期刊论文详细信息
BMC Nephrology
Diabetic nephropathy in a sibling and albuminuria predict early GFR decline: a prospective cohort study
Jeffrey R Schelling1  John R Sedor2  Charles Thomas1  Sudha K Iyengar4  Abdus Sattar4  Gregory B Russell3  Alicia O’Brien1  Robert L Thomas1  Anthony J Bleyer3  Douglas Gunzler1 
[1] Department of Medicine, Case Western Reserve University, 2500 MetroHealth Drive, Rammelkamp R415, Cleveland, OH, 44109, USA;Department of Physiology and Biophysics, Case Western Reserve University, 2500 MetroHealth Drive, Rammelkamp R415, Cleveland, OH, 44109, USA;Department of Medicine, Division on Nephrology, Wake Forest University, Medical Center Blvd, Winston Salem, NC, 27157, USA;Department of Epidemiology and Biostatistics, Case Western Reserve University, 2500 MetroHealth Drive, Rammelkamp R415, Cleveland, OH, 44109, USA
关键词: Proteinuria;    Progression;    Genetics;    ESRD;    Diabetes;    CKD;    Albuminuria;   
Others  :  1082915
DOI  :  10.1186/1471-2369-14-124
 received in 2013-02-13, accepted in 2013-06-05,  发布年份 2013
PDF
【 摘 要 】

Background

Diabetic nephropathy is a growing clinical problem, and the cause for >40% of incident ESRD cases. Unfortunately, few modifiable risk factors are known. The objective is to examine if albuminuria and history of diabetic nephropathy (DN) in a sibling are associated with early DN progression or mortality.

Methods

In this longitudinal study of adults >18 yrs with diabetes monitored for up to 9 yrs (mean 4.6 ± 1.7 yrs), 435 subjects at high risk (DN family history) and 400 at low risk (diabetes >10 yrs, normoalbuminuria, no DN family history) for DN progression were evaluated for rate of eGFR change using the linear mixed effects model and progression to ESRD. All-cause mortality was evaluated by Kaplan-Meier analyses while controlling for baseline covariates in a Cox proportional hazards model. Covariates included baseline eGFR, age, gender, race, diabetes duration, blood pressure, hemoglobin A1c and urine albumin:creatinine ratio. Propensity score matching was used to identify high and low risk group pairs with balanced covariates. Sensitivity analyses were employed to test for residual confounding.

Results

Mean baseline eGFR was 74 ml/min/1.73 m2 (86% of cohort >60 ml/min/1.73 m2). Thirty high risk and no low risk subjects developed ESRD. eGFR decline was significantly greater in high compared to low risk subjects. After controlling for confounders, change in eGFR remained significantly different between groups, suggesting that DN family history independently regulates GFR progression. Mortality was also significantly greater in high versus low risk subjects, but after controlling for baseline covariates, no significant difference was observed between groups, indicating that factors other than DN family history more strongly affect mortality. Analyses of the matched pairs confirmed change in eGFR and mortality findings. Sensitivity analyses demonstrated that the eGFR results were not due to residual confounding by unmeasured covariates of a moderate effect size in the propensity matching.

Conclusions

Diabetic subjects with albuminuria and family history of DN are vulnerable for early GFR decline, whereas subjects with diabetes for longer than 10 years, normoalbuminuria and negative family history, experience slower eGFR decline, and are extremely unlikely to require dialysis. Although we would not recommend that patients with low risk characteristics be neglected, scarce resources would be more sensibly devoted to vulnerable patients, such as the high risk cases in our study, and preferably prior to the onset of albuminuria or GFR decline.

【 授权许可】

   
2013 Gunzler et al.; licensee BioMed Central Ltd.

【 预 览 】
附件列表
Files Size Format View
20141224190056197.pdf 555KB PDF download
Figure 4. 24KB Image download
Figure 3. 42KB Image download
Figure 2. 33KB Image download
Figure 1. 35KB Image download
【 图 表 】

Figure 1.

Figure 2.

Figure 3.

Figure 4.

