为了预测肺癌和死亡率，评估自动化冠状动脉钙化（CAC）和定量肺气肿（低密度区域百分比[%LAA]）在肺癌筛查中的作用；探索%LAA，CAC和一秒钟内强制呼气值（FEV1）之间的相关性以及%LAA对气流阻塞的识别能力。利用人工智能软件分析BioMILD试验的基线低剂量计算机断层扫描。进行单因素和多因素分析，以评估%LAA和CAC的预测价值。对3个嵌套模型进行Harrell C统计和时间相关下的曲线下面积（AUC）报告（模型调查：年龄，性别，吸烟年数；模型调查-LDCT：模型调查加上%LAA和CAC；最终模型：模型调查-LDCT加上选定的混杂因素）。利用Pearson相关系数和AUC-受试者工作特征曲线分别测试 %LAA，CAC和FEV1之间的相关性和%LAA对气流阻塞的识别能力。总共有4098名志愿者参加。%LAA和CAC独立地预测了6年的全因死亡（最终权值比[HR]，1.14每个%LAA四分位差[ IQR]增加[95％CI，1.05-1.23]，CAC≥400为2.13[95％CI，1.36-3.28]），非癌症（最终权值比[HR]，1.25每个%LAA IQR增加[95％CI，1.11-1.37]，CAC≥400为3.22[95％CI，1.62-6.39]），心血管（最终权值比[HR]，1.25每个%LAA IQR增加[95％CI，1.00-1.46]，CAC≥400为4.66[95％CI，1.80-12.58]）死亡率，在模型调查-LDCT中的一致性概率比模型调查高（P <0.05）。调整后，在LC发生率上未发现显着关联。两个生物标志物均与FEV1呈负相关（P <0.01）。%LAA可识别气流阻塞，其识别能力适中（AUC，0.738）。自动化CAC和%LAA相对于年龄，性别和吸烟年数的预测信息可用于预测死亡率，但不可用于预测LC发生率。两个生物标志物与FEV1呈负相关，%LAA可用于适度识别气流阻塞。版权所有© 2023作者。 Wolters Kluwer Health公司发表。

To assess automated coronary artery calcium (CAC) and quantitative emphysema (percentage of low attenuation areas [%LAA]) for predicting mortality and lung cancer (LC) incidence in LC screening. To explore correlations between %LAA, CAC, and forced expiratory value in 1 second (FEV1) and the discriminative ability of %LAA for airflow obstruction.Baseline low-dose computed tomography scans of the BioMILD trial were analyzed using an artificial intelligence software. Univariate and multivariate analyses were performed to estimate the predictive value of %LAA and CAC. Harrell C-statistic and time-dependent area under the curve (AUC) were reported for 3 nested models (Modelsurvey: age, sex, pack-years; Modelsurvey-LDCT: Modelsurvey plus %LAA plus CAC; Modelfinal: Modelsurvey-LDCT plus selected confounders). The correlations between %LAA, CAC, and FEV1 and the discriminative ability of %LAA for airflow obstruction were tested using the Pearson correlation coefficient and AUC-receiver operating characteristic curve, respectively.A total of 4098 volunteers were enrolled. %LAA and CAC independently predicted 6-year all-cause (Modelfinal hazard ratio [HR], 1.14 per %LAA interquartile range [IQR] increase [95% CI, 1.05-1.23], 2.13 for CAC ≥400 [95% CI, 1.36-3.28]), noncancer (Modelfinal HR, 1.25 per %LAA IQR increase [95% CI, 1.11-1.37], 3.22 for CAC ≥400 [95%CI, 1.62-6.39]), and cardiovascular (Modelfinal HR, 1.25 per %LAA IQR increase [95% CI, 1.00-1.46], 4.66 for CAC ≥400, [95% CI, 1.80-12.58]) mortality, with an increase in concordance probability in Modelsurvey-LDCT compared with Modelsurvey (P<0.05). No significant association with LC incidence was found after adjustments. Both biomarkers negatively correlated with FEV1 (P<0.01). %LAA identified airflow obstruction with a moderate discriminative ability (AUC, 0.738).Automated CAC and %LAA added prognostic information to age, sex, and pack-years for predicting mortality but not LC incidence in an LC screening setting. Both biomarkers negatively correlated with FEV1, with %LAA enabling the identification of airflow obstruction with moderate discriminative ability.Copyright © 2023 The Author(s). Published by Wolters Kluwer Health, Inc.