Viewing Study NCT04777032


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Study NCT ID: NCT04777032
Status: ENROLLING_BY_INVITATION
Last Update Posted: 2025-04-03
First Post: 2021-02-16
Is NOT Gene Therapy: False
Has Adverse Events: False

Brief Title: The Danish Comorbidity in Liver Transplant Recipients Study
Sponsor:
Organization:

Raw JSON

{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}}, 'protocolSection': {'designModule': {'bioSpec': {'retention': 'SAMPLES_WITHOUT_DNA', 'description': 'Biochemical analyses including fasting insulin and fasting blood glucose. Blood will be collected for a research biobank, and peripheral blood mononuclear cells, serum and plasma will be stored for further analyses of inflammation markers (chemokines, cytokines, soluble surface markers), coagulation markers (standard and functional platelet aggregation test), simulation assays and flowcytometry of PBMC, endothelial function markers (asymmetric dimethylarginine (ADMA), syndecan-1, trombomodulin and sE-selectin), markers of microbial translocation and bacterial degradation (sCD14, lipopolysaccharide, trimethylamine N-oxide), markers of lung tissue (alpha-1-antitrypsine, endothelin-1), liver markers (hyaluronic acid and fibrosis markers) and metabolomics and multiomics.'}, 'studyType': 'OBSERVATIONAL', 'designInfo': {'timePerspective': 'PROSPECTIVE', 'observationalModel': 'COHORT'}, 'enrollmentInfo': {'type': 'ESTIMATED', 'count': 600}, 'patientRegistry': False}, 'statusModule': {'overallStatus': 'ENROLLING_BY_INVITATION', 'startDateStruct': {'date': '2021-03-15', 'type': 'ACTUAL'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2025-04', 'completionDateStruct': {'date': '2043-01-01', 'type': 'ESTIMATED'}, 'lastUpdateSubmitDate': '2025-04-02', 'studyFirstSubmitDate': '2021-02-16', 'studyFirstSubmitQcDate': '2021-02-25', 'lastUpdatePostDateStruct': {'date': '2025-04-03', 'type': 'ACTUAL'}, 'studyFirstPostDateStruct': {'date': '2021-03-02', 'type': 'ACTUAL'}, 'primaryCompletionDateStruct': {'date': '2033-01-01', 'type': 'ESTIMATED'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': 'Prevalence of coronary artery disease', 'timeFrame': 'Baseline cross-sectional data', 'description': 'Assessed by coronary CT angiography'}, {'measure': 'Change in Coronary artery disease', 'timeFrame': '10 years follow-up', 'description': 'Assessed by coronary CT angiography'}, {'measure': 'Cardiac function', 'timeFrame': 'Baseline cross-sectional data', 'description': 'Determined by transthoracic echocardiography'}, {'measure': 'Change in Cardiac function', 'timeFrame': '10 years follow-up', 'description': 'Determined by transthoracic echocardiography'}, {'measure': 'Cardiac structure', 'timeFrame': 'Baseline cross-sectional data', 'description': 'Determined by transthoracic echocardiography'}, {'measure': 'Change in cardiac structure', 'timeFrame': '10 years follow-up', 'description': 'Determined by transthoracic echocardiography'}, {'measure': 'Cardiac structure', 'timeFrame': 'Baseline cross-sectional data', 'description': 'Assessed by cardiac computed tomography (CT)'}, {'measure': 'Change in Cardiac structure', 'timeFrame': '10 years follow-up', 'description': 'Assessed by cardiac computed tomography (CT)'}, {'measure': 'Cardiac function', 'timeFrame': 'Baseline cross-sectional data', 'description': 'Assessed by cardiac computed tomography (CT)'}, {'measure': 'Change in Cardiac function', 'timeFrame': '10 years follow-up', 'description': 'Assessed by cardiac computed tomography (CT)'}, {'measure': 'Dynamic lung function indices assessed by spirometry', 'timeFrame': 'Baseline cross-sectional data', 'description': 'FVC and FEV1 assessed by spirometry'}, {'measure': 'Change in Dynamic lung function indices