Ignite Creation Date:
2025-12-24 @ 11:20 PM
Ignite Modification Date:
2025-12-25 @ 9:02 PM
Study NCT ID:
NCT05309356
Status:
UNKNOWN
Last Update Posted:
2023-05-10
First Post:
2022-03-14
Is NOT Gene Therapy:
False
Has Adverse Events:
False
Brief Title:
Using Clinical Prediction Models to Improve Treatment for Patients With Chronic Obstructive Pulmonary Disease (COPD)
Sponsor:
Organization:
Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}, 'conditionBrowseModule': {'meshes': [{'id': 'D029424', 'term': 'Pulmonary Disease, Chronic Obstructive'}, {'id': 'D055118', 'term': 'Medication Adherence'}], 'ancestors': [{'id': 'D008173', 'term': 'Lung Diseases, Obstructive'}, {'id': 'D008171', 'term': 'Lung Diseases'}, {'id': 'D012140', 'term': 'Respiratory Tract Diseases'}, {'id': 'D002908', 'term': 'Chronic Disease'}, {'id': 'D020969', 'term': 'Disease Attributes'}, {'id': 'D010335', 'term': 'Pathologic Processes'}, {'id': 'D013568', 'term': 'Pathological Conditions, Signs and Symptoms'}, {'id': 'D010349', 'term': 'Patient Compliance'}, {'id': 'D010342', 'term': 'Patient Acceptance of Health Care'}, {'id': 'D000074822', 'term': 'Treatment Adherence and Compliance'}, {'id': 'D015438', 'term': 'Health Behavior'}, {'id': 'D001519', 'term': 'Behavior'}]}}, 'protocolSection': {'designModule': {'phases': ['NA'], 'studyType': 'INTERVENTIONAL', 'designInfo': {'allocation': 'RANDOMIZED', 'maskingInfo': {'masking': 'NONE'}, 'primaryPurpose': 'HEALTH_SERVICES_RESEARCH', 'interventionModel': 'CROSSOVER', 'interventionModelDescription': 'The investigators will conduct a prospective, pragmatic two-year stepped-wedged cluster RCT to evaluate the impact of ACCEPT on the process of care, patient-reported, and clinical outcomes. The trial was designed based on 24 participating physicians, comprising the study clusters. All physicians will be assigned to the comparator arm (usual care) at the beginning of the study. After 6 months, under a sequential rollout, two randomly selected physicians will be reassigned to the intervention arm (ACCEPT) every month.'}, 'enrollmentInfo': {'type': 'ESTIMATED', 'count': 1130}}, 'statusModule': {'overallStatus': 'UNKNOWN', 'lastKnownStatus': 'RECRUITING', 'startDateStruct': {'date': '2023-03-21', 'type': 'ACTUAL'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2023-05', 'completionDateStruct': {'date': '2025-07', 'type': 'ESTIMATED'}, 'lastUpdateSubmitDate': '2023-05-08', 'studyFirstSubmitDate': '2022-03-14', 'studyFirstSubmitQcDate': '2022-03-31', 'lastUpdatePostDateStruct': {'date': '2023-05-10', 'type': 'ACTUAL'}, 'studyFirstPostDateStruct': {'date': '2022-04-04', 'type': 'ACTUAL'}, 'primaryCompletionDateStruct': {'date': '2025-01', 'type': 'ESTIMATED'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': 'Prescription appropriateness', 'timeFrame': 'Cross-sectional: data collected during each patients initial study visit for the duration of the trial (24 months)', 'description': 'Binary variable indicating the concordance between the physician- and ACCEPT-based treatment recommendations (0: discordant prescription, 1: concordant prescription). We will compare the percentage of prescription appropriateness between the two study arms.\n\nThe prescription recommended by the physician during the clinical encounter will be recorded. After the encounter, a research coordinator will interview the patient, use ACCEPT to produce the ACCEPT-based optimal treatment for the patient.\n\nThe physician prescription will be considered concordant if it is the same as the prescription based on the ACCEPT recommendation (or if ACCEPT suggests more than one eligible prescription, the physician prescription is one of them), otherwise it will be considered discordant.'}], 'secondaryOutcomes': [{'measure': 'Medication adherence', 'timeFrame': '1 year before and 1 year after initial study visit (day 1).', 'description': "Medication adherence will be measured by the Medication Possession Ratio, defined as the ratio of the total days' supply dispensed to the total days' supply prescribed during the study period. This outcome will be assessed by linking patient data to BC's administrative health databases using each individual's unique Personal Health Number."}, {'measure': 'Rate of moderate or severe exacerbations', 'timeFrame': '1 year before and 1 year after initial study visit.', 'description': "This outcome will be assessed by linking patient data to BC's administrative health databases using each individual's unique Personal Health Number. Moderate exacerbations will be defined any outpatient physician visit for COPD followed by filling prescriptions for antibiotic or oral corticosteroids. Severe exacerbations will be define as hospital admission with the main discharge code of COPD."