This study was conducted in order to review the outcomes regarding polygenic risk score (PRS) in prediction of prostate cancer (PCa). With the increasing proficiency of genetic analysis, assessment of PRS for prediction of PCa has been performed in numerous studies. Genetic risk prediction models for PCa that include hundreds to thousands of independent risk-associated variants are under development. For estimation of additive effect of multiple variants, the number of risk alleles carried by an individual is summed, and each variant is weighted according to its estimated effect size for generation of a PRS. Currently, regarding the accuracy of PRS alone, PCa detection rate ranged from 0.56 to 0.67. A higher rate of accuracy of 0.866–0.880 was observed for other models combining PRS with established clinical markers. The results of PRS from Asian populations showed a level of accuracy that is somewhat low compared with values from Western populations (0.63–0.67); however, recent results from Asian cohorts were similar to that of Western counterparts. Here, we review current PRS literature and examine the clinical utility of PRS for prediction of PCa. Emerging data from several studies regarding PRS in PCa could be the solution to adding predictive value to PCa risk estimation. Although commercial markers are available, development of a large-scale, well validated PRS model should be undertaken in the near future, in order to translate hypothetical scenarios to actual clinical practice.
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