Paolo Fontanella1, Luigi Benecchi2, Angelica Grasso3, Vipul Patel4, David Albala5, Claude Abbou6, Francesco Porpiglia7, Marco Sandri8, Bernardo Rocco9,10, Giampaolo Bianchi10. 1. Department of Surgery, Regional Hospital of Mendrisio, Mendrisio, Switzerland. 2. Department of Urology, Cremona Hospitals, Cremona, Italy. 3. Department of Urology, Ca' Granda Institute for Research and Care, Maggiore Polyclinic Hospital, Milan, Italy. 4. Department of Urology, College of Medicine, Global Robotics Institute, University of Central Florida, Florida Hospital Celebration Health, Kissimmee, FL, USA. 5. Department of Urology, Associated Medical Professionals and Crouse Hospital, Syracuse, NY, USA. 6. Department of Urology, Henri Mondor Hospital, Assistance-Publique Hopitaux de Paris, Créteil, France. 7. Department of Urology, San Luigi Gonzaga Hospital, University of Turin, Orbassano, Turin, Italy. 8. DMS StatLab, Data Methods and Systems Statistical Laboratory, University of Brescia, Brescia, Italy. 9. Department of Urology, Ca' Granda Institute for Research and Care, Maggiore Polyclinic Hospital, Milan, Italy - bernardo.rocco@gmail.com. 10. Department of Urology, University of Modena and Reggio Emilia, Modena, Italy.
Abstract
INTRODUCTION: Prostate cancer (PCa) is the most common solid neoplasm and the second leading cause of cancer death in men. After the Partin tables were developed, a number of predictive and prognostic tools became available for risk stratification. These tools have allowed the urologist to better characterize this disease and lead to more confident treatment decisions for patients. The purpose of this study is to critically review the decision-making tools currently available to the urologist, from the moment when PCa is first diagnosed until patients experience metastatic progression and death. EVIDENCE ACQUISITION: A systematic and critical analysis through Medline, EMBASE, Scopus and Web of Science databases was carried out in February 2016 as per the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. The search was conducted using the following key words: "prostate cancer," "prediction tools," "nomograms." EVIDENCE SYNTHESIS: Seventy-two studies were identified in the literature search. We summarized the results into six sections: Tools for prediction of life expectancy (before treatment), Tools for prediction of pathological stage (before treatment), Tools for prediction of survival and cancer-specific mortality (before/after treatment), Tools for prediction of biochemical recurrence (before/after treatment), Tools for prediction of metastatic progression (after treatment) and in the last section biomarkers and genomics. CONCLUSIONS: The management of PCa patients requires a tailored approach to deliver a truly personalized treatment. The currently available tools are of great help in helping the urologist in the decision-making process. These tests perform very well in high-grade and low-grade disease, while for intermediate-grade disease further research is needed. Newly discovered markers, genomic tests, and advances in imaging acquisition through mpMRI will help in instilling confidence that the appropriate treatments are being offered to patients with prostate cancer.
INTRODUCTION:Prostate cancer (PCa) is the most common solid neoplasm and the second leading cause of cancer death in men. After the Partin tables were developed, a number of predictive and prognostic tools became available for risk stratification. These tools have allowed the urologist to better characterize this disease and lead to more confident treatment decisions for patients. The purpose of this study is to critically review the decision-making tools currently available to the urologist, from the moment when PCa is first diagnosed until patients experience metastatic progression and death. EVIDENCE ACQUISITION: A systematic and critical analysis through Medline, EMBASE, Scopus and Web of Science databases was carried out in February 2016 as per the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. The search was conducted using the following key words: "prostate cancer," "prediction tools," "nomograms." EVIDENCE SYNTHESIS: Seventy-two studies were identified in the literature search. We summarized the results into six sections: Tools for prediction of life expectancy (before treatment), Tools for prediction of pathological stage (before treatment), Tools for prediction of survival and cancer-specific mortality (before/after treatment), Tools for prediction of biochemical recurrence (before/after treatment), Tools for prediction of metastatic progression (after treatment) and in the last section biomarkers and genomics. CONCLUSIONS: The management of PCa patients requires a tailored approach to deliver a truly personalized treatment. The currently available tools are of great help in helping the urologist in the decision-making process. These tests perform very well in high-grade and low-grade disease, while for intermediate-grade disease further research is needed. Newly discovered markers, genomic tests, and advances in imaging acquisition through mpMRI will help in instilling confidence that the appropriate treatments are being offered to patients with prostate cancer.
Authors: Ericka M Sohlberg; I-Chun Thomas; Jaden Yang; Kristopher Kapphahn; Timothy J Daskivich; Ted A Skolarus; Jeremy B Shelton; Danil V Makarov; Jonathan Bergman; Christine Ko Bang; Mary K Goldstein; Todd H Wagner; James D Brooks; Manisha Desai; John T Leppert Journal: Urol Oncol Date: 2020-07-13 Impact factor: 3.498