Ignite Creation Date:
2025-12-24 @ 10:58 PM
Ignite Modification Date:
2025-12-25 @ 8:27 PM
Study NCT ID:
NCT04884269
Status:
COMPLETED
Last Update Posted:
2024-02-15
First Post:
2021-05-11
Is NOT Gene Therapy:
False
Has Adverse Events:
False
Brief Title:
A Non Interventional Pilot Study on Machine Learning for ILD Detection Based on the Patient Data From Digital Devices in Unresectable Stage III Non-Small Cell Lung Cancer Patients Receiving Durvalumab
Sponsor:
Organization:
Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}, 'conditionBrowseModule': {'meshes': [{'id': 'D002289', 'term': 'Carcinoma, Non-Small-Cell Lung'}], 'ancestors': [{'id': 'D002283', 'term': 'Carcinoma, Bronchogenic'}, {'id': 'D001984', 'term': 'Bronchial Neoplasms'}, {'id': 'D008175', 'term': 'Lung Neoplasms'}, {'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': {'studyType': 'OBSERVATIONAL', 'designInfo': {'timePerspective': 'PROSPECTIVE', 'observationalModel': 'OTHER'}, 'enrollmentInfo': {'type': 'ACTUAL', 'count': 144}, 'patientRegistry': False}, 'statusModule': {'overallStatus': 'COMPLETED', 'startDateStruct': {'date': '2021-08-11', 'type': 'ACTUAL'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2024-02', 'completionDateStruct': {'date': '2023-03-03', 'type': 'ACTUAL'}, 'lastUpdateSubmitDate': '2024-02-14', 'studyFirstSubmitDate': '2021-05-11', 'studyFirstSubmitQcDate': '2021-05-11', 'lastUpdatePostDateStruct': {'date': '2024-02-15', 'type': 'ACTUAL'}, 'studyFirstPostDateStruct': {'date': '2021-05-12', 'type': 'ACTUAL'}, 'primaryCompletionDateStruct': {'date': '2023-03-03', 'type': 'ACTUAL'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': 'Grade 2 and higher ILD including radiation pneumonitis', 'timeFrame': '6 months'}], 'secondaryOutcomes': [{'measure': 'Disease progression', 'timeFrame': '6 months'}]}, 'conditionsModule': {'conditions': ['Carcinoma, Non-Small-Cell Lung']}, 'referencesModule': {'seeAlsoLinks': [{'url': 'https://filehosting-v2.pharmacm.com/api/Attachment/Download?tenantId=80217111&parentIdentifier=D4194R00024&attachmentIdentifier=fafd99bc-ab04-4c2c-8c02-3b3773753f95&fileName=D4194R00024_CSR_synopsis.pdf&versionIdentifier=', 'label': 'CSR Synopsis'}]}, 'descriptionModule': {'briefSummary': 'Objective in this study is to investigate feasibility of developing machine-learning based model for the identification of future development of diagnosed Grade 2 and higher ILD and of disease progression in patients with unresectable Stage III NSCLC receiving durvalumab', 'detailedDescription': 'Study design: Multicentre, prospective, non-interventional pilot study\n\nData Source(s): Medical records, wearable devices, and mobile application.\n\nStudy Population:Patients treated durvalumab following chemoradiation therapy for stage III unresectable NSCLC in Japan from the June 2021 to June 2022. They must fulfil all of the inclusion /exclusion criteria.\n\nExposure(s): dulvalumab\n\nOutcome(s): Disease progression, ILD including radiation pneumonitis.\n\nSample Size Estimations : 150 patients\n\nStatistical Analysis: Continuous variables will be reported as mean, median, standard deviation, IQR, maximum, and minimum. Categorical variables will be summarized as absolute frequency and percentage. Ninety-five percent confidence intervals (CIs) will be presented where appropriate. Time-to event for ILD/Disease progression will be estimated by Kaplan-Meir method. Also, in the process of developing model, data production such as per-patient plots of the physiological data(multivariate time series) and physiological data before and after (in a shorter time-scale) the ILD event per event will be considered.'}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['ADULT', 'OLDER_ADULT'], 'minimumAge': '20 Years', 'samplingMethod': 'NON_PROBABILITY_SAMPLE', 'studyPopulation': 'The study population consists of stage III unresectable NSCLC patients treated durvalumab following chemoradiation therapy in Japan from the June 2021 to June 2022. They must fulfil all of the following inclusion /exclusion criteria.', 'healthyVolunteers': False, 'eligibilityCriteria': 'Inclusion Criteria:\n\n* Patient who provided written signed informed consent prior to the first study-specific procedures.