Literature DB >> 28091412

Incidence, Development, and Prognosis of Diabetic Kidney Disease in China: Design and Methods.

Yao-Zheng Yang1, Jin-Wei Wang1, Fang Wang1, Yun-Tao Wu2, Hai-Yan Zhao2, Min Chen1, Lu-Xia Zhang1, Shou-Ling Wu2, Ming-Hui Zha1.   

Abstract

BACKGROUND: Although that glomerulonephritis is the major cause of end-stage renal disease in developing countries such as China, the increasing prevalence of diabetes has contributed to the changing spectrum of predialysis chronic kidney disease. Recent studies have revealed an increased proportion of patients with diabetic kidney disease (DKD) in hemodialysis populations in large cities in China. However, studies regarding the clinical phenotype of DKD in China are extremely limited. The incidence, development, and prognosis of diabetic kidney disease (INDEED) study aims to investigate the incidence, progression, and prognosis of DKD, as well as the associated genetic, behavioral, and environmental factors and biomarkers in patients with DKD in China.
METHODS: INDEED study is a prospective cohort study based on all participants with diabetes in the Kailuan study, which is a general population-based cohort study in northern China. Altogether, over 10,000 participants with diabetes will be followed biennially. Questionnaires documenting general characteristics, behavioral and environmental factors, and medical history will be administrated. Anthropometric measurements and a series of laboratory tests will be performed in one central laboratory. The DNA, plasma, and urine samples of every participant will be stored in a biobank for future research.
CONCLUSIONS: INDEED study will provide essential information regarding the clinical phenotype and prognosis of patients with DKD in China and will be valuable to identify factors and biomarkers associated with patients with DKD in China.

Entities:  

Mesh:

Substances:

Year:  2017        PMID: 28091412      PMCID: PMC5282677          DOI: 10.4103/0366-6999.198002

Source DB:  PubMed          Journal:  Chin Med J (Engl)        ISSN: 0366-6999            Impact factor:   2.628


Introduction

Chronic kidney disease (CKD) is an important public health problem in China because of its high prevalence and adverse effects on patients’ outcomes as well as placing a burden on health-care system.[1] In addition to entering end-stage renal disease (ESRD), patients with CKD are at increased risk of mortality and cardiovascular diseases (CVDs).[2345] Previously, glomerulonephritis was considered as the leading cause of ESRD in China.[26] A recent study[7] has revealed an increased proportion of patients with diabetic kidney disease (DKD) in hemodialysis population in large cities such as Beijing and Shanghai, which is consistent with the substantially escalating incidence of diabetes in China during the past two decades.[8910] Our recent research showed that DKD has already become the leading cause of CKD in the predialysis CKD population, surpassing glomerulonephritis, and hence, it will inevitably become the major cause accounting for dialysis in the near future.[7] However, studies regarding risk factors, clinical phenotype, progression, treatment, and prognosis of DKD are limited in Chinese populations. This is in part due to the late referral to nephrologists of patients with DKD. The Kailuan study,[1112] an ongoing longitudinal prospective study based on the general population, provides a unique opportunity to investigate DKD in China. Therefore, the Renal Division of Peking University First Hospital, in collaboration with the Kailuan study, has initiated the incidence, development, and prognosis of diabetic kidney disease (INDEED) study, which aims to provide reliable data on the clinical phenotype, the genetic, behavioral, and environmental factors, and biomarkers associated with DKD in China.

Methods

Study design

INDEED study is a prospective cohort study based on all participants with diabetes in the Kailuan study. Detailed information about the Kailuan study was described elsewhere.[1112] In brief, it is an ongoing longitudinal cohort study based on the general population that began in 2006. Altogether, 101,510 individuals (81,110 men and 20,400 women, aged ≥18 years), who were employees (including the retired) of the Kailuan Group and their family members, were recruited to undergo questionnaire assessments and clinical and laboratory examinations conducted in the 11 hospitals affiliated with the Kailuan community in Tangshan.[1112] The information collected included demographic characteristics, medical comorbidities (e.g., hypertension, diabetes, and CVDs), and lifestyle behaviors (e.g., smoking status, alcohol consumption, and physical activity). Furthermore, pulse wave velocity and ankle-brachial index were measured among certain subgroups.[12] Then, four repeated follow-up examinations were conducted biennially from 2008 to 2014. For INDEED study, all participants with diabetes in the Kailuan study were included and were prospectively followed with a focus on DKD. The DNA, plasma, and urine samples of every participant will be stored in a biobank for future research. The duration of INDEED study is tentatively fixed at 5 years.

