[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100571820":3},{"organization":4,"armGroups":7,"interventions":20,"overallOfficials":17,"centralContacts":30,"locations":17,"responsibleParty":36,"collaborators":40,"id":44,"slug":45,"hasResults":46,"nctId":47,"briefTitle":48,"officialTitle":49,"acronym":17,"eligibilityCriteria":50,"healthyVolunteers":46,"sex":51,"minAge":52,"maxAge":17,"enrollmentInfo":53,"targetDuration":17,"studyType":56,"phases":57,"briefSummary":59,"conditions":60,"keywords":62,"overallStatus":66,"whyStopped":17,"lastUpdateSubmitDate":67,"lastUpdatePostDateStruct":68,"startDateStruct":71,"completionDateStruct":73,"leadSponsor":75,"locationsCount":17},{"fullName":5,"class":6},"Second Affiliated Hospital of Zunyi Medical University","OTHER",[8,14],{"label":9,"type":10,"description":11,"interventionNames":12},"The group with milder symptoms and better quality of life","PLACEBO_COMPARATOR","the group uses unsupervised machine learning to identify patients with severe symptoms and poor functionality who are receiving immunotherapy for non-small cell lung cancer, and implements a symptom cluster care intervention.",[13],"Behavioral: Conventional care intervention",{"label":15,"type":16,"description":17,"interventionNames":18},"The group with more severe symptoms and poorer quality of life","ACTIVE_COMPARATOR",null,[19],"Behavioral: Symptom cluster-based care intervention",[21,26],{"type":22,"name":23,"description":24,"armGroupLabels":25,"otherNames":17},"BEHAVIORAL","Symptom cluster-based care intervention","The patient symptoms were surveyed to develop a symptom cluster care intervention plan. The specific steps were as follows: a research team was established, relevant literature was reviewed, and qualitative interviews were conducted. Guided by symptom management theory and the Knowledge-Attitude-Practice (KAP) behavior model, a draft of the care intervention was created. This draft was then refined through expert consultation to finalize the intervention plan.",[15],{"type":22,"name":27,"description":28,"armGroupLabels":29,"otherNames":17},"Conventional care intervention","Standard nursing intervention. This refers to routine clinical care without a specific care plan tailored to the patient's symptoms. For example, if a patient has symptoms, the nurse assists the patient in notifying the doctor but does not provide any special treatment themselves",[9],[31],{"name":32,"role":33,"phone":34,"phoneExt":17,"email":35},"Jianguo zhou","CONTACT","+8618311543939","jianguo.zhou@yahoo.com",{"type":37,"investigatorFullName":38,"investigatorTitle":39,"investigatorAffiliation":5,"oldNameTitle":17,"oldOrganization":17},"PRINCIPAL_INVESTIGATOR","Jian-Guo Zhou, MD, PhD","associate professor and associate chief physician",[41],{"name":42,"class":43},"Ministry of Education of the People's Republic of China, Department of Humanities and Social Sciences","UNKNOWN","100571820","machine-learning-for-predicting-and-managing-quality-of-life-in-lung-cancer-immunotherapy-patients-100571820",false,"NCT06725225","Machine Learning for Predicting and Managing Quality of Life in Lung Cancer Immunotherapy Patients","Development of a Machine Learning-Based Risk Prediction Model and Stratified Management Strategies for Quality of Life in Lung Cancer Patients Undergoing Immunotherapy","Inclusion Criteria:\n\n1. Histologically diagnosed with lung cancer\n2. Age over 18 years\n3. Currently receiving immunotherapy for lung cancer\n4. Good verbal communication ability\n5. Informed consent signed by the patient or family member\n\nExclusion Criteria:\n\n1. Cognitive impairment or mental illness\n2. Other severe diseases","ALL","18 Years",{"count":54,"type":55},200,"ESTIMATED","INTERVENTIONAL",[58],"NA","The goal of this study is to explore whether health-related quality of life (HRQoL) can be used as a predictive indicator for lung cancer patients and to implement clinical interventions. The study addresses two main objectives:\n\nAnalyzing HRQoL data of lung cancer patients undergoing immunotherapy using machine learning clustering methods to explore data patterns and build an HRQoL early warning model (already developed).\n\nValidating this HRQoL early warning model in real-world settings by classifying patients with different HRQoL characteristics and assessing the clinical value of the model",[61],"Lung Cancer Patients",[63,64,65],"HRQOL","lung cancer","immunotherapy","NOT_YET_RECRUITING","2024-12-09",{"date":69,"type":70},"2024-12-13","ACTUAL",{"date":72,"type":55},"2025-01-01",{"date":74,"type":55},"2026-04-01",{"name":5,"class":6}]