三种遗传风险指标预测前列腺癌发病和死亡风险的性能：基于人群的前瞻性分析。
Performance of Three Inherited Risk Measures for Predicting Prostate Cancer Incidence and Mortality: A Population-based Prospective Analysis.
机构信息
Program for Personalized Cancer Care, NorthShore University HealthSystem, Evanston, IL, USA.
Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA; Department of Urology and the James Buchanan Brady Urologic Institute, Johns Hopkins University School of Medicine, and the Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins, Baltimore, MD, USA.
出版信息
Eur Urol. 2021 Mar;79(3):419-426. doi: 10.1016/j.eururo.2020.11.014. Epub 2020 Nov 28.
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.
背景
基于单核苷酸多态性的遗传风险评分（GRS）已被开发和验证，用于评估前列腺癌（PCa）的风险。由于 GRS 是基于人群标准化的，其值可以解释为对一般人群的相对风险。
目的
比较 GRS 与两种指南推荐的遗传风险测量方法（家族史（FH）和罕见致病性突变（RPMs））在预测 PCa 发病和死亡中的性能。
设计、设置和参与者：从英国生物库中衍生出一个前瞻性队列，其中招募时 208685 名无 PCa 诊断的参与者通过英国癌症和死亡登记处进行随访。
结局测量和统计分析
通过英国癌症和死亡登记处，测量 FH（阳性与阴性）、RPMs（携带者与非携带者）和 GRS（最高与最低四分位数）的 PCa 发病和死亡率的率比（RR）。
结果和局限性
中位随访 9.67 年后，共确定了 6890 例 PCa 发病病例（419 例死于 PCa）。在单变量分析中，这三种方法均与 PCa 发病显著相关；FH 的 RR（95%置信区间[CI]）值为 1.88（1.75-2.01），RPMs 的 RR 值为 2.89（1.89-4.25），GRS 的 RR 值为 1.97（1.87-2.07）（均 p<0.001）。多变量分析中，这些关联是独立的。虽然 FH 和 RPMs 确定了 11%的高 PCa 风险男性，但 GRS 又确定了 22%的高 PCa 风险男性，区分发病的 C 统计量从 0.58 增加到 0.67（p<0.001），区分死亡率的 C 统计量从 0.65 增加到 0.71（p=0.002）。局限性在于少数患者人群和较短的死亡率随访。
结论
这项基于人群的前瞻性研究表明，GRS 补充了两种指南推荐的遗传风险测量方法（FH 和 RPMs），用于分层 PCa 发病和死亡率的风险。
患者总结
在一项源自英国生物库的大型基于人群的前列腺癌（PCa）前瞻性研究中，遗传风险评分（GRS）补充了两种指南推荐的遗传风险测量方法（家族史和罕见致病性突变），用于预测 PCa 的发病和死亡。这些结果为将 GRS 纳入 PCa 风险评估提供了重要数据。
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