: Publication 5524

Publication 5524

Title:	Performance of Three Inherited Risk Measures for Predicting Prostate Cancer Incidence and Mortality: A Population-based Prospective Analysis
Journal:	European Urology
Published:	28 Nov 2020
Pubmed:	https://pubmed.ncbi.nlm.nih.gov/33257031/
DOI:	https://doi.org/10.1016/j.eururo.2020.11.014
URL:	http://manuscript.elsevier.com/S0302283820308782/pdf/S0302283820308782.pdf
Citations:	40 (12 in last 2 years) as of 8 Aug 2024

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.

Abstract

7 Keywords

14 Authors