assessed by spirometry', 'timeFrame': '10 years follow-up', 'description': 'FVC and FEV1 assessed by spirometry'}, {'measure': 'Renal function', 'timeFrame': 'Baseline cross-sectional data', 'description': 'Estimated glomerular filtration rate'}, {'measure': 'Change in Renal function', 'timeFrame': '10 years follow-up', 'description': 'Estimated glomerular filtration rate'}, {'measure': 'Metabolic diseases', 'timeFrame': 'Baseline cross-sectional data', 'description': 'Prevalence of Diabetes'}, {'measure': 'Metabolic diseases', 'timeFrame': '10 years follow-up', 'description': 'Change in Diabetes'}, {'measure': 'Metabolic diseases', 'timeFrame': 'Baseline cross-sectional data', 'description': 'Prevalence of Dyslipidaemia'}, {'measure': 'Metabolic diseases', 'timeFrame': '10 years follow-up', 'description': 'Change in Dyslipidaemia'}], 'secondaryOutcomes': [{'measure': 'Prevalence of Depression', 'timeFrame': 'Baseline cross sectional data', 'description': "Major Depression Inventory (MDI): A depression questionnaire. The questionnaire consists of the ten symptoms contained in the World Health Organization WHO's depression demarcation. The patient's completed questionnaire is scored using a scoring key.\n\nWhen MDI is used as a rating scale in the same way as the Hamilton scales, then the sum of the ten questions indicates the degree of depression. The theoretical score range is from 0 (no depression) to 50 (maximum depression).\n\nMild depression: MDI total score from 21 to 25 Moderate depression: MDI total score from 26 to 30 Severe depression: MDI total score of 31 or higher"}, {'measure': 'Change in Depression', 'timeFrame': '10 years follow-up', 'description': "Major Depression Inventory (MDI): A depression questionnaire. The questionnaire consists of the ten symptoms contained in the World Health Organization WHO's depression demarcation. The patient's completed questionnaire is scored using a scoring key.\n\nWhen MDI is used as a rating scale in the same way as the Hamilton scales, then the sum of the ten questions indicates the degree of depression. The theoretical score range is from 0 (no depression) to 50 (maximum depression).\n\nMild depression: MDI total score from 21 to 25 Moderate depression: MDI total score from 26 to 30 Severe depression: MDI total score of 31 or higher"}, {'measure': 'Fracture risk', 'timeFrame': 'Baseline cross sectional data', 'description': 'FRAX® score. The FRAX® tool has been developed to evaluate fracture risk of patients. It is based on individual patient models that integrate the risks associated with clinical risk factors.\n\nThe FRAX® algorithms give the 10-year probability of fracture. The output is a 10-year probability of hip fracture and the 10-year probability of a major osteoporotic fracture (clinical spine, forearm, hip or shoulder fracture).'}, {'measure': 'Change in Fracture risk', 'timeFrame': '10 year follow-up', 'description': 'FRAX® score. The FRAX® tool has been developed to evaluate fracture risk of patients. It is based on individual patient models that integrate the risks associated with clinical risk factors.\n\nThe FRAX® algorithms give the 10-year probability of fracture. The output is a 10-year probability of hip fracture and the 10-year probability of a major osteoporotic fracture (clinical spine, forearm, hip or shoulder fracture).'}, {'measure': 'Obstructive pulmonary disease', 'timeFrame': 'Baseline cross sectional data', 'description': 'Nitric oxide in exhaled breath'}, {'measure': 'Obstructive pulmonary disease', 'timeFrame': '10 year follow-up', 'description': 'Change in Nitric oxide in exhaled breath'}, {'measure': 'Prevalence of Peripheral artery disease', 'timeFrame': 'Baseline cross sectional data', 'description': 'Ankle-brachial-index (ABI) is measured using a Doppler meter by determining the systolic pressure in the arm and ankle.'