Using a Polygenic Risk Score to Improve the Risk Prediction of Non-Small Cell Lung Cancer in Taiwan.

IF 5.3 2区 医学 Q1 ONCOLOGY
JCO precision oncology Pub Date : 2024-10-01 Epub Date: 2024-10-02 DOI:10.1200/PO.24.00236
Po-Hsin Lee, I-Chieh Chen, Yi-Ming Chen, Tzu-Hung Hsiao, Jeng-Sen Tseng, Yen-Hsiang Huang, Kuo-Hsuan Hsu, Ho Lin, Tsung-Ying Yang, Yu-Hsuan Joni Shao
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引用次数: 0

Abstract

Purpose: Low-dose computed tomography (LDCT) can help reducing lung cancer mortality. In Taiwan, the existing screening criteria revolve around smoking habits and family history of lung cancer. The role of genetic variation in non-small cell lung cancer (NSCLC) development is increasingly recognized. In this study, we aimed to investigate the potential benefits of polygenic risk scores (PRSs) in predicting NSCLC and enhancing the effectiveness of screening programs.

Methods: We conducted a retrospective cohort study that included participants without prior diagnosis of lung cancer and later received LDCT for lung cancer screening. Genetic data for these participants were obtained from the project of Taiwan Precision Medicine Initiative. We adopted the model of genome-wide association study-derived PRS calculation using 19 susceptibility loci associated with the risk of NSCLC as reported by Dai et al.

Results: We studied a total of 2,287 participants (1,197 male, 1,090 female). More female participants developed NSCLC during the follow-up period (4.4% v 2.5%, P = .015). The only risk factor of NSCLC diagnosis among male participants was age. Among female participants, independent risk factors of NSCLC diagnosis were age (adjusted hazard ratio [aHR], 1.08 [95% CI, 1.04 to 1.11]), a family history of lung cancer (aHR, 3.21 [95% CI, 1.78 to 5.77]), and PRS fourth quartile (aHR, 2.97 [95% CI, 1.25 to 7.07]). We used the receiver operating characteristics to show an AUC value of 0.741 for the conventional model. With the further incorporation of PRS, the AUC rose to 0.778.

Conclusion: The evaluation of PRS for NSCLC prediction holds promise for enhancing the effectiveness of lung cancer screening in Taiwan especially in women. By incorporating genetic information, screening criteria can be tailored to identify individuals at higher risks of NSCLC.

使用多基因风险评分改进台湾非小细胞肺癌的风险预测。
目的:低剂量计算机断层扫描(LDCT)有助于降低肺癌死亡率。在台湾,现有的筛查标准主要围绕吸烟习惯和肺癌家族史。基因变异在非小细胞肺癌(NSCLC)发展中的作用日益得到认可。本研究旨在探讨多基因风险评分(PRS)在预测非小细胞肺癌和提高筛查计划有效性方面的潜在益处:我们进行了一项回顾性队列研究,研究对象包括既往未确诊肺癌、后来接受了 LDCT 肺癌筛查的参与者。这些参与者的基因数据来自台湾精准医疗计划项目。我们采用了 Dai 等人报告的全基因组关联研究得出的 PRS 计算模型,使用了 19 个与 NSCLC 风险相关的易感基因位点:我们共研究了 2,287 名参与者(男性 1,197 人,女性 1,090 人)。更多女性参与者在随访期间罹患了 NSCLC(4.4% 对 2.5%,P = .015)。男性参与者确诊 NSCLC 的唯一风险因素是年龄。在女性参与者中,确诊 NSCLC 的独立危险因素是年龄(调整后危险比 [aHR],1.08 [95% CI,1.04 至 1.11])、肺癌家族史(aHR,3.21 [95% CI,1.78 至 5.77])和 PRS 第四四分位数(aHR,2.97 [95% CI,1.25 至 7.07])。我们使用接收器操作特征显示,传统模型的 AUC 值为 0.741。在进一步纳入 PRS 后,AUC 上升到 0.778:对预测 NSCLC 的 PRS 进行评估,有望提高台湾肺癌筛查(尤其是女性肺癌筛查)的有效性。通过纳入基因信息,筛查标准可以量身定制,以识别罹患 NSCLC 风险较高的个体。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
9.10
自引率
4.30%
发文量
363
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