Study organization

INDEED study was initiated by the Renal Division of Peking University First Hospital, collaborating with investigators in the Kailuan study. The Kailuan study investigators took charge of on-site investigation, including enrollment and follow-up of participants, processing and transferring samples, distributing and gathering questionnaires, and data collection. Peking University First Hospital performed the central laboratory tests and constructed the central biobank. In addition, we set up a steering committee to develop policies for ancillary studies, performance standards, publications, and presentations; and a scientific advisory committee to provide professional advice about the study protocol and practice. The INDEED study was approved by the Ethics Committee of the Peking University First Hospital in compliance with the World's Association Declaration of Helsinki. All of the participants gave written informed consent before data collection.

Participants

INDEED study will enroll all patients with diabetes in the Kailuan study based on existing data. The inclusion criteria are self-reported history of diabetes mellitus and/or fasting blood glucose ≥7.0 mmol/L and/or self-reported use of antidiabetic medications. INDEED study will recruit 11,192 patients with diabetes on the basis of existing data from the 2014 Kailuan study.[13]

Baseline and follow-up visit

The baseline visit for INDEED study began in April 2016. In addition to the questionnaire and original tests performed for the Kailuan study, a set of questionnaires regarding the diagnosis and treatment of diabetes, lifestyle and environmental risk factors, complication of diabetes including DKD, and cognitive function was administrated. Furthermore, biosamples including fasting blood and morning urine samples were transported to the Peking University First Hospital in cold chain of −80° C. Laboratory tests including plasma creatinine, cystatin C, HbA1C, retinol-binding protein; urinary protein-creatinine ratio, albumin-creatinine ratio, orosomucoid, transferrin, and α-microglobulin were measured in the central laboratory to avoid variations in testing values among laboratories. All participants will be followed biennially using protocols similar to the baseline visit.

Biobank

DNA, plasma, and morning spot urine samples from each participant will be collected at baseline and biennially. All biosamples will be stored at −80 °C for future scientific research. A biobank management system will ensure the quality control of sample management.

Study outcomes

The principal clinical outcomes of INDEED can be categorized as CVD events, renal disease events, and death. CVD events include myocardial infarction, coronary artery disease such as angina pectoris, congestive heart failure, cardiac arrhythmia (resuscitated cardiac arrest, ventricular fibrillation, ventricular tachycardia, atrial fibrillation or flutter, sever bradycardia or atrioventricular block), cerebrovascular events (such as intraparenchymal hemorrhage, subarachnoid hemorrhage, cerebral infarction, and cardioembolic cerebral infarction), peripheral vascular diseases, and venous thrombosis.[14] All CVD events will be acquired from the health insurance reimbursement record and were ascertained by chart review of medical records. Renal disease events include entering ESRD or a reduction of estimated glomerular filtration rate (eGFR) by half. ESRD is defined as receiving renal replacement therapy, involving dialysis and kidney transplantation. eGFR will be calculated using the CKD Epidemiology Collaboration (CKD-EPI) equation (see below)[15] based on serum creatinine concentration (Scr) at every visit. ESRD will also be acquired from the health insurance reimbursement record and will be ascertained by chart review of medical records. CKD-EPI equation: eGFR (ml·min−1·1.73 m−2) = 144 × (Scr/0.7)−0.3289 × (0.993)Age (if female, Scr ≤0.7 mg/dl) eGFR (ml·min−1·1.73 m−2) = 144 × (Scr/0.7)−1.209 × (0.993)Age (if female, Scr >0.7 mg/dl) eGFR (ml·min−1·1.73 m−2) = 141 × (Scr/0.9)−0.411 × (0.993)Age (if male, Scr ≤0.9 mg/dl) eGFR (ml·min−1·1.73 m−2) = 141 × (Scr/0.9)−1.209 × (0.993)Age (if male, Scr >0.9 mg/dl).

