate biopsy in a high-volume center in Mexico between January 2017 and June 2020. Clinical utility of PBCG and PCPTRC 2.0 to predict high-grade prostate cancer (HGPCa) biopsy outcomes was evaluated using decision curve analysis and compared to actual biopsy decision making. Receiver operating characteristics area under the curve (AUC) was used to measure discrimination and external validation. RESULTS From 687 patients eligible for prostate biopsy, 433 met selections criteria. One hundred and thirty-five (31.17%) patients were diagnosed with HGPCa, 63 (14.54%) with low-grade disease and 235 (54.27%) had a negative biopsy. PCPTRC 2.0 ≥15% threshold got a standardized net benefit (sNB) of 0.70, while PBCG ≥30% and ≥35% had a sNB of 0.27 and 0.15, respectively. Use of both models for guiding prostate biopsy decision resulted in no statistical difference for HGCPa detection rates, while achieved a significant difference in reducing total and unnecessary biopsies. However, this difference was lower (better) for PCPTRC 2.0, being statistically significative when compared against PBCG thresholds. Both models were well calibrated (AUC 0.79) and achieved external validation compared with international cohorts. CONCLUSIONS Our study is the first to effectively validate both PCPTRC 2.0 and PBCG predictions for the Mexican population, proving that their use in daily practice improves biopsy decision making by accurately predicting HGPCa and limit unnecessary biopsies without representing additional costs to screening programs.
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Affiliation(s)
- Eduardo Amaya-Fragoso
- Department of Urology, Northeast National Medical Center, Instituto Mexicano del Seguro Social. Monterrey, Nuevo León, México.
| | - Carlos Marcel García-Pérez
- Department of Urology, Northeast National Medical Center, Instituto Mexicano del Seguro Social. Monterrey, Nuevo León, México
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Environmental Factors-Induced Oxidative Stress: Hormonal and Molecular Pathway Disruptions in Hypogonadism and Erectile Dysfunction. Antioxidants (Basel) 2021; 10:antiox10060837. [PMID: 34073826 PMCID: PMC8225220 DOI: 10.3390/antiox10060837] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2021] [Revised: 05/19/2021] [Accepted: 05/20/2021] [Indexed: 01/09/2023] Open
Abstract
Hypogonadism is an endocrine disorder characterized by inadequate serum testosterone production by the Leydig cells of the testis. It is triggered by alterations in the hypothalamic–pituitary–gonadal axis. Erectile dysfunction (ED) is another common disorder in men that involves an alteration in erectile response–organic, relational, or psychological. The incidence of hypogonadism and ED is common in men aged over 40 years. Hypogonadism (including late-onset hypogonadism) and ED may be linked to several environmental factors-induced oxidative stresses. The factors mainly include exposure to pesticides, radiation, air pollution, heavy metals and other endocrine-disrupting chemicals. These environmental risk factors may induce oxidative stress and lead to hormonal dysfunctions. To better understand the subject, the study used many keywords, including “hypogonadism”, “late-onset hypogonadism”, “testosterone”, “erectile dysfunction”, “reactive oxygen species”, “oxidative stress”, and “environmental pollution” in major online databases, such as SCOPUS and PUBMED to extract relevant scientific information. Based on these parameters, this review summarizes a comprehensive insight into the important environmental issues that may have a direct or indirect association with hypogonadism and ED in men. The study concludes that environmental factors-induced oxidative stress may cause infertility in men. The hypothesis and outcomes were reviewed critically, and the mechanistic approaches are applied through oxidant-sensitive pathways. This study also provides reccomendations on future therapeutic interventions and protective measures against such adverse environmental factors-induced hypogonadism and ED.
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Presti JC, Alexeeff S, Horton B, Prausnitz S, Avins AL. Prospective validation of the Kaiser Permanente prostate cancer risk calculator in a contemporary, racially diverse, referral population. Urol Oncol 2021; 39:783.e11-783.e19. [PMID: 33962850 DOI: 10.1016/j.urolonc.2021.03.023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2020] [Revised: 02/26/2021] [Accepted: 03/28/2021] [Indexed: 10/21/2022]
Abstract
PURPOSE To prospectively validate a new prostate cancer risk calculator in a racially diverse population. MATERIALS AND METHODS We recently developed, internally validated and published the Kaiser Permanente Prostate Cancer Risk Calculator. This study is a prospective validation of the calculator in a separate, referral population over a 21-month period. All patients were tested with a uniform PSA assay and a standardized systematic, ultrasound-guided biopsy scheme. We report on 3 calculator models: Model 1 included age, race, PSA, prior biopsy status, body mass index, and family history of prostate cancer; Model 2 added digital rectal exam to Model 1 variables; Model 3 added prostate volume to Model 2 variables. We considered three outcomes: high-grade disease (Gleason score ≥7), low-grade disease (Gleason score=6), and no cancer. Predictive discrimination and calibration were calculated. How each model might alter biopsy frequency and outcomes at various thresholds of risk was assessed. We compared the performance of our calculator with two other calculators. RESULTS In 4178 patients (16.2% Asian, 11.3% African American, 13.5% Hispanic), cancer was found in 53%; 62% were Gleason score ≥7. Using a high-grade risk threshold for biopsy of ≥10%, Model 2 predictions would result in 9% of men avoiding a biopsy, while only missing 2% of high-grade cancers. At the same threshold, Model 3 predictions would result in 26% of men avoiding a biopsy, while only missing 5% of high-grade cancers. The c-statistics for Models 1, 2, and 3 to predict high-grade disease vs. low-grade or no cancer were 0.76, 0.79 and 0.85, respectively. The c-statistics for Models 1, 2, and 3 to predict any prostate cancer vs. no cancer were 0.70, 0.72 and 0.80, respectively. All models were well calibrated for all outcomes. Our Model 3 calculator had superior discrimination for high grade disease (c-statistic=0.85, 0.84-0.86) and any cancer (0.80, 0.79-0.82) compared to the PBCG calculator [(0.79, 0.78-0.80); 0.72 (0.70-0.73)] and the PCPT calculator [(0.75, 0.74-0.77); 0.69 (0.67-0.70)], respectively. In the high-grade cancer predicted risk range of 0-30%, our Model 2 was better calibrated than the PCPT and PBCG calculators. CONCLUSIONS This validation of our calculator showed excellent performance characteristics.
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Affiliation(s)
- Joseph C Presti
- Department of Urology, Kaiser Permanente Northern California, Oakland, CA; Division of Research, Kaiser Permanente Northern California, Oakland, CA.
| | - Stacey Alexeeff
- Division of Research, Kaiser Permanente Northern California, Oakland, CA
| | - Brandon Horton
- Division of Research, Kaiser Permanente Northern California, Oakland, CA
| | | | - Andrew L Avins
- Division of Research, Kaiser Permanente Northern California, Oakland, CA; Department of Medicine, Kaiser Permanente Northern California, Oakland, CA
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