Prognostic Imaging Biomarkers for Diabetic Kidney Disease
试验速览
- 阶段
- 不适用
- 状态
- 招募中
- 入组人数
- 500
- 试验地点
- 7
- 主要终点
- Cross-sectional (multi-centre collaboration)
研究概览
简要总结
Diabetic kidney disease (DKD) is a common complication of diabetes, and is now the most common form of chronic kidney disease. DKD is the leading cause of kidney disease requiring dialysis or kidney transplantation, and its global incidence and prevalence have reached epidemic levels. While the risk of developing DKD can be ameliorated by tight blood glucose and blood pressure control, it is not fully preventable and once established DKD cannot be cured. Therefore many patients are left with poor and worsening health and with increased mortality risk. Developing new ways to treat DKD requires healthcare professionals to be able to identify those patients most in need of treatment.
One promising approach for identifying patients that are at risk is the use of imaging measurements (called "biomarkers") derived from Magnetic Resonance Imaging (MRI) and Ultrasound (US) of the kidneys. Evidence from early studies shows that such imaging biomarkers can identify underlying problems in DKD such as blood supply, oxygen supply, kidney scarring and kidney function, in ways that are better than those currently available.
The investigators think that imaging biomarkers will improve the identification of patients who are likely to decline from DKD in the short term. The changes found by imaging may even happen before effects on the blood and urine.
The investigators plan to test this hypothesis by performing a study observing 500 patients with early stage DKD, recruited in 5 sites across Europe. All patients will have detailed assessment at the start of their involvement, including clinical assessment, blood and urine samples, and MRI and US scans. The investigators will look at whether imaging biomarkers are associated with other measures that predict progression in DKD, and follow patients every year for 3 years (4 years total study participation) to see if the imaging biomarkers predict worsening DKD.
详细描述
STUDY OVERVIEW
Prognostic Imaging Biomarkers for Diabetic Kidney Disease (iBEAt) is a prospective observational multi-centre collaborative cohort study, conducted in 6 European countries. It will have a first phase with a cross-sectional design (for an association study - primary objective) and a second phase with a longitudinal design (for a prognostic objective - secondary objective).
All 5 recruiting centres will follow the same recruitment criteria and take the same data using a standardised methodology, including demographic, clinical and family history, medication history, blood- and urine samples as well as MRI and US. Annual follow-up visits will occur in years 2,3,4, where the same data will be collected except MRI and US (acquired only at baseline). In addition, each of the centres will acquire additional centre-specific data to address ancillary objectives.
All biofluids will be processed on site, stored temporarily and shipped in batches to a central biobank for central analysis and long-term storage (University of Lund, Malmo, Sweden). Hemoglobin, Hematocrit and HbA1c will be measured locally on fresh blood. A proportion of the biofluids will be analysed centrally to address the objectives. The remainder will be stored for future biomarker validation studies to be determined by the study Steering Committee in line with objectives of the Biomarker Enterprise to Attack DKD (BEAt-DKD).
All data generated by the study will be centralised in anonymised form in an archive hosted by the Swiss Institute of Bioinformatics. Data access will be limited to licensed study investigators and ancillary studies approved by the steering committee. MRI images will be analysed centrally in the University of Leeds to extract the imaging biomarkers.
研究设计
- 研究类型
- Observational
- 观察模型
- Cohort
- 时间视角
- Cross Sectional
入排标准
- 年龄范围
- 18 Years 至 80 Years（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •Diagnosis Diabetes Type 2;
- •eGFR >= 30 ml/min/1.73m2;
- •Able to provide informed consent;
- •Age between 18 years and 80 years;
- •Unchanged antidiabetic and antihypertensive medication for the past 3 months (not including dose changes).
排除标准
- •Transplantation (except corneal);
- •On permanent dialysis;
- •Significant comorbidities with life expectancy of < 1 year;
- •Use of investigational drug within 1 month prior to screening;
- •Known clinical history of urinary obstruction on renal US: either post-voiding residue over 100 ml, or pyelectasis;
- •Known clinical history of aortic endoprosthesis at the renal level;
- •Current pregnancy;
- •History of Hepatitis B or Hepatitis C +;
- •Use of antiretroviral medication;
- •Known current or clinical history of renal or urinary tract malignancy;
- •Concurrent other renal disease (suspected or proven);
- •Cirrhotic liver disease, or non-cirrhotic chronic liver disease where ALT >2 x upper limit of normal;
- •Current metastatic malignancy;
- •Current malignancy with expected survival < study follow up period (4 years);
- •Melanomatous skin cancer < 5 years ago (fully resected melanoma >5 years ago, i.e. surgical cure, can be recruited);
- •Any other significant disease or disorder which, in the opinion of the investigators, may either put the patient at risk because of participation in the study, or may influence the result of the study, or the patient's ability to participate in the study;
- •Cochlear Implant;
- •Aneurysm Clips;
- •Neurological stimulator;
- •Implanted cardiac devices (ICD, PPM, loop recorders, or any others);
- •Metal heart valve;
- •History of metal foreign bodies in orbits;
- •Other implanted metal device which prevents MR imaging;
- •Known allergy to Gadolinium contrast;
- •Claustrophobia;
- •Weight exceeding 250 kg;
- •[Bari arm] Absolute contraindications to percutaneous renal biopsy;
- •[Bari arm] Bleeding diathesis;
- •[Bari arm] Severe uncontrolled hypertension;
- •[Bari arm] End stage renal disease with small hyperechoic kidneys;
结局指标
主要结局
Cross-sectional (multi-centre collaboration)
时间窗: 2 years
MRI biomarkers will be combined with fluid-based biomarkers to discover radiomics features that correlate with renal function
次要结局
- Longitudinal (multi-centre collaboration)(4 years)
研究者
Steven Sourbron
Lecturer
University of Leeds