Validation of a Deep Learning-Based Model to Predict Lung Cancer Risk Using Chest Radiographs and Electronic Medical Record Data

• Published in: JAMA network open 2022-12, Vol.5 (12), p.e2248793-e2248793
• Main Authors: Raghu, Vineet K, Walia, Anika S, Zinzuwadia, Aniket N, Goiffon, Reece J, Shepard, Jo-Anne O, Aerts, Hugo J W L, Lennes, Inga T, Lu, Michael T
• Format: Article
• Language: English
• Subjects: Aged; Deep Learning; Early Detection of Cancer; Electronic Health Records; Female; Humans; Lung cancer; Lung Neoplasms - diagnostic imaging; Lung Neoplasms - epidemiology; Male; Medical records; Medical screening; Medicare; Middle Aged; Oncology; Online Only; Original Investigation; United States
• ISSN: 2574-3805; 2574-3805
• DOI: 10.1001/jamanetworkopen.2022.48793

Lung cancer screening with chest computed tomography (CT) prevents lung cancer death; however, fewer than 5% of eligible Americans are screened. CXR-LC, an open-source deep learning tool that estimates lung cancer risk from existing chest radiograph images and commonly available electronic medical record (EMR) data, may enable automated identification of high-risk patients as a step toward improving lung cancer screening participation. To validate CXR-LC using EMR data to identify individuals at high-risk for lung cancer to complement 2022 US Centers for Medicare & Medicaid Services (CMS) lung cancer screening eligibility guidelines. This prognostic study compared CXR-LC estimates with CMS screening guidelines using patient data from a large US hospital system. Included participants were persons who currently or formerly smoked cigarettes with an outpatient posterior-anterior chest radiograph between January 1, 2013, and December 31, 2014, with no history of lung cancer or screening CT. Data analysis was performed between May 2021 and June 2022. CXR-LC lung cancer screening eligibility (previously defined as having a 3.297% or greater 12-year risk) based on inputs (chest radiograph image, age, sex, and whether currently smoking) extracted from the EMR. 6-year incident lung cancer. A total of 14 737 persons were included in the study population (mean [SD] age, 62.6 [6.8] years; 7154 [48.5%] male; 204 [1.4%] Asian, 1051 [7.3%] Black, 432 [2.9%] Hispanic, 12 330 [85.2%] White) with a 2.4% rate of incident lung cancer over 6 years (361 patients with cancer). CMS eligibility could be determined in 6277 patients (42.6%) using smoking pack-year and quit-date from the EMR. Patients eligible by both CXR-LC and 2022 CMS criteria had a high rate of lung cancer (83 of 974 patients [8.5%]), higher than those eligible by 2022 CMS criteria alone (5 of 177 patients [2.8%]; P