Yang Shuang, Liang Muxuan, Mehta Hiren J, Salloum Ramzi G, Braithwaite Dejana, Wu Yonghui, Islam Jessica, Zhang Xuhong, Shih Ya-Chen Tina, Huo Jinhai, Bian Jiang, Guo Yi
Department of Health Outcomes and Biomedical Informatics, College of Medicine, University of Florida, Gainesville, FL, USA.
Cancer Informatics Shared Resource, University of Florida Health Cancer Center, Gainesville, FL, USA.
Sci Rep. 2025 Aug 9;15(1):29172. doi: 10.1038/s41598-025-15053-1.
We examined the association of pulmonary nodule characteristics with adherence to follow-up low-dose computed tomography (LDCT) after the initial screening in lung cancer screening. Using 2014-2021 electronic health record data from a large integrated health system, we analyzed adherence to Lung Imaging Reporting and Data System (Lung-RADS) follow-up recommendations, considering socio-demographic, clinical factors, and natural language processing-extracted nodule characteristics. Multivariable logistic regression models assessed the impact of these factors on adherence to follow-up LDCT. Among 2,673 individuals (mean age = 66.8 ± 5.9 years), overall adherence was 27.6%, with rates of 24.2%, 27.5%, 26.7%, and 64.0% for Lung-RADS categories 1-4 A. A race-ethnicity disparity in adherence was observed among category 1, with non-Hispanic blacks less likely to adhere than non-Hispanic whites (OR[95% CI] = 0.59[0.41-0.85]). Among patients in categories 2 to 4 A, category 4 A was significantly more likely to adhere (OR[95% CI] = 3.18[1.86-5.40]) and having more nodules increased adherence (OR[95% CI] = 1.12[1.09-1.14]). Adherence to follow-up LDCT is suboptimal, driven by patient and nodule characteristics, and influenced by how physicians communicated initial CT results. These findings underscore the need for structured screening programs and consistent follow-up protocols to improve adherence and ensure effective lung cancer screening.
我们在肺癌筛查的初次筛查后,研究了肺结节特征与后续低剂量计算机断层扫描(LDCT)依从性之间的关联。利用来自大型综合医疗系统的2014 - 2021年电子健康记录数据,我们分析了对肺部影像报告和数据系统(Lung-RADS)随访建议的依从性,同时考虑了社会人口统计学、临床因素以及通过自然语言处理提取的结节特征。多变量逻辑回归模型评估了这些因素对后续LDCT依从性的影响。在2673名个体(平均年龄 = 66.8 ± 5.9岁)中,总体依从率为27.6%,Lung-RADS 1 - 4A类别的依从率分别为24.2%、27.5%、26.7%和64.0%。在1类中观察到依从性存在种族差异,非西班牙裔黑人比非西班牙裔白人更不太可能依从(比值比[95%置信区间]= 0.59[0.41 - 0.85])。在2至4A类患者中,4A类显著更有可能依从(比值比[95%置信区间]= 3.18[1.86 - 5.40]),并且结节数量增加会提高依从性(比值比[95%置信区间]= 1.12[1.09 - 1.14])。后续LDCT的依从性欠佳,受患者和结节特征驱动,并受到医生传达初始CT结果方式的影响。这些发现强调了需要有结构化的筛查计划和一致的随访方案,以提高依从性并确保有效的肺癌筛查。
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