Patient and nodule characteristics associated with adherence to lung cancer screening in a large integrated healthcare system

S Shuang Yang (Micro−Nano Engineering Sciences Research Center, School of Mechanical Engineering) M Muxuan Liang H Hiren J. Mehta R Ramzi G. Salloum D Dejana Braithwaite Y Yonghui Wu J Jessica Islam X Xuhong Zhang Y Ya-Chen Tina Shih J Jinhai Huo J Jiang Bian Y Yi Guo

Abstract

Abstract 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.

Article Details

Volume / Issue Vol. 15, Issue 1
Published August 09, 2025
ISSN 2045-2322
Publisher Nature Portfolio

Journal Info

Scientific Reports

Nature Portfolio

ISSN: 2045-2322 Open Access Life Sciences

Authors (12)

S

Shuang Yang

Micro−Nano Engineering Sciences Research Center, School of Mechanical Engineering

M

Muxuan Liang

H

Hiren J. Mehta

R

Ramzi G. Salloum

D

Dejana Braithwaite

Y

Yonghui Wu

J

Jessica Islam

X

Xuhong Zhang

Y

Ya-Chen Tina Shih

J

Jinhai Huo

J

Jiang Bian

Y

Yi Guo