Ignite Creation Date:
2025-12-24 @ 12:58 PM
Ignite Modification Date:
2026-01-01 @ 7:51 PM
Study NCT ID:
NCT06259461
Status:
ACTIVE_NOT_RECRUITING
Last Update Posted:
2024-02-14
First Post:
2024-01-20
Is NOT Gene Therapy:
True
Has Adverse Events:
False
Brief Title:
Machine Learning to Construct an Association Model for Lung Cancer and Environmental Hormone
Sponsor:
Organization:
Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}, 'conditionBrowseModule': {'meshes': [{'id': 'D008175', 'term': 'Lung Neoplasms'}], 'ancestors': [{'id': 'D012142', 'term': 'Respiratory Tract Neoplasms'}, {'id': 'D013899', 'term': 'Thoracic Neoplasms'}, {'id': 'D009371', 'term': 'Neoplasms by Site'}, {'id': 'D009369', 'term': 'Neoplasms'}, {'id': 'D008171', 'term': 'Lung Diseases'}, {'id': 'D012140', 'term': 'Respiratory Tract Diseases'}]}}, 'protocolSection': {'designModule': {'bioSpec': {'retention': 'SAMPLES_WITHOUT_DNA', 'description': '(1) 20 years or older; (2) conscious, without mental disorders; (3) able to use Mandarin to communicate, had a smartphone or tablet computer and could operate it by themselves, and were willing to participate in the study after the reasons for participation were explained and a consent form was signed, indicating their consent.'}, 'studyType': 'OBSERVATIONAL', 'designInfo': {'timePerspective': 'CROSS_SECTIONAL', 'observationalModel': 'CASE_CONTROL'}, 'enrollmentInfo': {'type': 'ESTIMATED', 'count': 128}, 'patientRegistry': False}, 'statusModule': {'overallStatus': 'ACTIVE_NOT_RECRUITING', 'startDateStruct': {'date': '2023-01-01', 'type': 'ACTUAL'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2024-02', 'completionDateStruct': {'date': '2024-06-30', 'type': 'ESTIMATED'}, 'lastUpdateSubmitDate': '2024-02-05', 'studyFirstSubmitDate': '2024-01-20', 'studyFirstSubmitQcDate': '2024-02-05', 'lastUpdatePostDateStruct': {'date': '2024-02-14', 'type': 'ACTUAL'}, 'studyFirstPostDateStruct': {'date': '2024-02-14', 'type': 'ACTUAL'}, 'primaryCompletionDateStruct': {'date': '2024-06-30', 'type': 'ESTIMATED'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': 'identify factors that may lead to lung cancer and environmental hormones.', 'timeFrame': 'the database research samples from May 2014 to December 2020.', 'description': 'This association model can assist in identifying the risk groups of lung cancer and advising physicians on the appropriate environmental hormone testing and treatment to provide nursing guidance and medical advice'}]}, 'oversightModule': {'oversightHasDmc': False, 'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': False}, 'conditionsModule': {'keywords': ['Environmental Substance'], 'conditions': ['Lung Neoplasms']}, 'descriptionModule': {'briefSummary': 'To apply machine learning to construct an association model regarding lung cancer and environmental hormones to more comprehensively identify factors that may lead to lung cancer and to improve existing lung cancer nursing assessments.', 'detailedDescription': 'The present study is exploratory, and its design was divided into three stages: Stage 1 explored the environmental hormonal risk factors for lung cancer and constructed an association model using machine learning algorithms. Stage 2 validated the results of the association model with better predictive results in clinical settings. Stage 3 involved recommendations for reconstructing nursing assessments based on the results of the clinical model validation. The three stages are summarized as follows.'}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['ADULT', 'OLDER_ADULT'], 'minimumAge': '20 Years', 'samplingMethod': 'NON_PROBABILITY_SAMPLE', 'studyPopulation': 'The study focused on lung cancer cases and investigated the association with exposure to environmental hormones', 'healthyVolunteers': True, 'eligibilityCriteria': 'Inclusion Criteria:\n\n1. 20 years or older;\n2. conscious, without mental disorders;\n3. able to use Mandarin to communicate, had a smartphone or tablet computer and could operate it by themselves,\n4. and were willing to participate in the study after the reasons for participation were explained and a consent form was signed, indicating their consent.\n\nExclusion Criteria:\n\n* The exclusion criteria were those who could not understand the content of the nursing assessment questions and those with mental disorders.'}, 'identificationModule': {'nctId': 'NCT06259461', 'briefTitle': 'Machine Learning to Construct an Association Model for Lung Cancer and Environmental Hormone', 'organization': {'class': 'OTHER', 'fullName': 'National Taipei University of Nursing and Health Sciences'}, 'officialTitle': 'Identifying the Risk of Lung Cancer Linked to Environmental Hormones', 'orgStudyIdInfo': {'id': '202204055RINA'}}, 'contactsLocationsModule': {'locations': [{'city': 'Taipei', 'country': 'Taiwan', 'facility': 'National Taipei university of nursing and health science', 'geoPoint': {'lat': 25.05306, 'lon': 121.52639}}, {'city': 'Taipei', 'country': 'Taiwan', 'facility': 'National Taiwan University, Cancer Center', 'geoPoint': {'lat': 25.05306, 'lon': 121.52639}}]}, 'ipdSharingStatementModule': {'ipdSharing': 'NO'}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'Pei-Hung Liao', 'class': 'OTHER'}, 'responsibleParty': {'type': 'SPONSOR_INVESTIGATOR', 'investigatorTitle': 'Associate Professor', 'investigatorFullName': 'Pei-Hung Liao', 'investigatorAffiliation': 'National Taipei University of Nursing and Health Sciences'}}}}