}, {'measure': 'Self-reported medication adherence and beliefs', 'timeFrame': 'BMQ-COPD will be administered at baseline (study visit 1, day 1), month 3, and month 6', 'description': 'COPD-specific Beliefs about Medicines Questionnaire (BMQ)'}, {'measure': "Impact of COPD on patient's daily life", 'timeFrame': 'CAT will be administered at baseline (study visit 1, day 1), month 3, and month 6', 'description': 'Measured by the COPD Assessment Test (CAT)'}, {'measure': "COPD patient's Quality of Life", 'timeFrame': 'EQ5D will be administered at baseline (study visit 1, day 1), month 3, and month 6', 'description': 'Measured by the EuroQoL 5-dimension (EQ5D) questionnaire'}]}, 'oversightModule': {'oversightHasDmc': True, 'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': False}, 'conditionsModule': {'keywords': ['Precision medicine', 'Clinical prediction models', 'Medication adherence', 'Prescription appropriateness', 'Decision aid'], 'conditions': ['Chronic Obstructive Pulmonary Disease']}, 'referencesModule': {'references': [{'pmid': '36782301', 'type': 'DERIVED', 'citation': 'Michaux KD, Metcalfe RK, Burns P, Conklin AI, Hoens AM, Smith D, Struik L, Safari A, Sin DD, Sadatsafavi M; IMPACT Study Group. IMplementing Predictive Analytics towards efficient COPD Treatments (IMPACT): protocol for a stepped-wedge cluster randomized impact study. Diagn Progn Res. 2023 Feb 14;7(1):3. doi: 10.1186/s41512-023-00140-6.'}]}, 'descriptionModule': {'briefSummary': 'Chronic Obstructive Pulmonary Disease (COPD) is a chronic disease of the lungs that affects more than 2.5 million Canadians. Patients with COPD experience episodes of lung attacks (or exacerbations). During these attacks, patients experience an intense increase in symptoms, such as breathlessness and cough. It is challenging to decide which patients should be put on treatments that would reduce the risk of such lung attacks. The digitization of health records in many clinics and hospitals means complex risk prediction algorithms can be used to predict the risk of lung attacks to enable personalized care. In this study, our team will implement a risk prediction tool (called ACCEPT) into the electronic health records in two teaching hospitals in Vancouver, British Columbia (BC), Canada. A clinical study will be conducted to evaluate if the use of this tool results in patients with COPD receiving better care with better outcomes, and if they are more satisfied with the care they are receiving.', 'detailedDescription': "COPD is a heterogenous and progressive disease of the airways that affects millions of people worldwide. However, current treatment guidelines fail to provide personalised, patient-centered disease management. In contrast, precision medicine emphasizes the tailoring of disease management to patient characteristics and values to optimize patient care and outcomes. Clinical prediction models (CPMs) are major enablers of precision medicine, and facilitate targeted therapies to patients who will benefit the most from them.\n\nThe investigators developed a CPM called ACCEPT that improves risk stratification for COPD patients by predicting the risk of exacerbation at an individual level and thereby enabling personalized, preventive disease management. Using a stepped wedged cluster randomized controlled trial (RCT), the investigators aim to evaluate the impact of integrating ACCEPT into routine COPD care at two outpatient respiratory clinics in Vancouver, British Columbia, Canada.\n\nThe 'stepped wedged' RCT has a cross-over design, with treatment assignment done in a uni-directional, staggered format that will provide opportunities to control for time trend. The total duration of the study is 30 months. There will be a one-month phase in period with patient recruitment and data collection starting on month two. The last physician assignment will occur in month 18, and patient recruitment will continue until month 24. Follow-up data will be collected until month 30 to ensure six months of follow-up data for all patients.\n\nPrimary and secondary outcomes will be analysed using generalized estimating equations to account for possible clustering of endpoints (multiple visits for each physician). Further, following the intention to treat principle, clusters (physicians) will be analyzed according to their randomized crossover time irrespective of whether crossover was achieved at the desired time."