Incorporating Prognostic Biomarkers into Risk Assessment Models and TNM Staging for Prostate Cancer

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In current practice, prostate cancer staging alone is not sufficient to adequately assess the patient's prognosis and plan the management strategies. Multiple clinicopathological parameters and risk tools for prostate cancer have been developed over the past decades to better characterize the disease and provide an enhanced assessment of prognosis. Herein, we review novel prognostic biomarkers and their integration into risk assessment models for prostate cancer focusing on their capability to help avoid unnecessary imaging studies, biopsies and diagnosis of low risk prostate cancers, to help in the decision-making process between active surveillance and treatment intervention, and to predict recurrence after radical prostatectomy. There is an imperative need of reliable biomarkers to stratify prostate cancer patients that may benefit from different management approaches. The integration of biomarkers panel with risk assessment models appears to improve prostate cancer diagnosis and management. However, integration of novel genomic biomarkers in future prognostic models requires further validation in their clinical efficacy, standardization, and cost-effectiveness in routine application.

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Biomarkers, Molecular classifier, Predictive scores, Prognosis, Prostate cancer, Risk assessment models, Staging, Antigens, neoplasm, Biomarkers, tumor, Clinical decision-making, Disease management, Gene expression, Humans, Kallikreins, Male, Models, statistical, Neoplasm proteins, Neoplasm recurrence, local, Neoplasm staging, Prostate, Prostate-specific antigen, Prostatectomy, Prostatic neoplasms, Risk assessment, Kallikrein, Kallikrein-related peptidase 3, human, Prostate cancer antigen 3, human, Prostate specific antigen, Tumor antigen, Tumor marker, Tumor protein, Cancer staging, Clinical decision making, Genetics, Human, Metabolism, Pathology, Procedures, Prostate tumor, Statistical model, Tumor recurrence

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