Prognostic imaging biomarkers for diabetic kidney disease (iBEAt): study protocol
Autor: | Dick de Zeeuw, M.W. Mansfield, Matthew Wellberry-Smith, Nicolas Grenier, Anna V. Zetterqvist, Anna-Maria Dutius Andersson, Kim M. Gooding, Loreto Gesualdo, Massimo Papale, Irvin Teh, Hiddo J.L. Heerspink, Chrysta Lienczewski, Peter S. Gilmour, Sapna Puppala, Pirjo Nuutila, Paola Pontrelli, Mark Gilchrist, Claire Ball, Rosamonde E. Banks, David Shelley, Anil Karihaloo, Marlena Maziarz, Alberto Garcia Hernandez, iBEAt investigators, Kay Tobin, Steven Sourbron, Niina Koivuviita, Angela C. Shore, Mark Ibberson, Matthias Kretzler, Dennis L. Andress, Kanishka Sharma, Julie Bailey, Maria F. Gomez, Kaj Metsärinne, Virva Saunavaara |
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Přispěvatelé: | Groningen Kidney Center (GKC), Real World Studies in PharmacoEpidemiology, -Genetics, -Economics and -Therapy (PEGET) |
Rok vydání: | 2020 |
Předmět: |
SELECTION
Oncology Nephrology 030232 urology & nephrology Type 2 diabetes Renal decline 030204 cardiovascular system & hematology lcsh:RC870-923 Kidney Study Protocol 0302 clinical medicine Oxygen Radioisotopes Diabetic Nephropathies Prospective Studies Prospective cohort study POPULATION Ultrasonography education.field_of_study Progression medicine.diagnostic_test Prognosis DIFFUSION 3. Good health Observational Studies as Topic Disease Progression Biomarker (medicine) medicine.symptom MRI Cohort study RENAL-FUNCTION medicine.medical_specialty Population Chronic kidney disease stages 1–3 Renal function Renal Circulation 03 medical and health sciences Magnetic resonance imaging Internal medicine Ultrasound medicine Humans Albuminuria Renal Insufficiency Chronic Diabetic kidney disease education DECLINE business.industry Prospective cohort lcsh:Diseases of the genitourinary system. Urology medicine.disease Diabetes Mellitus Type 1 Diabetes Mellitus Type 2 Positron-Emission Tomography Renal blood flow Chronic kidney disease stages 1-3 business Biomarkers Blood sampling |
Zdroj: | BMC Nephrology Bmc nephrology, 21(1):242. BMC BMC Nephrology, Vol 21, Iss 1, Pp 1-11 (2020) |
ISSN: | 1471-2369 |
Popis: | Background Diabetic kidney disease (DKD) remains one of the leading causes of premature death in diabetes. DKD is classified on albuminuria and reduced kidney function (estimated glomerular filtration rate (eGFR)) but these have modest value for predicting future renal status. There is an unmet need for biomarkers that can be used in clinical settings which also improve prediction of renal decline on top of routinely available data, particularly in the early stages. The iBEAt study of the BEAt-DKD project aims to determine whether renal imaging biomarkers (magnetic resonance imaging (MRI) and ultrasound (US)) provide insight into the pathogenesis and heterogeneity of DKD (primary aim) and whether they have potential as prognostic biomarkers in DKD (secondary aim). Methods iBEAt is a prospective multi-centre observational cohort study recruiting 500 patients with type 2 diabetes (T2D) and eGFR ≥30 ml/min/1.73m2. At baseline, blood and urine will be collected, clinical examinations will be performed, and medical history will be obtained. These assessments will be repeated annually for 3 years. At baseline each participant will also undergo quantitative renal MRI and US with central processing of MRI images. Biological samples will be stored in a central laboratory for biomarker and validation studies, and data in a central data depository. Data analysis will explore the potential associations between imaging biomarkers and renal function, and whether the imaging biomarkers improve the prediction of DKD progression. Ancillary substudies will: (1) validate imaging biomarkers against renal histopathology; (2) validate MRI based renal blood flow measurements against H2O15 positron-emission tomography (PET); (3) validate methods for (semi-)automated processing of renal MRI; (4) examine longitudinal changes in imaging biomarkers; (5) examine whether glycocalyx and microvascular measures are associated with imaging biomarkers and eGFR decline; (6) explore whether the findings in T2D can be extrapolated to type 1 diabetes. Discussion iBEAt is the largest DKD imaging study to date and will provide valuable insights into the progression and heterogeneity of DKD. The results may contribute to a more personalised approach to DKD management in patients with T2D. Trial registration Clinicaltrials.gov (NCT03716401). |
Databáze: | OpenAIRE |
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