Prosserman Center for Population Health Research, Lunenfeld-Tanenbaum Research Institute, Sinai Health, Toronto, ON, Canada.
Department of Public Health Sciences, Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada.
J Natl Cancer Inst. 2022 Dec 8;114(12):1665-1673. doi: 10.1093/jnci/djac176.
Lung 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.
Based 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.
Predictors 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.
This 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.
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检测可以显著改善预后。然而，大多数风险模型都是在北美吸烟人群队列中开发的，而对于从不吸烟者的风险特征了解较少，从不吸烟者在亚洲人群中越来越多，是肺癌的主要组成部分。
基于中国慢性病前瞻性研究，这是一项包含 512639 名成年人的基于人群的前瞻性队列研究，随访时间长达 12 年，我们使用灵活的参数生存模型为从不吸烟者和曾经吸烟者分别建立了亚洲肺癌绝对风险模型（ALARM），以预测肺癌死亡率，同时考虑了死亡率的竞争风险。我们使用时间依赖性曲线下面积和校准模型预测风险与观察风险的比较来评估模型在 25%保留测试集中的性能。
从不吸烟者肺癌死亡率模型中评估的预测因素包括人口统计学特征、体重指数、肺功能、肺气肿或支气管炎病史、个人或家族癌症史、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。在测试集中，5 年的曲线下面积分别为 0.77（95%置信区间=0.73 至 0.80）和 0.81（95%置信区间=0.79 至 0.84），用于 ALARM-从不吸烟者和 ALARM-曾经吸烟者。从不吸烟者和曾经吸烟者的最高 5 年风险分别为 2.6%和 12.7%。
这项研究是首次专门为亚洲人群分别为从不吸烟者和曾经吸烟者开发风险模型。我们的模型准确地识别出了肺癌死亡风险较高的亚洲人，并且可能识别出了风险超过常见入选标准的人群，这些人群可能受益于筛查。