Statistical consideration

The baseline characteristics will be presented with descriptive methods such as summary statistics and frequency tables. We will calculate the incidence or mortality according to the existing data from the Kailuan study, which enrolled more than 100,000 people for the biennial follow-up examinations. Then, Kaplan-Meier curves, log-rank tests, and Cox proportional hazards models will be employed to estimate the survival function from lifetime data, compare the survival distributions of patients in various subgroups, and explore the associations of baseline variables with study outcomes.[16] Standard mixed-effects growth curve models supplemented by generalized estimating equations will be used for variables with repeated measurements such as eGFR. Analyses will also be adjusted for potential confounding factors and stratified by potential effect modifiers. All statistical analyses will be conducted in SAS version 9.3 (SAS Institute, Inc., Cary, NC, USA). Values will be considered statistically significant when P < 0.05.

Discussion

Glomerulonephritis in developing countries such as China was traditionally the major cause of CKD.[26] However, the rapidly increasing incidence of diabetes has played a key role in the transition of the predialysis CKD spectrum.[7] An increasing proportion of patients with DKD among incident hemodialysis patients in large cities in China has been observed,[7] which is consistent with the continuous growth of diabetes in the past 20 years. Despite the increasing incidence of DKD, as a result of the increasing incidence of diabetes, an unmet need exists in China for information about the incidence and development of DKD. Furthermore, most patients with diabetes are not referred to nephrologists until they have reached ESRD. All of the above-mentioned issues constitute obstacles to the early prevention and treatment of DKD. INDEED study, which was established by both renal division of the Peking University First Hospital and Kailuan study, offers a unique opportunity to explore the clinical phenotype, genetic, behavioral, and environmental factors and biomarkers associated with DKD. The data about diabetes and patients with DKD at a relatively early stage collected in INDEED study will provide valuable information for early identification and interventions for high-risk DKD populations, which is crucial in reducing the burden of CKD in China. A set of strategies were set up for the sake of quality control of this study. A manual of procedures with detailed instructions about the study protocol has been distributed to all study centers of the Kailuan study. All study investigators and staff members completed a training program that taught the methods and process of the study. Periodic on-site monitoring will be repeated every 3 months. In addition to describing the clinical phenotype of DKD, we expect that INDEED study can provide more insight into the diagnosis, pathogenesis, and treatment of DKD. Albuminuria and eGFR were traditionally used as early markers of glomerular damage.[17] However, given that many diabetic patients do not develop albuminuria when they suffer from irreparable renal impairment,[1819] and not all patients with proteinuria will develop progressive kidney dysfunction,[20] new biomarkers are needed to provide better prediction of incidence and progression of DKD. The establishment of the biobank, together with information about the clinical phenotype, could offer opportunities for discovering novel biomarkers associated with the diagnosis and prediction of DKD, exploring the genetic background of DKD, and searching for new targets for intervention. In conclusion, the INDEED study is designed to collect longitudinal data and biomaterials from a cohort of general population-based patients with diabetes in China. The aim is to provide essential information regarding the clinical phenotype and prognosis of patients with DKD in China and may be able to identify biomarkers associated with the incidence and progression of DKD. Results from the INDEED study will provide reliable data regarding formulating the prevention and intervention strategies for DKD in China.

Financial support and sponsorship

The study was supported by the grants from National Key Technology R & D Program of the Ministry of Science and Technology (No. 2011BAI10B01, and No. 2013BAI09B14), establishment of early diagnosis pathway and model for evaluating progression of chronic kidney disease (No. D131100004713007) from the Beijing Science and Technology Committee, and the National Natural Science Fund (No. 81425008).

