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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. [ABSTRACT FROM AUTHOR]

Purpose: To test the performance of the American College of Chest Physicians (ACCP) and British Thoracic Society (BTS) algorithms to stratify high-risk nodules identified at lung cancer screening.Method and Materials: Patients with Lung-RADS category 4 nodules identified on lung cancer screening computed tomography (CT) between March 2014 and August 2018 were identified, and a subset of 150 were randomly selected. Nodule characteristics and, if available, fluorodeoxyglucose (FDG) uptake on positron emission tomography (PET)-CT scan were recorded. Radiologists blinded to final diagnosis and downstream testing performed five-point visual assessment score for probability of nodule malignancy; their accuracies are averaged below. Probabilities of malignancy according to Brock and Herder models were calculated. ACCP and BTS algorithms were applied to the nodules.Results: Final diagnosis of malignancy was made in 65/150 (43%) of patients. The sensitivity, specificity and accuracy for nodule malignancy were: radiologist visual score (92%, 85%, 88%); BTS (76%, 91%, 85%); ACCP (63%, 89%, 78%); and Brock calculator (77%, 71%, 73%). The sensitivity, specificity, and accuracy for nodule malignancy in patients with FDG PET-CT scan (n = 78) were: FDG uptake (91%, 64%, 83%); Herder probability (91%, 68%, 83%); radiologist visual score (93%, 69%, 86%); BTS (84%, 64%, 78%); Brock probability (82%, 50%, 72%); and ACCP (68%, 59%, 65%).Conclusion: Thoracic radiologist visual analysis yielded the greatest accuracy for nodule triage in the entire cohort. BTS performed better than ACCP guidelines and both performed better than the Brock model alone. [ABSTRACT FROM AUTHOR]

In the optimism surrounding screening for lung cancer, the downsides of screening should not be ignored. The article examines the dark side of screening, which is not an unmitigated good. [ABSTRACT FROM AUTHOR]