\n* Patient who receives durvalumab for unresectable stage III NSCLC at first time following chemoradiation therapy\n* Patient whose performance status showed 0 or 1 prior to durvalumab treatment\n* Patient who is able and willing to wear the devices daily for up to 6 months as instructed\n\nExclusion Criteria:\n\n* Patient under immunotherapy treatment other than durvalumab.\n* Patient had received prior immunotherapy\n* Patient under the interventional clinical studies using unapproved drugs or off-label use of drugs\n* Patient who showed ILD (including radiation pneumonitis) of Grade 2 and higher, after consolidated chemoradiation therapy.\n* Patient who is judged as not suitable for the study by the study site investigators, in terms of fitting wearable devices, presence of silicone or metallic allergy'}, 'identificationModule': {'nctId': 'NCT04884269', 'acronym': 'iDETECT', 'briefTitle': 'A Non Interventional Pilot Study on Machine Learning for ILD Detection Based on the Patient Data From Digital Devices in Unresectable Stage III Non-Small Cell Lung Cancer Patients Receiving Durvalumab', 'organization': {'class': 'INDUSTRY', 'fullName': 'AstraZeneca'}, 'officialTitle': 'A Non Interventional Pilot Study on Machine Learning for ILD Detection Based on the Patient Data From Digital Devices in Unresectable Stage III Non-Small Cell Lung Cancer Patients Receiving Durvalumab', 'orgStudyIdInfo': {'id': 'D4194R00024'}}, 'contactsLocationsModule': {'locations': [{'zip': '460-0001', 'city': 'Nagoya', 'state': 'Aichi-ken', 'country': 'Japan', 'facility': 'Research Site', 'geoPoint': {'lat': 35.18147, 'lon': 136.90641}}, {'zip': '464-8681', 'city': 'Nagoya', 'state': 'Aichi-ken', 'country': 'Japan', 'facility': 'Research Site', 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{'zip': '951-8566', 'city': 'Niigata', 'country': 'Japan', 'facility': 'Research Site', 'geoPoint': {'lat': 37.92259, 'lon': 139.04125}}, {'zip': '700-8558', 'city': 'Okayama', 'country': 'Japan', 'facility': 'Research Site', 'geoPoint': {'lat': 34.65, 'lon': 133.93333}}, {'zip': '541-8567', 'city': 'Osaka', 'country': 'Japan', 'facility': 'Research Site', 'geoPoint': {'lat': 34.69379, 'lon': 135.50107}}, {'zip': '770-8503', 'city': 'Tokushima', 'country': 'Japan', 'facility': 'Research Site', 'geoPoint': {'lat': 34.06667, 'lon': 134.56667}}, {'zip': '641-8510', 'city': 'Wakayama', 'country': 'Japan', 'facility': 'Research Site', 'geoPoint': {'lat': 34.23333, 'lon': 135.16667}}]}, 'ipdSharingStatementModule': {'url': 'https://astrazenecagroup-dt.pharmacm.com/DT/Home', 'timeFrame': 'AstraZeneca will meet or exceed data availability as per the commitments made to the EFPIA Pharma Data Sharing Principles. For details of our timelines, please rerefer to our disclosure commitment at https://astrazenecagrouptrials.pharmacm.com/ST/Submission/Disclosure.', 'ipdSharing': 'YES', 'description': 'Qualified researchers can request access to anonymized individual patient-level data from AstraZeneca group of companies sponsored clinical trials/studies via the request portal. All request will be evaluated as per the AZ disclosure commitment: https://astrazenecagrouptrials.pharmacm.com/ST/Submission/Disclosure. Yes, indicates that AZ are accepting requests for IPD, but this does not mean all requests will be shared.', 'accessCriteria': 'When a request has been approved AstraZeneca will provide access to the de-identified individual patient-level data in an approved sponsored tool . Signed Data Sharing Agreement (non-negotiable contract fordata accessors) must be in place before accessing requested information. Additionally, all users will need to accept the terms and conditions of the SAS MSE to gain access. For additional details, please review the Disclosure Statements at https://astrazenecagrouptrials.pharmacm.com/ST/Submission/Disclosure.'}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'AstraZeneca', 'class': 'INDUSTRY'}, 'responsibleParty': {'type': 'SPONSOR'}}}}