}, {'measure': 'Change in Peripheral artery disease', 'timeFrame': '10 years follow-up', 'description': 'Ankle-brachial-index (ABI) is measured using a Doppler meter by determining the systolic pressure in the arm and ankle.'}]}, 'oversightModule': {'oversightHasDmc': True, 'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': False}, 'conditionsModule': {'conditions': ['Liver Transplantation', 'Comorbidities and Coexisting Conditions']}, 'referencesModule': {'references': [{'pmid': '38570629', 'type': 'DERIVED', 'citation': 'Suarez-Zdunek MA, Arentoft NS, Krohn PS, Lauridsen EHE, Afzal S, Hogh J, Thomsen MT, Knudsen AD, Nordestgaard BG, Hillingso JG, Villadsen GE, Holland-Fischer P, Rasmussen A, Fialla AD, Feldt-Rasmussen U, Nielsen SD. Prevalence of hyperthyroidism and hypothyroidism in liver transplant recipients and associated risk factors. Sci Rep. 2024 Apr 3;14(1):7828. doi: 10.1038/s41598-024-58544-3.'}, {'pmid': '33794793', 'type': 'DERIVED', 'citation': 'Thomsen MT, Hogh J, Knudsen AD, Jensen AMR, Gelpi M, Villadsen GE, Abazi R, Holland-Fischer P, Kober L, Clemmesen O, Krohn PS, Hillingso J, Vilsboll T, Biering-Sorensen T, Kofoed KF, Nordestgaard BG, Rasmussen A, Nielsen SD. The Danish comorbidity in liver transplant recipients study (DACOLT): a non-interventional prospective observational cohort study. BMC Gastroenterol. 2021 Apr 1;21(1):145. doi: 10.1186/s12876-021-01733-5.'}]}, 'descriptionModule': {'briefSummary': 'Background:\n\nLiver transplantation is the only curative treatment for patients with end-stage liver disease. Short-term survival has improved due to improved surgical techniques and greater efficacy of immunosuppressive drugs. At present, the 10-year survival after liver transplantation is 60%, but long-term survival has not improved to the same extent the short-term survival. In addition to liver- and transplant-related causes, comorbidities such as cardiovascular, pulmonary, renal, and metabolic diseases have emerged as leading causes of morbidity and mortality in liver transplant recipients.\n\nThe objective of this study is to assess the burden of comorbidities and identify both liver- and transplant-related risk factors as well as traditional risk factors that contribute to the pathogenesis of comorbidity in liver transplant recipients.\n\nMethods/design:\n\nThe DACOLT study is an observational, longitudinal study. The investigators aim to include all adult liver transplant recipients in Denmark. Participants will be matched by sex and age to controls from the Copenhagen General Population Study (CGPS) and the Copenhagen City Heart Study (CCHS). Physical and biological measures including blood pressure, ancle-brachial index, spirometry, exhaled nitric oxide, electrocardiogram, transthoracic echocardiography, computed tomography (CT) angiography of the heart, unenhanced CT of chest and abdomen and blood samples will be collected using uniform protocols in participants in CGPS, CCHS and DACOLT. Blood samples will be collected and stored in a research biobank. Follow-up examinations at regular intervals up to 10 years of follow-up are planned.\n\nDiscussion:\n\nThere is no international consensus standard for optimal clinical care or monitoring of liver transplant recipients. The study will determine prevalence, incidence and risk factors for comorbidity in liver transplant recipients and may be used to provide evidence for guidelines on screening and long-term treatment and thereby contribute to improvement of the long-term survival.'