protocolSection identificationModule nctId: NCT06262386, orgStudyIdInfo id: 202202172B0, briefTitle: Combined Relapse Prediction Model for Resectable Non-Small Cell Patients - a Prospective Clinical Feasibility Trial, statusModule overallStatus: RECRUITING, startDateStruct date: 2023-08-01, primaryCompletionDateStruct date: 2028-07-31, completionDateStruct date: 2028-07-31, studyFirstPostDateStruct date: 2024-02-16, lastUpdatePostDateStruct date: 2024-02-16, sponsorCollaboratorsModule leadSponsor name: Chang Gung Memorial Hospital, class: OTHER, collaborators name: National Science and Technology Council, descriptionModule briefSummary: For patients with lung cancer who have undergone tumor resection, early relapse significantly impacts survival. However, there are currently no reliable screening or imaging tools available to identify patients at risk of early relapse. To address this clinical challenge, many studies have focused on understanding the clinicopathologic characteristics associated with an increased risk of early relapse. Despite these efforts, we can identify patients at risk but cannot pinpoint which individuals will actually experience early relapse. Studies on adjuvant therapy have shown improved survival in cases of more advanced disease but have not demonstrated a reduction in early relapse rates.In our preliminary analysis of previous study data, we observed that patients with a smaller reduction in circulating tumor cells (CTCs) within the first three days after surgery, followed by an increase on the third-day post-operation, are more likely to experience early relapse during regular monitoring. This pattern may be indicative of minimal residual disease. By combining trends in circulating tumor cell variations with pathologic characteristics, we aim to select patients for adjuvant therapy who are at high risk of developing early relapse.The objective of our study is to employ screening based on circulating tumor cell dynamics and pathologic features to identify patients likely to experience early relapse and to assess the effectiveness of adjuvant therapy in these cases., conditionsModule conditions: Lung Cancer, conditions: Relapse/Recurrence, designModule studyType: INTERVENTIONAL, phases: NA, designInfo allocation: NA, interventionModel: SINGLE_GROUP, primaryPurpose: OTHER, maskingInfo masking: NONE, enrollmentInfo count: 358, type: ESTIMATED, armsInterventionsModule interventions name: Cisplatin based chemottherapy, outcomesModule primaryOutcomes measure: Accuracy of proposed relapse prediction model, primaryOutcomes measure: early relapse rate, secondaryOutcomes measure: Overall surveival, eligibilityModule sex: ALL, minimumAge: 20 Years, maximumAge: 90 Years, stdAges: ADULT, stdAges: OLDER_ADULT, contactsLocationsModule locations facility: Ching-Yang Wu, status: RECRUITING, city: Taoyuan City, zip: 333, country: Taiwan, contacts name: Ching-Yang Wu, role: CONTACT, phone: +886975368204, email: wu.chingyang@gmail.com, contacts name: Jason CH Hsieh, role: CONTACT, phone: +886975366137, email: wisdom5000@gmail.com, contacts name: Jui-Ying Fu, role: SUB_INVESTIGATOR, contacts name: Ching-Feng Wu, role: SUB_INVESTIGATOR, geoPoint lat: 24.95233, lon: 121.20193, hasResults: False