protocolSection identificationModule nctId: NCT06295497, orgStudyIdInfo id: LC-SHIELD, briefTitle: Lung Cancer Screening by Artificial Intelligence Device, statusModule overallStatus: NOT_YET_RECRUITING, startDateStruct date: 2024-04-01, primaryCompletionDateStruct date: 2027-06-30, completionDateStruct date: 2027-12-31, studyFirstPostDateStruct date: 2024-03-06, lastUpdatePostDateStruct date: 2024-03-06, sponsorCollaboratorsModule leadSponsor name: Chinese University of Hong Kong, class: OTHER, descriptionModule briefSummary: Lung cancer screening is currently not recommended in non-smokers due to paucity of evidence. Emerging evidence suggests that first-degree family history is a strong risk factor for lung cancer in Asian non-smokers. In Asia, lack of resource is a major challenge in successful implementation of lung cancer screening. Artificial intelligence (AI) is a promising tool to overcome this resource. In this study, we aim to study the clinical utility and demonstrate the feasibility of using an AI assisted programme for lung cancer screening in Asian non-smokers with a positive family history. This is a single-arm non-randomized lung cancer screening study. 1000 non-smokers, age 50 to 75 year old, with a first-degree family history of lung cancer, will be enrolled. Participants will undergo low does computed tomography (LDCT) of thorax and blood taking at enrolment. LDCT films will be interpreted by AI softwares for presence of lung nodules. Participants with lung nodules will be further investigated and followed up according to the risk of malignancy. The primary endpoint is the prevalence of early-staged lung cancer detected by first-round LDCT thorax in this population., conditionsModule conditions: Lung Cancer, designModule studyType: INTERVENTIONAL, phases: NA, designInfo allocation: NA, interventionModel: SINGLE_GROUP, primaryPurpose: SCREENING, maskingInfo masking: NONE, enrollmentInfo count: 1000, type: ESTIMATED, armsInterventionsModule interventions name: Lung-SIGHT, outcomesModule primaryOutcomes measure: The prevalence of early-staged lung cancer detected by first-round LDCT thorax (T0) in a high-risk non-smoker population, secondaryOutcomes measure: Sensitivity of AI-assisted programme in lung nodule detection and monitoring compared to radiologist assessment, secondaryOutcomes measure: Rate of invasive workup and incidence of associated complications., secondaryOutcomes measure: Prevalence of lung cancer detected by second-round LDCT (T1) in patients with negative first-round LDCT, secondaryOutcomes measure: Diagnostic accuracy and discrimination ability of plasma-based fragmentomic assay in detection of lung cancer via assessment of sensitivity, specificity, positive predictive value and negative predictive value, secondaryOutcomes measure: To determine the quality adjusted life years (QALYs) gained through screening, eligibilityModule sex: ALL, minimumAge: 50 Years, maximumAge: 75 Years, stdAges: ADULT, stdAges: OLDER_ADULT, contactsLocationsModule locations facility: Department of Clinical Oncology, Prince of Wales Hospital, city: Hong Kong, country: Hong Kong, contacts name: Molly SC LI, MBBS, MRCP, role: CONTACT, phone: 3505 2166, email: molly@clo.cuhk.edu.hk, geoPoint lat: 22.27832, lon: 114.17469, hasResults: False