Automated Coronary Artery Calcium and Quantitative Emphysema in Lung Cancer Screening: Association With Mortality, Lung Cancer Incidence, and Airflow Obstruction.
Automated Coronary Artery Calcium and Quantitative Emphysema in Lung Cancer Screening: Association With Mortality, Lung Cancer Incidence, and Airflow Obstruction.
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DOI：
10.1097/rti.0000000000000698
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发表时间：
2023-07-01
影响因子：
3.3
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中科院分区：
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在LC筛查中评估自动冠状动脉钙化(CAC)和定量肺气肿(低密度区百分比[%LAA])预测死亡率和肺癌(LC)发病率。探讨%LAA、CAC与1秒用力呼气值(FEV1)的相关性及%LAA对气流阻塞的判别能力。使用人工智能软件分析了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估计%LAA和CAC的预测值。报告3个嵌套模型的Harrell C统计量和曲线下时间依赖面积(AUC)(模型调查：年龄、性别、包年；模型调查-LDCT：模型调查+%LAA+CAC；模型最终：模型调查-LDCT+选定的混杂因素)。分别用皮尔逊相关系数和AUC-受试者工作特性曲线检验%LAA、CAC和FEV1的相关性以及%LAA对气流阻塞的判别能力。共有4098名志愿者参加。%LAA和CAC独立预测了6年的全因(模型最终危险比[HR]，1.14每%LAA四分位数范围[IQR]增加[95%CI，1.05-1.23]，CAC≥4002.13[95%CI，1.36-3.28])，非癌症(模型最终HR，1.25PER%LAA IQR增加[95%CI，1.11-1.37]，CAC≥4003.22[95%CI，1.62-6.39])，以及心血管(模型最终HR，1.25/%LAA IQR增加[95%CI，1.00-1.46]，4.66对于CAC≥400，死亡率[95%CI，1.80-12.58])，与模型调查相比，模型调查-LDCT的符合率增加(P<；0.05)。经校正后，未发现与LC发病率有显著关联。两项指标均与FEV1呈负相关(P<；0.01)。%LAA识别气流阻塞，具有中等辨别能力(AuC，0.738)。在LC筛查环境中，自动CAC和%LAA增加了年龄、性别和包年的预后信息，用于预测死亡率，而不是LC发病率。这两个生物标志物与FEV1呈负相关，%LAA有助于识别气流阻塞，具有中等的区分能力。
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.