Decision-making tools in prostate cancer: from risk grouping to nomograms
| Autor: | Claude C. Abbou, Francesco Porpiglia, David M. Albala, Paolo Fontanella, Giampaolo Bianchi, Luigi Benecchi, Angelica Grasso, Marco Sandri, Vipul R. Patel, Bernardo Rocco |
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| Rok vydání: | 2017 |
| Předmět: |
Biochemical recurrence
Male medicine.medical_specialty medicine.medical_treatment Urology Clinical Decision-Making MEDLINE Diagnosis Nomograms Prostate neoplasms Prostatectomy Nephrology Risk Assessment 03 medical and health sciences Prostate cancer 0302 clinical medicine medicine Humans Medical physics 030212 general & internal medicine business.industry Prostatic Neoplasms medicine.disease Prognosis Systematic review 030220 oncology & carcinogenesis Partin Tables Prostate neoplasm business Risk assessment |
| Zdroj: | Minerva urologica e nefrologica = The Italian journal of urology and nephrology. 69(6) |
| ISSN: | 1827-1758 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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