Factors Influencing the False Positive Rate in CT Lung Cancer Screening

Purpose: To identify factors influencing the likelihood of a false positive lung cancer screening (LCS) computed tomography (CT), which may lead to increased costs and patient anxiety. Materials and Methods: In this retrospective study, we examined all LCS CTs performed across our healthcare network from 2014 to 2018, recording Lung-RADS category and diagnosis of lung cancer. A false positive was defined by Lung-RADS 3-4X and no diagnosis of lung cancer within 1 year. Patient demographics and smoking history, presence of emphysema, diagnosis of chronic obstructive pulmonary disease, radiologist years of experience and annual volume, income level by patient zip code, and screening institution were evaluated in a multivariate logistic regression model for false positive exams. Results: A total of 5835 LCS CTs were included from 3735 patients. Lung cancer was diagnosed in 142 cases (2%). Of the LCS CTs, 905 (16%) were positive by Lung-RADS, and 766 (13%) represented false positives. Logistic regression analysis showed that screening institution (odds ratios [OR] 0.91 - 2.43), baseline scan (OR 1.43), radiologist experience (OR 0.59), patient age (OR 2.08), diagnosis of chronic obstructive pulmonary disease (OR 1.34), presence of emphysema (OR 1.32), and income level (OR 0.43) were significant predictors of false positives. Conclusion: A number of patient-specific and site/radiologist-specific factors influence the false positive rate in CT LCS. In particular, radiologists with less experience had a higher false positive rate. Screening programs may wish to develop quality assurance programs to compare the false positive rates of their radiologists to national benchmarks.

Automated summary

This study investigated factors influencing the false positive rate in CT LCS and found that patient-specific and site/radiologist-specific factors significantly affected the results, particularly with less experienced radiologists having a higher false positive rate. Screening programs may compare their radiologists' false positive rates to national benchmarks through quality assurance programs.