Ignite Creation Date:
2025-12-24 @ 5:39 PM
Ignite Modification Date:
2026-01-01 @ 12:13 PM
Study NCT ID:
NCT06969768
Status:
COMPLETED
Last Update Posted:
2025-05-14
First Post:
2025-04-30
Is NOT Gene Therapy:
True
Has Adverse Events:
False
Brief Title:
Proteogenomics for Follicular Cell-derived Thyroid Cancer: Development of a Classification and Prognosis Prediction Model
Sponsor:
Organization:
Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}, 'conditionBrowseModule': {'meshes': [{'id': 'D013964', 'term': 'Thyroid Neoplasms'}], 'ancestors': [{'id': 'D004701', 'term': 'Endocrine Gland Neoplasms'}, {'id': 'D009371', 'term': 'Neoplasms by Site'}, {'id': 'D009369', 'term': 'Neoplasms'}, {'id': 'D006258', 'term': 'Head and Neck Neoplasms'}, {'id': 'D004700', 'term': 'Endocrine System Diseases'}, {'id': 'D013959', 'term': 'Thyroid Diseases'}]}}, 'protocolSection': {'designModule': {'bioSpec': {'retention': 'SAMPLES_WITHOUT_DNA', 'description': 'Surgical specimen'}, 'studyType': 'OBSERVATIONAL', 'designInfo': {'timePerspective': 'RETROSPECTIVE', 'observationalModel': 'COHORT'}, 'enrollmentInfo': {'type': 'ACTUAL', 'count': 275}, 'patientRegistry': False}, 'statusModule': {'overallStatus': 'COMPLETED', 'startDateStruct': {'date': '2018-02-21', 'type': 'ACTUAL'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2025-05', 'completionDateStruct': {'date': '2024-02-28', 'type': 'ACTUAL'}, 'lastUpdateSubmitDate': '2025-05-12', 'studyFirstSubmitDate': '2025-04-30', 'studyFirstSubmitQcDate': '2025-05-12', 'lastUpdatePostDateStruct': {'date': '2025-05-14', 'type': 'ACTUAL'}, 'studyFirstPostDateStruct': {'date': '2025-05-14', 'type': 'ACTUAL'}, 'primaryCompletionDateStruct': {'date': '2021-02-21', 'type': 'ACTUAL'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': 'Classification Accuracy of Gene-Based Model', 'timeFrame': '1 year', 'description': "The accuracy of the decision-tree model using specific gene set to classify thyroid cancer into BRAFV600E-like, RAS-like, and NT (normal thyroid) -like subtypes. Model performance will be evaluated using accuracy, sensitivity, specificity, and Cohen's kappa."}]}, 'oversightModule': {'oversightHasDmc': False, 'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': False}, 'conditionsModule': {'keywords': ['Thyroid cancer', 'Proteogenomics'], 'conditions': ['Thyroid Cancer']}, 'descriptionModule': {'briefSummary': 'This study aims to refine the molecular classification of thyroid cancer (TC) using a multi-omics approach. By identifying a novel gene set and applying decision-tree modeling, the study seeks to improve diagnostic accuracy and predict tumor progression in BRAFV600E-like and RAS-like TC subtypes. Protein biomarkers were validated via immunohistochemistry (IHC), with findings confirmed across external datasets.'}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['ADULT', 'OLDER_ADULT'], 'minimumAge': '18 Years', 'samplingMethod': 'NON_PROBABILITY_SAMPLE', 'studyPopulation': 'All patients diagnosed with thyroid cancer', 'healthyVolunteers': False, 'eligibilityCriteria': 'Inclusion Criteria:\n\n* Patients with a confirmed clinical diagnosis of thyroid cancer\n* Availability of surgically resected thyroid tissue suitable for omics analysis\n\nExclusion Criteria:\n\n\\- Patients who have received chemotherapy for other malignancies'}, 'identificationModule': {'nctId': 'NCT06969768', 'briefTitle': 'Proteogenomics for Follicular Cell-derived Thyroid Cancer: Development of a Classification and Prognosis Prediction Model', 'organization': {'class': 'OTHER', 'fullName': 'Seoul National University Hospital'}, 'officialTitle': 'Integrative Multi-Omics Refines the Molecular Subtypes of Thyroid Cancers and Enhances Cancer-Progression Prediction', 'orgStudyIdInfo': {'id': '1802-067-922'}}, 'armsInterventionsModule': {'armGroups': [{'label': 'Thyroid cancer', 'description': 'All patients diagnosed with thyroid cancer who underwent thyroidectomy at Seoul National University Hospital'}]}, 'contactsLocationsModule': {'locations': [{'city': 'Seoul', 'country': 'South Korea', 'facility': 'Seoul National University Hospital', 'geoPoint': {'lat': 37.566, 'lon': 126.9784}}]}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'Seoul National University Hospital', 'class': 'OTHER'}, 'collaborators': [{'name': 'Korea Health Industry Development Institute', 'class': 'OTHER_GOV'}, {'name': 'National Research Foundation of Korea', 'class': 'OTHER'}], 'responsibleParty': {'type': 'PRINCIPAL_INVESTIGATOR', 'investigatorTitle': 'Professor', 'investigatorFullName': 'YoungJoo Park', 'investigatorAffiliation': 'Seoul National University Hospital'}}}}