Lung Cancer Absolute Risk Models for Mortality in an Asian Population using the China Kadoorie Biobank.
Lung Cancer Absolute Risk Models for Mortality in an Asian Population using the China Kadoorie Biobank.
复制标题
使用中国嘉道理生物库建立亚洲人群肺癌死亡率绝对风险模型。
DOI：
10.1093/jnci/djac176
复制
发表时间：
2022
期刊：
影响因子：
--
通讯作者：
Hung,RayjeanJ
中科院分区：
文献类型：
--
作者：
Warkentin,MatthewT;Tammemägi,MartinC;Espin-Garcia,Osvaldo;Budhathoki,Sanjeev;Liu,Geoffrey;Hung,RayjeanJ
背景肺癌是全球癌症死亡的主要原因。通过基于风险的筛查进行早期发现可以显著改善预后。然而，大多数风险模型是在北美吸烟者队列中开发的，而对从不吸烟者的风险特征知之甚少，这代表了肺癌的比例越来越大，特别是在亚洲人群中。我们建立了亚洲肺癌绝对风险模型（ALARM）肺癌死亡率使用灵活的参数生存模型，分别为从不吸烟者和曾经吸烟者，占死亡率的竞争风险。模型的性能进行了评估，在一个25%的保留测试集使用的时间依赖性的曲线下面积，并通过比较模型预测和观察到的风险calibration.ResultsPredictors在从不吸烟的肺癌死亡率模型评估的人口统计学，体重指数，肺功能，肺气肿或支气管炎，个人或家族史的癌症，被动吸烟，和室内空气污染。曾经吸烟者模型还评估了吸烟史。对于ALARM-从不吸烟者和ALARM-曾经吸烟者，测试集中的5年曲线下面积分别为0.77（95%置信区间= 0.73 - 0.80）和0.81（95%置信区间= 0.79 - 0.84）。最大的5年的风险从来没有和曾经吸烟者为2.6%和12.7%，respectively.ConclusionsThis研究是第一个专门为亚洲人群开发风险模型分别从来没有和曾经吸烟者。我们的模型准确地识别出肺癌死亡高风险的亚洲人，并可能识别出那些风险超过常见资格阈值的人，他们可能从筛查中受益。
BackgroundLung cancer is the leading cause of cancer mortality globally. Early detection through risk-based screening can markedly improve prognosis. However, most risk models were developed in North American cohorts of smokers, whereas less is known about risk profiles for never-smokers, which represent a growing proportion of lung cancers, particularly in Asian populations.MethodsBased on the China Kadoorie Biobank, a population-based prospective cohort of 512 639 adults with up to 12 years of follow-up, we built Asian Lung Cancer Absolute Risk Models (ALARM) for lung cancer mortality using flexible parametric survival models, separately for never and ever-smokers, accounting for competing risks of mortality. Model performance was evaluated in a 25% hold-out test set using the time-dependent area under the curve and by comparing model-predicted and observed risks for calibration.ResultsPredictors assessed in the never-smoker lung cancer mortality model were demographics, body mass index, lung function, history of emphysema or bronchitis, personal or family history of cancer, passive smoking, and indoor air pollution. The ever-smoker model additionally assessed smoking history. The 5-year areas under the curve in the test set were 0.77 (95% confidence interval = 0.73 to 0.80) and 0.81 (95% confidence interval = 0.79 to 0.84) for ALARM-never-smokers and ALARM-ever smokers, respectively. The maximum 5-year risk for never and ever-smokers was 2.6% and 12.7%, respectively.ConclusionsThis study is among the first to develop risk models specifically for Asian populations separately for never and ever-smokers. Our models accurately identify Asians at high risk of lung cancer death and may identify those with risks exceeding common eligibility thresholds who may benefit from screening.