据报道，结合风险因素的易感性遗传变异可以增强多基因风险评分（PRS）的风险预测。然而，目前尚不清楚这种方法对肺癌是否有效。因此，我们的目的是构建肺癌元多基因风险评分（metaPRS），并评估其对肺癌风险的预测和对风险分层的影响。在这里，总共使用了 2180 个基因变异来分别开发 9 个针对肺癌的 PRS、3 个针对不同组织病理学亚型的 PRS 以及 17 个针对肺癌相关危险因素的 PRS。然后使用英国生物库中的弹性网 Cox 回归模型将这些 PRS 整合到肺癌的 MetaPRS 中 (N = 442,508)。此外，metaPRS 的预测效果在前列腺癌、肺癌、结直肠癌和卵巢癌 (PLCO) 癌症筛查试验中进行了评估 (N = 108,665)。 metaPRS 与肺癌风险相关，每增加一个标准差，风险比为 1.33（95% 置信区间：1.27-1.39）。与 PLCO 中之前的 9 个 PRS（C 指数：0.513-0.564）相比，metaPRS 显示了最高的 C 指数（0.580）。此外，临床风险模型预测的中风险组（1.34%-1.51%）中具有中高遗传风险的吸烟者6年平均绝对肺癌风险超过临床风险模型阈值（≥1.51%） 。将metaPRS添加到临床风险模型中显示PLCO的净重分类持续改善（连续NRI = 6.50%）。这些发现表明，与之前的 PRS 相比，metaPRS 可以提高肺癌的预测效率，并细化肺癌的风险分层。© 2024 UICC。

Incorporating susceptibility genetic variants of risk factors has been reported to enhance the risk prediction of polygenic risk score (PRS). However, it remains unclear whether this approach is effective for lung cancer. Hence, we aimed to construct a meta polygenic risk score (metaPRS) of lung cancer and assess its prediction of lung cancer risk and implication for risk stratification. Here, a total of 2180 genetic variants were used to develop nine PRSs for lung cancer, three PRSs for different histopathologic subtypes, and 17 PRSs for lung cancer-related risk factors, respectively. These PRSs were then integrated into a metaPRS for lung cancer using the elastic-net Cox regression model in the UK Biobank (N = 442,508). Furthermore, the predictive effects of the metaPRS were assessed in the prostate, lung, colorectal, and ovarian (PLCO) cancer screening trial (N = 108,665). The metaPRS was associated with lung cancer risk with a hazard ratio of 1.33 (95% confidence interval: 1.27-1.39) per standard deviation increased. The metaPRS showed the highest C-index (0.580) compared with the previous nine PRSs (C-index: 0.513-0.564) in PLCO. Besides, smokers in the intermediate risk group predicted by the clinical risk model (1.34%-1.51%) with the intermediate-high genetic risk had a 6-year average absolute lung cancer risk that exceeded the clinical risk model threshold (≥1.51%). The addition of metaPRS to the clinical risk model showed continuous net reclassification improvement (continuous NRI = 6.50%) in PLCO. These findings suggest the metaPRS can improve the predictive efficiency of lung cancer compared with the previous PRSs and refine risk stratification for lung cancer.© 2024 UICC.