Ignite Creation Date:
2025-12-26 @ 11:13 PM
Ignite Modification Date:
2025-12-26 @ 11:13 PM
Study NCT ID:
NCT05465512
Status:
COMPLETED
Last Update Posted:
2022-07-19
First Post:
2022-07-12
Is NOT Gene Therapy:
False
Has Adverse Events:
False
Brief Title:
Using Radiomics to Predict Neoadjuvant Chemotherapy Efficacy
Sponsor:
Organization:
Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}, 'conditionBrowseModule': {'meshes': [{'id': 'D013274', 'term': 'Stomach Neoplasms'}], 'ancestors': [{'id': 'D005770', 'term': 'Gastrointestinal Neoplasms'}, {'id': 'D004067', 'term': 'Digestive System Neoplasms'}, {'id': 'D009371', 'term': 'Neoplasms by Site'}, {'id': 'D009369', 'term': 'Neoplasms'}, {'id': 'D004066', 'term': 'Digestive System Diseases'}, {'id': 'D005767', 'term': 'Gastrointestinal Diseases'}, {'id': 'D013272', 'term': 'Stomach Diseases'}]}}, 'protocolSection': {'designModule': {'studyType': 'OBSERVATIONAL', 'designInfo': {'timePerspective': 'PROSPECTIVE', 'observationalModel': 'COHORT'}, 'enrollmentInfo': {'type': 'ACTUAL', 'count': 193}, 'targetDuration': '3 Years', 'patientRegistry': True}, 'statusModule': {'overallStatus': 'COMPLETED', 'startDateStruct': {'date': '2022-01-04', 'type': 'ACTUAL'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2022-07', 'completionDateStruct': {'date': '2022-07-10', 'type': 'ACTUAL'}, 'lastUpdateSubmitDate': '2022-07-15', 'studyFirstSubmitDate': '2022-07-12', 'studyFirstSubmitQcDate': '2022-07-15', 'lastUpdatePostDateStruct': {'date': '2022-07-19', 'type': 'ACTUAL'}, 'studyFirstPostDateStruct': {'date': '2022-07-19', 'type': 'ACTUAL'}, 'primaryCompletionDateStruct': {'date': '2022-06-01', 'type': 'ACTUAL'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': 'AUC for ICSS', 'timeFrame': '2022-01-01 to 2022-07-31', 'description': 'The predictive performance of imaging change scoring system before and after neoadjuvant chemotherapy (ICSS)'}, {'measure': 'AUC for BNCISS', 'timeFrame': '2022-01-01 to 2022-07-31', 'description': 'The predictive performance of before neoadjuvant chemotherapy imaging scoring system (BNCISS)'}], 'secondaryOutcomes': [{'measure': 'overall survival', 'timeFrame': '2010-01-01 to 2022-07-31', 'description': '3 year overall survival'}, {'measure': 'disease free survival', 'timeFrame': '2010-01-01 to 2022-07-31', 'description': '3 year disease free survival'}]}, 'oversightModule': {'oversightHasDmc': False, 'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': False}, 'conditionsModule': {'keywords': ['tumor regression grade', 'radiomics', 'neoadjuvant chemotherapy', 'advanced gastric cancer', 'chemotherapy benefit'], 'conditions': ['Gastric Cancer']}, 'descriptionModule': {'briefSummary': 'Neoadjuvant chemotherapy (NC) is an important treatment for advanced gastric cancer (AGC). However, tools that effectively predict the efficacy of NC before treatment are lacking. Computed tomography images before and after NC were used to construct a deep learning-based radiomics signature to predict the efficacy of NC, prognoses and postoperative adjuvant chemotherapy benefit.', 'detailedDescription': 'Background: Neoadjuvant chemotherapy (NC) is an important treatment for advanced gastric cancer (AGC). However, tools that effectively predict the efficacy of NC before treatment are lacking.\n\nMethods: Computed tomography images before and after NC were used to construct a deep learning-based radiomics signature to predict the efficacy of NC, prognoses and postoperative adjuvant chemotherapy benefit. Tumor regression grade (TRG) =0 or 1 was defined as a good response to neoadjuvant chemotherapy (GRNC), and TRG=2 or 3 was defined as a poor response to neoadjuvant chemotherapy (PRNC). 