Performance of Three Inherited Risk Measures for Predicting Prostate Cancer Incidence and Mortality: A Population-based Prospective Analysis

Zhuqing Shi, Elizabeth A. Platz, Jun Wei, Rong Na, Richard J. Fantus, Chi Hsiung Wang, Scott E. Eggener, Peter J. Hulick, David Duggan, S. Lilly Zheng, Kathleen A. Cooney, William B. Isaacs, Brian T. Helfand, Jianfeng Xu

Research output: Contribution to journalArticlepeer-review

Abstract

Background: Single nucleotide polymorphism–based genetic risk score (GRS) has been developed and validated for prostate cancer (PCa) risk assessment. As GRS is population standardized, its value can be interpreted as a relative risk to the general population. Objective: To compare the performance of GRS with two guideline-recommended inherited risk measures, family history (FH) and rare pathogenic mutations (RPMs), for predicting PCa incidence and mortality. Design, setting, and participants: A prospective cohort was derived from the UK Biobank where 208 685 PCa diagnosis-free participants at recruitment were followed via the UK cancer and death registries. Outcome measurements and statistical analysis: Rate ratios (RRs) of PCa incidence and mortality for FH (positive vs negative), RPMs (carriers vs noncarriers), and GRS (top vs bottom quartile) were measured. Results and limitations: After a median follow-up of 9.67 yr, 6890 incident PCa cases (419 died of PCa) were identified. Each of the three measures was significantly associated with PCa incidence in univariate analyses; RR (95 % confidence interval [CI]) values were 1.88 (1.75–2.01) for FH, 2.89 (1.89–4.25) for RPMs, and 1.97(1.87–2.07) for GRS (all p < 0.001). The associations were independent in multivariable analyses. While FH and RPMs identified 11 % of men at higher PCa risk, addition of GRS identified an additional 22 % of men at higher PCa risk, and increases in C-statistic from 0.58 to 0.67 for differentiating incidence (p < 0.001) and from 0.65 to 0.71 for differentiating mortality (p = 0.002). Limitations were a small number of minority patients and short mortality follow-up. Conclusions: This population-based prospective study suggests that GRS complements two guideline-recommended inherited risk measures (FH and RPMs) for stratifying the risk of PCa incidence and mortality. Patient summary: In a large population-based prostate cancer (PCa) prospective study derived from UK Biobank, genetic risk score (GRS) complements two guideline-recommended inherited risk measures (family history and rare pathogenic mutations) in predicting PCa incidence and mortality. These results provide critical data for including GRS in PCa risk assessment. In this first population-based prospective cohort study, single nucleotide polymorphism–based genetic risk score (GRS) performs better than and complements two guideline-recommended inherited risk measures (family history and rare pathogenic mutations) in predicting prostate cancer (PCa) incidence and mortality. This provides critical data for including GRS in guidelines for PCa risk assessment.

Original languageEnglish (US)
Pages (from-to)419-426
Number of pages8
JournalEuropean Urology
Volume79
Issue number3
DOIs
StateAccepted/In press - 2020

Keywords

  • Family history
  • Genetic risk score
  • High-penetrance genes
  • Prostate cancer
  • Risk assessment

ASJC Scopus subject areas

  • Urology

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