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Clinical Trial Details — Status: Completed

Administrative data

NCT number NCT02364323
Other study ID # GEM Study
Secondary ID
Status Completed
Phase N/A
First received
Last updated
Start date February 17, 2015
Est. completion date December 31, 2018

Study information

Verified date March 2022
Source Chinese University of Hong Kong
Contact n/a
Is FDA regulated No
Health authority
Study type Interventional

Clinical Trial Summary

The risk of diabetic kidney complications includes non-modifiable risk factors such as genetic predictors, as well as modifiable risk factors such as hyperglycaemia, hypertension, hyperlipidaemia and proteinuria. Genetic testing for personalized medicine is increasing in popularity, though evidence that genetic testing can empower patients to modify behaviour and reduce clinical risk remains lacking. In this project, the investigators aim to utilize a personalized risk counseling with genetic testing to evaluate its impact on risk factor control in diabetic patients. The investigators hypothesize that knowledge of genetic +/- clinical risk will empower patients and lead to improvement in the number of treatment targets achieved. The investigators will recruit 400 patients with diabetes. All subjects will undergo a comprehensive assessment of the risk of diabetic complications based on clinical risk factors. Half of the patients will be randomized to receive additional genetic testing of a panel of genetic markers proven to predict renal complications in our population: ACE I/D, aldose reductase (CA)n and PRKCB1 gene polymorphisms. The results of personalized risk assessment will be communicated by a health counsellor in the intervention arm. The impact of testing and patient knowledge of the result of genetic testing on achievement of treatment targets (A1c, BP, LDL-cholesterol, TG, use of ACEI/ARB) and patient behavior will be evaluated after 12 months. The other arm will receive results of the genetic testing at the completion of the study period. The study will help towards developing a strategy to empower patients through structured and personalized risk assessment will provide a novel approach to identify high-risk subjects for early intensive management, and may lead to reduction in long-term complications.


Description:

Asia is in the midst of an epidemic of diabetes. Approximately 1 in 10 people in China has diabetes [1]. Asian patients with diabetes are characterized by early age of onset and increased risk of kidney complications. Young age of onset and long disease duration will place Chinese diabetic patients at high risk for complications. In the Hong Kong Diabetes Registry, which includes more than 7000 patients with type 2 diabetes, we have reported a high risk of diabetic complications, with 30% having died or sustained a major clinical event within 10years after diagnosis, including 10% developing cardiovascular complications, and 10% developing end-stage renal disease [2] [3]. The medical costs for the diabetic patient with complication is 2.2-3.8 fold that of patients without complications, and patients with cardiorenal complications are the most costly to manage [4]. Using our registry, we have identified clinical risk predictors for developing renal complications as glycaemic control, elevated blood pressure, hyperlipidaemia, and albuminuria [2] [3, 5], and have derived clinical risk prediction algorithms and incorporated them into a patient management portal, which can generate a standardized report for risk counseling based on clinical risk factors [6, 7]. Furthermore, in a multi-centre study utilizing a multidisciplinary team, we found that intensive management aiming to achieve targets of A1c, lipids, BP can significantly reduce the risk of developing kidney complication [8]. Therefore, the ability to identify subjects at risk of complications, and to target and motivate them to optimize modifiable risk factors for diabetic complications will be of clinical benefit and potentially cost-saving. There has been much recent interest in the use of genetic testing for personalized medicine [9]. Diabetic kidney complications has high heritability of around 40% and several genetic factors have been found to be associated with diabetic renal complications. Using candidate-gene approach, our group has identified several genetic markers for diabetic kidney complications [10, 11] [12]. These include the angiotensin converting enzyme deletion/ insertion (ACE D/I) polymorphism and the aldose reductase (ALR2) 5'-(CA) n microsatellite polymorphism, each being associated with 2-3 fold increased risk of diabetic cardio-renal complications in Chinese [10, 13]. More recently, we have found that carriers of risk alleles at the protein kinase C-β1 (PRKCB1) locus can have up to 6-fold increased risk of developing end-stage renal disease during follow-up, after adjusting for the effect of clinical risk predictors [12]. The recent increase in consumer-initiated genetic testing has been driven by direct-to-consumer genetic testing, which assumes that personal genetic information can motivate positive behavioural change in patients [14]. Interestingly, a recent survey of patients without type 2 diabetes suggests that genetic testing may be able to motivate patients, with 71% of respondents reporting that they would be "much more motivated" to make behavioural changes if they were informed to be of high genetic risk for diabetes [15]. Although evidence that genetic testing can lead to behavioural changes is still lacking, several randomized clinical trials are currently underway to examine the impact of genetic testing on behaviour to reduce risk of diabetes. Given the disabling consequences of diabetic complications, and the ability to predict those at risk of developing complications, we plan to examine the role of personalized risk counseling incorporating genetic markers, and to examine its role in patient empowerment and risk factor control, which may help to reduce the risk of developing complications.