193 patients with AGC from January 2010 to December 2018 in two different China university hospitals were included in this study. The before neoadjuvant chemotherapy imaging scoring system (BNCISS), imaging change scoring system before and after neoadjuvant chemotherapy (ICSS), which were constructed based on computed tomography images before after treatment.'}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['ADULT', 'OLDER_ADULT'], 'maximumAge': '85 Years', 'minimumAge': '18 Years', 'samplingMethod': 'NON_PROBABILITY_SAMPLE', 'studyPopulation': 'Prospective collection and a retrospective analysis of patients seen from January 2010 to December 2018 at Fujian Medical University Union Hospital (FMUUH) and the First Hospital of Lanzhou University (FHLU) who were diagnosed with gastric adenocarcinoma and underwent radical resection yielded 193 neoadjuvant chemotherapy (NC) patients, including 148 cases from FMUUH (derivation cohort) and 45 cases from the FHLU (validation cohort). Of the 148 patients from FMUUH, 139 had computed tomography (CT) images before NC, 141 had CT images after NC, and 132 had CT images before and after NC. All 45 patients in the FHLU underwent CT before and after NC. Patients with concurrent malignant disease, distant metastases, palliative resection, or gastric stump cancer were excluded.', 'eligibilityCriteria': 'Inclusion Criteria:\n\n* Prospective collection and a retrospective analysis of patients seen from January 2010 to December 2018 at Fujian Medical University Union Hospital (FMUUH) and the First Hospital of Lanzhou University (FHLU) who were diagnosed with gastric adenocarcinoma and underwent radical resection\n\nExclusion Criteria:\n\n* Patients with concurrent malignant disease, distant metastases, palliative resection, or gastric stump cancer were excluded.'}, 'identificationModule': {'nctId': 'NCT05465512', 'briefTitle': 'Using Radiomics to Predict Neoadjuvant Chemotherapy Efficacy', 'organization': {'class': 'OTHER', 'fullName': 'Fujian Medical University'}, 'officialTitle': 'Using Radiomics to Predict Neoadjuvant Chemotherapy Efficacy and Postoperative Adjuvant Chemotherapy Benefit in Advanced Gastric Cancer: a Two-center Study', 'orgStudyIdInfo': {'id': 'FMUUH-001'}}, 'armsInterventionsModule': {'armGroups': [{'label': 'good response to neoadjuvant chemotherapy (GRNC)', 'description': 'Tumor regression grade (TRG) =0 or 1 was defined as a good response to neoadjuvant chemotherapy (GRNC)', 'interventionNames': ['Other: response to neoadjuvant chemotherapy']}, {'label': 'poor response to neoadjuvant chemotherapy (PRNC)', 'description': 'TRG=2 or 3 was defined as a poor response to neoadjuvant chemotherapy (PRNC).', 'interventionNames': ['Other: response to neoadjuvant chemotherapy']}], 'interventions': [{'name': 'response to neoadjuvant chemotherapy', 'type': 'OTHER', 'description': 'Tumor regression grade (TRG) =0 or 1 was defined as a good response to neoadjuvant chemotherapy (GRNC), and TRG=2 or 3 was defined as a poor response to neoadjuvant chemotherapy (PRNC).', 'armGroupLabels': ['good response to neoadjuvant chemotherapy (GRNC)', 'poor response to neoadjuvant chemotherapy (PRNC)']}]}, 'contactsLocationsModule': {'locations': [{'city': 'Fuzhou', 'state': 'Fujian', 'country': 'China', 'facility': 'Department of Gastric Surgery', 'geoPoint': {'lat': 26.06139, 'lon': 119.30611}}], 'overallOfficials': [{'name': 'Hualong Zheng', 'role': 'STUDY_DIRECTOR', 'affiliation': '291167038@qq.com'}]}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'Fujian Medical University', 'class': 'OTHER'}, 'responsibleParty': {'type': 'PRINCIPAL_INVESTIGATOR', 'investigatorTitle': 'Principal Investigator', 'investigatorFullName': 'Chang-Ming Huang, Prof.', 'investigatorAffiliation': 'Fujian Medical University'}}}}