How Well do Polygenic Risk Scores Identify Men at High Risk for Prostate Cancer? Systematic Review and Meta-Analysis

Aino Siltari, Ragnar Lönnerbro, Karl Pang, Kirill Shiranov, Alex Asiimwe, Susan Evans-Axelsson, Billy Franks, Amit Kiran, Teemu J Murtola, Jack Schalken, Carl Steinbeisser, Anders Bjartell, Anssi Auvinen, PIONEER Consortium

Research output: Contribution to journalReview Articlepeer-review

2 Citations (Scopus)
18 Downloads (Pure)

Abstract

OBJECTIVES: Genome-wide association studies have revealed over 200 genetic susceptibility loci for prostate cancer (PCa). By combining them, polygenic risk scores (PRS) can be generated to predict risk of PCa. We summarize the published evidence and conduct meta-analyses of PRS as a predictor of PCa risk in Caucasian men.

PATIENTS AND METHODS: Data were extracted from 59 studies, with 16 studies including 17 separate analyses used in the main meta-analysis with a total of 20,786 cases and 69,106 controls identified through a systematic search of ten databases. Random effects meta-analysis was used to obtain pooled estimates of area under the receiver-operating characteristic curve (AUC). Meta-regression was used to assess the impact of number of single-nucleotide polymorphisms (SNPs) incorporated in PRS on AUC. Heterogeneity is expressed as I2 scores. Publication bias was evaluated using funnel plots and Egger tests.

RESULTS: The ability of PRS to identify men with PCa was modest (pooled AUC 0.63, 95% CI 0.62-0.64) with moderate consistency (I2 64%). Combining PRS with clinical variables increased the pooled AUC to 0.74 (0.68-0.81). Meta-regression showed only negligible increase in AUC for adding incremental SNPs. Despite moderate heterogeneity, publication bias was not evident.

CONCLUSION: Typically, PRS accuracy is comparable to PSA or family history with a pooled AUC value 0.63 indicating mediocre performance for PRS alone.

Original languageEnglish
Pages (from-to)316.e1-316.e11
Number of pages11
JournalCLINICAL GENITOURINARY CANCER
Volume21
Issue number2
Early online date11 Sept 2022
DOIs
Publication statusPublished - 2023
Publication typeA2 Review article in a scientific journal

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