Recruitment information / eligibility

Status Completed
Enrollment 435
Est. completion date December 31, 2018
Est. primary completion date April 18, 2017
Accepts healthy volunteers No
Gender All
Age group 40 Years to 75 Years
Eligibility Inclusion Criteria: 1. Adults with type 2 diabetes aged 40-75 who can give informed consent 2. Subjects with no known chronic kidney disease (CKD defined as eGFR<60ml/min at baseline) 3. Suboptimal glucose control with HbA1c = 7.5% 4. Known history of hypertension including elevated BP =140/90 on more than one occasion Exclusion Criteria: 1. Subjects with known coronary artery disease or coronary revascularisation 2. Subjects with previous history of cerebrovascular accident 3. Subjects with known proliferative retinopathy or previous laser treatment for diabetic retinopathy 4. Subjects with life-threatening conditions including malignancy 5. Subjects with known psychiatric conditions including depression 6. Subjects with significant renal impairment (eGFR<60ml/min at baseline) or non-diabetic renal disease (e.g. biopsy-proven glomerulonephritis or obstructive uropathy) 7. Subjects with major physical disability

Study Design


Related Conditions & MeSH terms


Intervention

Behavioral:
Personalized Risk Counselling
Motivational message- towards lifestyle change, improved compliance and risk factors control Review overall control of clinical risk factors based on lab test results
Other:
Normal usual care
General education on diabetes and diabetic complications

Locations

Country Name City State
Hong Kong Prince of Wales Hospital Shatin

Sponsors (1)

Lead Sponsor Collaborator
Chinese University of Hong Kong

Country where clinical trial is conducted

Hong Kong, 

References & Publications (18)

Chan BS, Tsang MW, Lee VW, Lee KK. Cost of Type 2 Diabetes mellitus in Hong Kong Chinese. Int J Clin Pharmacol Ther. 2007 Aug;45(8):455-68. — View Citation

Chan J, So W, Ko G, Tong P, Yang X, Ma R, Kong A, Wong R, Le Coguiec F, Tamesis B, Wolthers T, Lyubomirsky G, Chow P. The Joint Asia Diabetes Evaluation (JADE) Program: a web-based program to translate evidence to clinical practice in Type 2 diabetes. Diabet Med. 2009 Jul;26(7):693-9. doi: 10.1111/j.1464-5491.2009.02751.x. — View Citation

Chan JC, So W, Ma RC, Tong PC, Wong R, Yang X. The Complexity of Vascular and Non-Vascular Complications of Diabetes: The Hong Kong Diabetes Registry. Curr Cardiovasc Risk Rep. 2011 Jun;5(3):230-239. Epub 2011 Apr 12. — View Citation

Chan JC, So WY, Yeung CY, Ko GT, Lau IT, Tsang MW, Lau KP, Siu SC, Li JK, Yeung VT, Leung WY, Tong PC; SURE Study Group. Effects of structured versus usual care on renal endpoint in type 2 diabetes: the SURE study: a randomized multicenter translational study. Diabetes Care. 2009 Jun;32(6):977-82. doi: 10.2337/dc08-1908. — View Citation

Chen S, Chiu H, Xu B, Ma Y, Jin T, Wu M, Conwell Y. Reliability and validity of the PHQ-9 for screening late-life depression in Chinese primary care. Int J Geriatr Psychiatry. 2010 Nov;25(11):1127-33. doi: 10.1002/gps.2442. — View Citation

Grant RW, Hivert M, Pandiscio JC, Florez JC, Nathan DM, Meigs JB. The clinical application of genetic testing in type 2 diabetes: a patient and physician survey. Diabetologia. 2009 Nov;52(11):2299-2305. doi: 10.1007/s00125-009-1512-7. Epub 2009 Sep 2. — View Citation

Janssens AC, Gwinn M, Bradley LA, Oostra BA, van Duijn CM, Khoury MJ. A critical appraisal of the scientific basis of commercial genomic profiles used to assess health risks and personalize health interventions. Am J Hum Genet. 2008 Mar;82(3):593-9. doi: 10.1016/j.ajhg.2007.12.020. — View Citation

Ko GT, So WY, Tong PC, Le Coguiec F, Kerr D, Lyubomirsky G, Tamesis B, Wolthers T, Nan J, Chan J. From design to implementation--the Joint Asia Diabetes Evaluation (JADE) program: a descriptive report of an electronic web-based diabetes management program. BMC Med Inform Decis Mak. 2010 May 13;10:26. doi: 10.1186/1472-6947-10-26. — View Citation

