Education Level Predicts Appropriate Follow-Up of Incidental Findings From Lung Cancer Screening.

Abstact

The aim of this study was to identify predictors of appropriate follow-up for clinically significant incidental findings (IFs) detected with low-dose CT during lung cancer screening.

Charts of 1,458 prospectively enrolled lung screening patients from January 1, 2015, to October 31, 2018, were reviewed. IFs, other than coronary artery calcification and emphysema, were identified. ACR practice guidelines defined appropriate patient follow-up. Patient demographic and social characteristics were obtained from the initial shared decision-making visit and the electronic medical record. Factors of interest included age, gender, race, education level, and insurance status. Education level was reported as high school graduate or less or education past high school. A multivariate logistic regression was estimated to assess patient factors associated with appropriate follow-up.

One hundred thirty-eight participants (9%) with 141 actionable IFs were identified. The overall appropriate follow-up rate was 82%. The most common IFs were renal lesions (16%), dilated thoracic aorta (10%), and pulmonary fibrosis (10%). Univariate analysis of appropriate patient follow-up revealed a significant difference for education level (P = .02). A greater than high school education remained strongly associated with appropriate follow-up after controlling for other demographic factors.

Appropriate patient follow-up of clinically significant IFs from lung cancer screening is a well-recognized avenue to improve population health. Education level is a significant independent predictor of appropriate follow-up of IFs, whether as a surrogate for low socioeconomic status or as an indication of health literacy. To address these realities, lung screening shared decision making should adapt to consider health care access and health literacy.

Authors
  • Cook JP
  • Deppen SA
  • Haddad D
  • Kapoor S
  • Paulson AB
  • Sandler KL
PubMed ID
Appears In
J Am Coll Radiol, 2020, 17 (5)