Conflicts of interest

There are no conflicts of interest.
  20 in total

1.  Prevalence of diabetes among men and women in China.

Authors:  Wenying Yang; Juming Lu; Jianping Weng; Weiping Jia; Linong Ji; Jianzhong Xiao; Zhongyan Shan; Jie Liu; Haoming Tian; Qiuhe Ji; Dalong Zhu; Jiapu Ge; Lixiang Lin; Li Chen; Xiaohui Guo; Zhigang Zhao; Qiang Li; Zhiguang Zhou; Guangliang Shan; Jiang He
Journal:  N Engl J Med       Date:  2010-03-25       Impact factor: 91.245

2.  Chronic kidney disease in the developing world.

Authors:  Rashad S Barsoum
Journal:  N Engl J Med       Date:  2006-03-09       Impact factor: 91.245

Review 3.  Novel urinary biomarkers in early diabetic kidney disease.

Authors:  Atsuko Kamijo-Ikemori; Takeshi Sugaya; Kenjiro Kimura
Journal:  Curr Diab Rep       Date:  2014-08       Impact factor: 4.810

Review 4.  Prevention programmes of progressive renal disease in developing nations.

Authors:  Igor Codreanu; Norberto Perico; Sanjib K Sharma; Arrigo Schieppati; Giuseppe Remuzzi
Journal:  Nephrology (Carlton)       Date:  2006-08       Impact factor: 2.506

5.  Prevalence and control of diabetes in Chinese adults.

Authors:  Yu Xu; Limin Wang; Jiang He; Yufang Bi; Mian Li; Tiange Wang; Linhong Wang; Yong Jiang; Meng Dai; Jieli Lu; Min Xu; Yichong Li; Nan Hu; Jianhong Li; Shengquan Mi; Chung-Shiuan Chen; Guangwei Li; Yiming Mu; Jiajun Zhao; Lingzhi Kong; Jialun Chen; Shenghan Lai; Weiqing Wang; Wenhua Zhao; Guang Ning
Journal:  JAMA       Date:  2013-09-04       Impact factor: 56.272

Review 6.  New insights into the use of biomarkers of diabetic nephropathy.

Authors:  Jay C Jha; Karin A M Jandeleit-Dahm; Mark E Cooper
Journal:  Adv Chronic Kidney Dis       Date:  2014-05       Impact factor: 3.620

7.  Prevalence of diabetes and its risk factors in China, 1994. National Diabetes Prevention and Control Cooperative Group.

Authors:  X R Pan; W Y Yang; G W Li; J Liu
Journal:  Diabetes Care       Date:  1997-11       Impact factor: 19.112

Review 8.  Prevention of the progression of chronic kidney disease: practice in China.

Authors:  Haiyan Wang; Luxia Zhang; Jicheng Lv
Journal:  Kidney Int Suppl       Date:  2005-04       Impact factor: 10.545

9.  Ideal cardiovascular health metrics and the risks of ischemic and intracerebral hemorrhagic stroke.

Authors:  Qian Zhang; Yong Zhou; Xiang Gao; Chunxue Wang; Shufeng Zhang; Anxin Wang; Na Li; Liheng Bian; Jianwei Wu; Qian Jia; Shouling Wu; Xingquan Zhao
Journal:  Stroke       Date:  2013-07-18       Impact factor: 7.914

10.  A new equation to estimate glomerular filtration rate.

Authors:  Andrew S Levey; Lesley A Stevens; Christopher H Schmid; Yaping Lucy Zhang; Alejandro F Castro; Harold I Feldman; John W Kusek; Paul Eggers; Frederick Van Lente; Tom Greene; Josef Coresh
Journal:  Ann Intern Med       Date:  2009-05-05       Impact factor: 25.391

View more
  10 in total

1.  Establishment and Validation of a Nomogram Model for Prediction of Diabetic Nephropathy in Type 2 Diabetic Patients with Proteinuria.