Luk AO, So WY, Ma RC, Kong AP, Ozaki R, Ng VS, Yu LW, Lau WW, Yang X, Chow FC, Chan JC, Tong PC; Hong Kong Diabetes Registry. Metabolic syndrome predicts new onset of chronic kidney disease in 5,829 patients with type 2 diabetes: a 5-year prospective analysis of the Hong Kong Diabetes Registry. Diabetes Care. 2008 Dec;31(12):2357-61. doi: 10.2337/dc08-0971. Epub 2008 Oct 3. — View Citation

Ma RC, Tam CH, Wang Y, Luk AO, Hu C, Yang X, Lam V, Chan AW, Ho JS, Chow CC, Tong PC, Jia W, Ng MC, So WY, Chan JC. Genetic variants of the protein kinase C-beta 1 gene and development of end-stage renal disease in patients with type 2 diabetes. JAMA. 2010 Aug 25;304(8):881-9. doi: 10.1001/jama.2010.1191. — View Citation

Malandrino N, Smith RJ. Personalized medicine in diabetes. Clin Chem. 2011 Feb;57(2):231-40. doi: 10.1373/clinchem.2010.156901. Epub 2010 Dec 2. Review. — View Citation

Shiu AT, Martin CR, Thompson DR, Wong RY. Psychometric properties of the Chinese version of the diabetes empowerment scale. Psychol Health Med. 2006 May;11(2):198-208. — View Citation

So WY, Wang Y, Ng MC, Yang X, Ma RC, Lam V, Kong AP, Tong PC, Chan JC. Aldose reductase genotypes and cardiorenal complications: an 8-year prospective analysis of 1,074 type 2 diabetic patients. Diabetes Care. 2008 Nov;31(11):2148-53. doi: 10.2337/dc08-0712. Epub 2008 Aug 20. — View Citation

Ting RZ, Nan H, Yu MW, Kong AP, Ma RC, Wong RY, Loo K, So WY, Chow CC, Ko GT, Wing YK, Chan JC. Diabetes-related distress and physical and psychological health in chinese type 2 diabetic patients. Diabetes Care. 2011 May;34(5):1094-6. doi: 10.2337/dc10-1612. Epub 2011 Mar 11. — View Citation

Wang Y, Luk AO, Ma RC, So WY, Tam CH, Ng MC, Yang X, Lam V, Tong PC, Chan JC. Predictive role of multilocus genetic polymorphisms in cardiovascular disease and inflammation-related genes on chronic kidney disease in Type 2 diabetes--an 8-year prospective cohort analysis of 1163 patients. Nephrol Dial Transplant. 2012 Jan;27(1):190-6. doi: 10.1093/ndt/gfr343. Epub 2011 Jul 15. — View Citation

Wang Y, Ng MC, So WY, Tong PC, Ma RC, Chow CC, Cockram CS, Chan JC. Prognostic effect of insertion/deletion polymorphism of the ace gene on renal and cardiovascular clinical outcomes in Chinese patients with type 2 diabetes. Diabetes Care. 2005 Feb;28(2):348-54. — View Citation

Yang W, Lu J, Weng J, Jia W, Ji L, Xiao J, Shan Z, Liu J, Tian H, Ji Q, Zhu D, Ge J, Lin L, Chen L, Guo X, Zhao Z, Li Q, Zhou Z, Shan G, He J; China National Diabetes and Metabolic Disorders Study Group. Prevalence of diabetes among men and women in China. N Engl J Med. 2010 Mar 25;362(12):1090-101. doi: 10.1056/NEJMoa0908292. — View Citation

Yang XL, So WY, Kong AP, Clarke P, Ho CS, Lam CW, Ng MH, Lyu RR, Yin DD, Chow CC, Cockram CS, Tong PC, Chan JC. End-stage renal disease risk equations for Hong Kong Chinese patients with type 2 diabetes: Hong Kong Diabetes Registry. Diabetologia. 2006 Oct;49(10):2299-308. Epub 2006 Aug 30. — View Citation

* Note: There are 18 references in allClick here to view all references

Outcome

Type Measure Description Time frame Safety issue
Primary percentage of patients attaining = 3 pre-defined treatment targets from the following treatment targets: 1) BP <130/80 mm Hg 2) HbA1c <7% 3) Calculated LDL-cholesterol <2.6mmol/l 4) Fasting TG <2mmol/l 5) Use of ACEI or ARB primary outcome of 3 out of 5 targets achieved as defined above At 1 year
Secondary microalbuminuria as a marker of degree of renal damage new onset of microalbuminuria at 1 year follow-up At 1 year
Secondary Patient empowerment as measured on the Chinese Diabetes Empowerment Scale (DES) Score on the DES At 1 year
Secondary Patient behavior measured on the Summary of Diabetes Self-care Activities (SDSCA) Score of diabetes self-care as measured by the SDSCA At 1 year
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