}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['ADULT', 'OLDER_ADULT'], 'maximumAge': '100 Years', 'minimumAge': '20 Years', 'samplingMethod': 'NON_PROBABILITY_SAMPLE', 'studyPopulation': 'All liver transplanted individuals in Danmark.', 'healthyVolunteers': True, 'eligibilityCriteria': 'Inclusion Criteria:\n\n* Liver transplanted\n* age between 20 and 100 years\n* be able to understand the study information in either Danish or English and to be able to provide an informed consent\n\nExclusion Criteria:\n\n* none'}, 'identificationModule': {'nctId': 'NCT04777032', 'acronym': 'DACOLT', 'briefTitle': 'The Danish Comorbidity in Liver Transplant Recipients Study', 'organization': {'class': 'OTHER', 'fullName': 'Rigshospitalet, Denmark'}, 'officialTitle': 'The Danish Comorbidity in Liver Transplant Recipients Study (DACOLT) - a Non-interventional Prospective Observational Cohort Study', 'orgStudyIdInfo': {'id': 'Sponsor1 - Rigshospitalet'}}, 'armsInterventionsModule': {'armGroups': [{'label': 'Liver transplant recipients', 'description': 'All liver transplant recipient in Denmark aged 18-100 years will be eligible for inclusion in the DACOLT study. Inclusion requires the individual to be able to understand the study information in either Danish or English and to be able to provide an informed consent.'}, {'label': 'Control group 1_CGPS', 'description': 'The Copenhagen General Population Study (CGPS) is an ongoing observational population study with more than 110.000 participants from the greater Copenhagen area. All residents in the greater Copenhagen area \\> 40 years and 25% of 20-40 years old are invited to participate in the study and in follow-up examinations every decade. A random sample of 10.000 participants aged ≥ 40 years had a contrast enhanced CT of the chest including CT angiography of the heart performed. Of these, 6500 had a contrast enhanced CT of the abdomen.'}, {'label': 'Control group 1_CCHS', 'description': 'The Copenhagen City Heart Study (CCHS) includes a random population sample included from the greater Copenhagen area. Health surveys have been repeated 5 times between 1976 and 2015. Almost 4000 participants were randomly selected for echocardiography.'}]}, 'contactsLocationsModule': {'locations': [{'city': 'Aalborg', 'country': 'Denmark', 'facility': 'Aalborg University Hospital', 'geoPoint': {'lat': 57.048, 'lon': 9.9187}}, {'city': 'Aarhus', 'country': 'Denmark', 'facility': 'Aarhus University Hospital', 'geoPoint': {'lat': 56.15674, 'lon': 10.21076}}, {'zip': '2100', 'city': 'Copenhagen', 'country': 'Denmark', 'facility': 'Copenhagen University Hospital - Rigshospitalet', 'geoPoint': {'lat': 55.67594, 'lon': 12.56553}}, {'city': 'Odense', 'country': 'Denmark', 'facility': 'Odense University Hospital', 'geoPoint': {'lat': 55.39594, 'lon': 10.38831}}], 'overallOfficials': [{'name': 'Susanne D Rasmussen, Professor, MD, DMSc', 'role': 'PRINCIPAL_INVESTIGATOR', 'affiliation': 'Department of Infectious Diseases, Copenhagen University Hospital - Rigshospitalet'}, {'name': 'Allan Rasmussen, MD', 'role': 'STUDY_DIRECTOR', 'affiliation': 'Department of Transplantation and Digestive Diseases, Copenhagen University Hospital - Rigshospitalet'}, {'name': 'Klaus F Kofoed, Professor, MD, PhD, DMSc', 'role': 'STUDY_DIRECTOR', 'affiliation': 'Department of Cardiology, Copenhagen University Hospital - Rigshospitalet'}, {'name': 'Tor Biering-Sørensen, Professor, MD, MSc, PhD', 'role': 'STUDY_DIRECTOR', 'affiliation': 'Department of Cardiology, Copenhagen University Hospital - Herlev and Gentofte'}]}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'Rigshospitalet, Denmark', 'class': 'OTHER'}, 'responsibleParty': {'type': 'PRINCIPAL_INVESTIGATOR', 'investigatorTitle': 'Professor, MD, DMSc', 'investigatorFullName': 'Susanne Dam Nielsen, MD, DMSc', 'investigatorAffiliation': 'Rigshospitalet, Denmark'}}}}