Division of Chest Medicine, Department of Internal Medicine, Taichung Veterans General Hospital, Taichung, Taiwan.
School of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan.
JCO Precis Oncol. 2024 Oct;8:e2400236. doi: 10.1200/PO.24.00236. Epub 2024 Oct 2.
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.
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.
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% 2.5%, = .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.
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.
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。非小细胞肺癌（NSCLC）发生中遗传变异的作用越来越受到重视。在这项研究中，我们旨在探讨多基因风险评分（PRS）在预测 NSCLC 和提高筛查计划效果方面的潜在益处。
我们进行了一项回顾性队列研究，纳入了无肺癌既往诊断且随后接受 LDCT 肺癌筛查的参与者。这些参与者的遗传数据来自台湾精准医学计划项目。我们采用 Dai 等人报道的与 NSCLC 风险相关的 19 个易感性基因座的全基因组关联研究衍生的 PRS 计算模型。
我们共研究了 2287 名参与者（1197 名男性，1090 名女性）。在随访期间，更多的女性参与者发展为 NSCLC（4.4%比 2.5%，.015）。男性参与者中 NSCLC 诊断的唯一危险因素是年龄。在女性参与者中，NSCLC 诊断的独立危险因素是年龄（调整后的危险比[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]）。我们使用接收者操作特征曲线（ROC）显示传统模型的 AUC 值为 0.741。通过进一步纳入 PRS，AUC 升高至 0.778。
PRS 用于 NSCLC 预测的评估有望提高台湾尤其是女性肺癌筛查的效果。通过纳入遗传信息，可以根据个体 NSCLC 的风险定制筛查标准。