}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['ADULT', 'OLDER_ADULT'], 'minimumAge': '35 Years', 'healthyVolunteers': False, 'eligibilityCriteria': 'Inclusion Criteria:\n\n* Are a legal Canadian resident\n* Aged 35 years and older\n* Can speak English\n* Have a diagnosis of COPD\n\nExclusion Criteria:\n\n• Are under 35 years of age'}, 'identificationModule': {'nctId': 'NCT05309356', 'briefTitle': 'Using Clinical Prediction Models to Improve Treatment for Patients With Chronic Obstructive Pulmonary Disease (COPD)', 'organization': {'class': 'OTHER', 'fullName': 'University of British Columbia'}, 'officialTitle': 'IMplementing Predictive Analytics Towards Efficient COPD Treatments (IMPACT) Study', 'orgStudyIdInfo': {'id': 'H21-02348'}, 'secondaryIdInfos': [{'id': 'F20-05804', 'type': 'OTHER_GRANT', 'domain': 'Canadian Institutes of Health Research (CIHR)'}]}, 'armsInterventionsModule': {'armGroups': [{'type': 'ACTIVE_COMPARATOR', 'label': 'Usual care (Control)', 'description': 'Routine COPD patient care.', 'interventionNames': ['Other: Comparator']}, {'type': 'EXPERIMENTAL', 'label': 'ACCEPT Decision Intervention', 'description': "Clinical prediction model (ACCEPT)-based treatment recommendations: The ACCEPT tool will display the predicted risk of exacerbations, and the corresponding treatment recommendations to the physicians. These recommendations will be provided in a non-mandatory 'directive' format where the physician can override the recommendation, but is required to provide a justification (pre-set choices and a free text).", 'interventionNames': ['Other: ACCEPT Decision Intervention']}], 'interventions': [{'name': 'ACCEPT Decision Intervention', 'type': 'OTHER', 'description': 'The intervention consists of the CPM (ACCEPT) that is integrated with a decision aid, together called the ACCEPT Decision Intervention (ADI). The ADI will provide physicians with a quantification of the exacerbation risk for each patient and the corresponding treatment recommendation, as well as information about the benefits and risks of different inhaled therapies to discuss with the patients. The intervention also includes a 1-page take-home pamphlet on evidence-based risk behaviour factor modification for COPD, tailored to the treatment recommendation.', 'armGroupLabels': ['ACCEPT Decision Intervention']}, {'name': 'Comparator', 'type': 'OTHER', 'description': 'The patient will receive the physician-recommended treatment for COPD (usual care). All physicians will be provided refresher training on the Canadian Thoracic Society COPD guidelines during the phase in period (month 1).', 'armGroupLabels': ['Usual care (Control)']}]}, 'contactsLocationsModule': {'locations': [{'zip': 'V5Z 1M9', 'city': 'Vancouver', 'state': 'British Columbia', 'status': 'NOT_YET_RECRUITING', 'country': 'Canada', 'contacts': [{'name': 'Prabjit Barn, PhD', 'role': 'CONTACT', 'email': 'prabjit.barn@vch.ca', 'phone': '604-875-4111', 'phoneExt': '23137'}, {'name': 'Chris Carlsten, MD, MPH', 'role': 'PRINCIPAL_INVESTIGATOR'}], 'facility': 'The Lung Centre, Vancouver General Hospital', 'geoPoint': {'lat': 49.24966, 'lon': -123.11934}}, {'zip': 'V6Z1Y6', 'city': 'Vancouver', 'state': 'British Columbia', 'status': 'RECRUITING', 'country': 'Canada', 'contacts': [{'name': 'Alexander Lin, BA', 'role': 'CONTACT', 'email': 'alexander.lin@ubc.ca', 'phone': '604-418-1207'}, {'name': 'Don Sin, MD, MPH', 'role': 'PRINCIPAL_INVESTIGATOR'}], 'facility': "St Paul's Hospital, Heart and Lung Centre", 'geoPoint': {'lat': 49.24966, 'lon': -123.11934}}], 'centralContacts': [{'name': 'Mohsen Sadatsafavi, MD, PhD', 'role': 'CONTACT', 'email': 'mohsen.sadatsafavi@ubc.ca', 'phone': '(604) 827-3020'}, {'name': 'Don Sin, MD, MPH', 'role': 'CONTACT', 'email': 'Don.Sin@hli.ubc.ca', 'phone': '(604) 806-8395'}]}, 'ipdSharingStatementModule': {'url': 'http://datadryad.org/', 'infoTypes': ['STUDY_PROTOCOL', 'SAP', 'CSR', 'ANALYTIC_CODE'], 'timeFrame': 'Data will be made available 1 year after study completion, indefinitely', 'ipdSharing': 'YES', 'description': "All data sets collected as part of this study, with the exception of the administrative health data, will be shared via the DRYAD initiative. The Dryad Digital Repository is a curated resource that makes research data discoverable, freely reusable, and citable. Dryad provides a general-purpose home for a wide diversity of data types.\n\nStudy investigators will share anonymized (free from patient identifiers as well as any sensitive data that might identify specific patients \\[e.g., extremely rare comorbid conditions\\]). The linked administrative health data, however, will not be shared, as such data are under the stewardship of British Columbia's Ministry of Health and is protected by the provincial Freed of Information and Protection of Privacy Act which prohibits its sharing.", 'accessCriteria': 'Data will be freely accessible and publicly available via the DRYAD initiative.'}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'University of British Columbia', 'class': 'OTHER'}, 'collaborators': [{'name': 'Providence Health & Services', 'class': 'OTHER'}, {'name': 'Vancouver Coastal Health', 'class': 'OTHER_GOV'}], 'responsibleParty': {'type': 'PRINCIPAL_INVESTIGATOR', 'investigatorTitle': 'Principal Investigator', 'investigatorFullName': 'Mohsen Sadatsafavi', 'investigatorAffiliation': 'University of British Columbia'}}}}