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

Abstract

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.

Magnetic resonance imaging /ultrasonography fusion transperineal prostate biopsy for prostate cancer: Initial experience at a Middle Eastern tertiary medical centre

“…None of our targeted PI-RADS 3 lesions had csPCa, while most studies report a detection rate of 8–19% [ 17 , 18 , 19 , 20 , 21 , 22 ]. Several strategies of combining additional information regarding lesion size, PSA density and biomarkers may be beneficial in stratifying PI-RADS 3 lesions into high- and low-risk lesions in order to maximise detection rate of csPCa and minimise unnecessary biopsies [ 23 , 24 ]. In our present cohort, the lack of csPCa is partly due to selection bias due to a small sample size, as well as possible over reading of low-risk MRI lesions as PI-RADS 3.…”

Update on Prostate Cancer Diagnosis, Prognosis, and Prediction to Response to Therapy

“…Research on PCa is accompanied by the development of complex emerging techniques [ 9 ]. The pathologist has to integrate information from the pathological evaluation with the data from different sources to achieve a final diagnosis, prognosis and prediction to the response to therapy [ 4 ]. The ultimate issue is to improve our understanding of genomics in order to identify actionable targets as well as to develop novel treatments for patients with advanced PCa to extend survival and possibly provide cure [ 5 ].…”

“…The wide range of novelties reported in this Special Issue of the journal Cells on prostate cancer (PCa) diagnosis, prognosis, and prediction to response to therapy, has led us to a series of considerations related to a better understanding of the current and future role of effective molecular biomarkers in individual patients with PCa [ 1 , 2 , 3 , 4 , 5 , 6 , 7 ]: (1) Digital pathology, including multiplexing; (2) Clinical translation of genetic information; (3) Clinical significance of liquid biopsies; and (4) Multi-criteria decision making and information fusion.…”

Predictive Value of Malignancy Index in Tumour Staging in Prostate Cancer

“…22 To adequately assess the patient's prognosis and plan the management, PCa staging must make use of the many clinicopathological parameters at its disposal. 23 These novel prognostic biomarkers aid in avoiding unnecessary imaging studies and invasive interventions.…”