Authors:  Dong-Mei Zhou; Jing Wei; Ting-Ting Zhang; Feng-Jie Shen; Jin-Kui Yang
Journal:  Diabetes Metab Syndr Obes       Date:  2022-04-08       Impact factor: 3.168

Review 2.  Urinary Biomarkers for Chronic Kidney Disease with a Focus on Gene Transcript.

Authors:  Lin-Li Lyu; Ye Feng; Bi-Cheng Liu
Journal:  Chin Med J (Engl)       Date:  2017-09-20       Impact factor: 2.628

3.  Pathology and Prognosis of Type 2 Diabetes Mellitus with Renal Involvement.

Authors:  Lu Cheng; Ping Fu
Journal:  Chin Med J (Engl)       Date:  2017-04-20       Impact factor: 2.628

4.  Identification of Transcription Regulatory Relationships in Diabetic Nephropathy.

Authors:  Jing-Song Shi; Dan-Dan Qiu; Wei-Bo Le; Hui Wang; Shen Li; Yin-Hui Lu; Song Jiang
Journal:  Chin Med J (Engl)       Date:  2018-12-05       Impact factor: 2.628

5.  Clinicopathological Features of Nondiabetic Renal Diseases from Different Age Groups: An Observational Cross-sectional Study.

Authors:  Xiao-Min Liu; Qian Wang; Zhe-Yi Dong; Wei-Guang Zhang; Guang-Yan Cai; Li Zhang; Yong Wang; Han-Yu Zhu; Li Tang; Wan-Jun Shen; Xiang-Mei Chen
Journal:  Chin Med J (Engl)       Date:  2018-12-20       Impact factor: 2.628

6.  Effects of Keluoxin capsule combined with losartan potassium on diabetic kidney disease: study protocol for a randomized double-blind placebo-controlled multicenter clinical trial.

Authors:  Rui Wu; Fan Wei; Lianlian Qu; Litao Bai; Jun Li; Fei Li; Weitian Yan; Qiuhong Wang; Junping Wei
Journal:  Trials       Date:  2020-11-23       Impact factor: 2.279

7.  Diagnostic value of triglyceride and cystatin C ratio in diabetic kidney disease: a retrospective and prospective cohort study based on renal biopsy.

Authors:  Jing Wei; Bo Wang; Feng-Jie Shen; Ting-Ting Zhang; Zan Duan; Dong-Mei Zhou
Journal:  BMC Nephrol       Date:  2022-07-27       Impact factor: 2.585

8.  Potential Value of Datura stramonium Agglutinin-recognized Glycopatterns in Urinary Protein on Differential Diagnosis of Diabetic Nephropathy and Nondiabetic Renal Disease.

Authors:  Xiao-Li Yang; Han-Jie Yu; Han-Yu Zhu; Ying Zheng; Qiu-Xia Han; Guang-Yan Cai; Xiang-Mei Chen
Journal:  Chin Med J (Engl)       Date:  2018-01-20       Impact factor: 2.628

9.  SIRT1 rs10823108 and FOXO1 rs17446614 responsible for genetic susceptibility to diabetic nephropathy.

Authors:  Yanyan Zhao; Junfang Wei; Xuefeng Hou; Huimiao Liu; Feng Guo; Yingni Zhou; Yuanyuan Zhang; Yunhui Qu; Junfei Gu; Yuanli Zhou; Xiaobin Jia; Guijun Qin; Liang Feng
Journal:  Sci Rep       Date:  2017-08-31       Impact factor: 4.379

10.  Unstably controlled systolic blood pressure trajectories are associated with markers for kidney damage in prediabetic population: results from the INDEED cohort study.

Authors:  Zi-Jun Sun; Jin-Wei Wang; Dong-Yuan Chang; Shuo-Hua Chen; Hui-Fen Zhang; Shou-Ling Wu; Kevin He; Lu-Xia Zhang; Min Chen; Ming-Hui Zhao
Journal:  J Transl Med       Date:  2020-05-12       Impact factor: 5.531

  10 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.