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整合PRS特异性和年龄特异性变异后,风险适应性前列腺特异性抗原(PSA)筛查对前列腺癌的初步影响。

Preliminary effects of risk-adapted PSA screening for prostate cancer after integrating PRS-specific and age-specific variation.

作者信息

Liu Xiaomin, Duan Hongyuan, Liu Siwen, Zhang Yunmeng, Ji Yuting, Zhang Yacong, Feng Zhuowei, Li Jingjing, Liu Ya, Gao Ying, Wang Xing, Zhang Qing, Yang Lei, Dai Hongji, Lyu Zhangyan, Song Fangfang, Song Fengju, Huang Yubei

机构信息

Department of Epidemiology and Biostatistics, Key Laboratory of Molecular Cancer Epidemiology (Tianjin), National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China.

Department of Epidemiology and Biostatistics, School of Public Health, Tianjin Medical University, Tianjin, China.

出版信息

Front Genet. 2024 Aug 1;15:1387588. doi: 10.3389/fgene.2024.1387588. eCollection 2024.

DOI:10.3389/fgene.2024.1387588
PMID:39149591
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11324495/
Abstract

BACKGROUND

Although the risk of prostate cancer (PCa) varies across different ages and genetic risks, it's unclear about the effects of genetic-specific and age-specific prostate-specific antigen (PSA) screening for PCa.

METHODS

Weighed and unweighted polygenic risk scores (PRS) were constructed to classify the participants from the PLCO trial into low- or high-PRS groups. The age-specific and PRS-specific cut-off values of PSA for PCa screening were determined with time-dependent receiver-operating-characteristic curves and area-under-curves (tdAUCs). Improved screening strategies integrating PRS-specific and age-specific cut-off values of PSA were compared to traditional PSA screening on accuracy, detection rates of high-grade PCa (Gleason score ≥7), and false positive rate.

RESULTS

Weighted PRS with 80 SNPs significantly associated with PCa was determined as the optimal PRS, with an AUC of 0.631. After stratifying by PRS, the tdAUCs of PSA with a 10-year risk of PCa were 0.818 and 0.816 for low- and high-PRS groups, whereas the cut-off values were 1.42 and 1.62 ng/mL, respectively. After further stratifying by age, the age-specific cut-off values of PSA were relatively lower for low PRS (1.42, 1.65, 1.60, and 2.24 ng/mL for aged <60, 60-64, 65-69, and ≥70 years) than high PRS (1.48, 1.47, 1.89, and 2.72 ng/mL). Further analyses showed an obvious interaction of positive PSA and high PRS on PCa incidence and mortality. Very small difference in PCa risk were observed among subgroups with PSA (-) across different age and PRS, and PCa incidence and mortality with PSA (+) significantly increased as age and PRS, with highest risk for high-PRS/PSA (+) in participants aged ≥70 years [HRs (95%CI): 16.00 (12.62-20.29) and 19.48 (9.26-40.96)]. The recommended screening strategy reduced 12.8% of missed PCa, ensured high specificity, but not caused excessive false positives than traditional PSA screening.

CONCLUSION

Risk-adapted screening integrating PRS-specific and age-specific cut-off values of PSA would be more effective than traditional PSA screening.

摘要

背景

尽管前列腺癌(PCa)的风险在不同年龄和遗传风险人群中有所差异,但基因特异性和年龄特异性前列腺特异性抗原(PSA)筛查对PCa的影响尚不清楚。

方法

构建加权和未加权多基因风险评分(PRS),将前列腺、肺癌、结直肠癌和卵巢癌(PLCO)试验的参与者分为低PRS组或高PRS组。通过时间依赖性受试者工作特征曲线和曲线下面积(tdAUC)确定PCa筛查中PSA的年龄特异性和PRS特异性临界值。将整合了PRS特异性和年龄特异性PSA临界值的改进筛查策略与传统PSA筛查在准确性、高级别PCa(Gleason评分≥7)的检出率和假阳性率方面进行比较。

结果

确定80个与PCa显著相关的单核苷酸多态性(SNP)的加权PRS为最佳PRS,AUC为0.631。按PRS分层后,低PRS组和高PRS组中10年PCa风险的PSA的tdAUC分别为0.818和0.816,而临界值分别为1.42和1.62 ng/mL。进一步按年龄分层后,低PRS组的PSA年龄特异性临界值相对较低(年龄<60、60 - 64、65 - 69和≥70岁时分别为1.42、1.65、1.60和2.24 ng/mL),高于高PRS组(分别为1.48、1.47、1.89和2.72 ng/mL)。进一步分析显示,PSA阳性和高PRS在PCa发病率和死亡率上存在明显的交互作用。在不同年龄和PRS的PSA(-)亚组中,PCa风险差异很小,而PSA(+)的PCa发病率和死亡率随年龄和PRS显著增加,≥70岁参与者中高PRS/PSA(+)的风险最高[风险比(95%置信区间):16.00(12.62 - 20.29)和19.48(9.26 - 40.96)]。推荐的筛查策略减少了12.8%的PCa漏诊,确保了高特异性,且不会比传统PSA筛查导致过多的假阳性。

结论

整合PRS特异性和年龄特异性PSA临界值的风险适应性筛查比传统PSA筛查更有效。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3711/11324495/41eaccd9791f/fgene-15-1387588-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3711/11324495/58a90ba82e08/fgene-15-1387588-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3711/11324495/508eb7c86696/fgene-15-1387588-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3711/11324495/e3748c0ec6d4/fgene-15-1387588-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3711/11324495/41eaccd9791f/fgene-15-1387588-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3711/11324495/58a90ba82e08/fgene-15-1387588-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3711/11324495/508eb7c86696/fgene-15-1387588-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3711/11324495/e3748c0ec6d4/fgene-15-1387588-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3711/11324495/41eaccd9791f/fgene-15-1387588-g004.jpg

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