【 参考文献 】
  • [1]Harris MI, Klein R, Welborn TA, Knuiman MW: Onset of NIDDM occurs at least 4-7 yr before clinical diagnosis. Diabetes Care 1992, 15:815-819.
  • [2]Perkins BA, Ficociello LH, Silva KH, Finkelstein DM, Warram JH, Krolewski AS: Regression of microalbuminuria in type 1 diabetes. N Engl J Med 2003, 348:2285-2293.
  • [3]Caramori ML, Fioretto P, Mauer M: Low glomerular filtration rate in normoalbuminuric type 1 diabetic patients - An indicator of more advanced glomerular lesions. Diabetes 2003, 52:1036-1040.
  • [4]de Boer IH, Rue TC, Hall YN, Heagerty PJ, Weiss NS, Himmelfarb J: Temporal trends in the prevalence of diabetic kidney disease in the United States. JAMA 2011, 305:2532-2539.
  • [5]Mogensen CE: Microalbuminuria predicts clinical proteinuria and early mortality in maturity-onset diabetes. N Engl J Med 1984, 310:356-360.
  • [6]Go AS, Chertow GM, Fan D, McCulloch CE, Hsu CY: Chronic kidney disease and the risks of death, cardiovascular events, and hospitalization. N Engl J Med 2004, 351:1296-1305.
  • [7]Al-Aly Z, Zeringue A, Fu J, Rauchman MI, McDonald JR, El-Achkar TM, et al.: Rate of kidney function decline associates with mortality. J Am Soc Nephrol 2010, 21:1961-1969.
  • [8]Peralta CA, Shlipak MG, Judd S, Cushman M, McClellan W, Zakai NA, et al.: Detection of chronic kidney disease with creatinine, cystatin C, and urine albumin-to-creatinine ratio and association with progression to end-stage renal disease and mortality. JAMA 2011, 305:1545-1552.
  • [9]Pavkov ME, Knowler WC, Lemley KV, Mason CC, Myers BD, Nelson RG: Early renal function decline in type 2 diabetes. Clin J Am Soc Nephrol 2012, 7:78-84.
  • [10]Matsushita K, van der Velde M, Astor BC, Woodward M, Levey AS, De Jong PE, et al.: Association of estimated glomerular filtration rate and albuminuria with all-cause and cardiovascular mortality in general population cohorts: a collaborative meta-analysis. Lancet 2010, 375:2073-2081.
  • [11]Tonelli M, Muntner P, Lloyd A, Manns BJ, James MT, Klarenbach S, et al.: Using proteinuria and estimated glomerular filtration rate to classify risk in patients with chronic kidney disease: a cohort study. Ann Intern Med 2011, 154:12-21.
  • [12]Schelling JR, Zarif L, Sehgal A, Iyengar S, Sedor JR: Genetic susceptibility to end-stage renal disease. Curr Opin Nephrol Hypertens 1999, 8:465-472.
  • [13]Bleyer AJ, Sedor JR, Freedman BI, O'Brien A, Russell GB, Graley J, et al.: Risk factors for development and progression of diabetic kidney disease and treatment patterns among diabetic siblings of patients with diabetic kidney disease. Am J Kidney Dis 2008, 51:29-37.
  • [14]Inker LA, Eckfeldt J, Levey AS, Leiendecker-Foster C, Rynders G, Manzi J, et al.: Expressing the CKD-EPI (Chronic Kidney Disease Epidemiology Collaboration) cystatin C equations for estimating GFR with standardized serum cystatin C values. Am J Kidney Dis 2011, 58:682-684.
  • [15]Rubin DB: Multiple imputation after 18+ years. J Am Stat Assoc 1996, 91:473-489.
  • [16]Fitzmaurice GM, Laird NM, Ware JH: Applied Longitudinal Analysis. New York: John Wiley and Sons; 2004.
  • [17]Rosenbaum PR, Rubin DB: The central role of the propensity score in observational studies for causal effects. Biometrika 1983, 70:41-55.
  • [18]Rosenbaum PR: Design of Observational Studies. New York: Springer; 2010.
  • [19]Cox RD, Oakes D: Analysis of Survival Data. London: Chapman & Hall; 1984.
  • [20]Andersen PK, Gill RD: Cox's regression model counting process: A large sample study. Ann Stat 1982, 10:1100-1120.
  • [21]Klahr S, Levey AS, Beck GJ, Caggiula AW, Hunsicker L, Kusek JW, et al.: The effects of dietary protein restriction and blood-pressure control on the progression of chronic renal disease. Modification of Diet in Renal Disease Study Group. N Engl J Med 1994, 330:877-884.
  • [22]Lash JP, Go AS, Appel LJ, He J, Ojo A, Rahman M, et al.: Chronic Renal Insufficiency Cohort (CRIC) Study: Baseline Characteristics and Associations with Kidney Function. Clin J Am Soc Nephrol 2009, 8:1302-1311.
  • [23]Wolf G, Sharma K, Ziyadeh FN: Pathophysiology and pathogenesis of diabetic nephropathy. In Seldin and Giebisch's The Kidney: Physiology and Pathophysiology. Fourth edition. Edited by Alpern RJ, Hebert SC. Waltham: Academic; 2008:2215-2233.
  • [24]Quinn M, Angelico MC, Warram JH, Krolewski AS: Familial factors determine the development of diabetic nephropathy in patients with IDDM. Diabetologia 1996, 39:940-945.
  • [25]Imperatore G, Hanson RL, Pettitt DJ, Kobes S, Bennett PH, Knowler WC: Sib-pair linkage analysis for susceptibility genes for microvascular complications among Pima Indians with type 2 diabetes. Pima Diabetes Genes Group. Diabetes 1998, 47:821-830.
  • [26]Freedman BI, Tuttle AB, Spray BJ: Familial predisposition to nephropathy in African-Americans with non-insulin-dependent diabetes mellitus. Am J Kidney Dis 1995, 25:710-713.
  • [27]Iyengar SK, Freedman BI, Sedor JR: Mining the genome for susceptibility to diabetic nephropathy: the role of large-scale studies and consortia. Semin Nephrol 2007, 27:208-222.
  • [28]Freedman BI, Soucie JM, Kenderes B, Krisher J, Garrett LE, Caruana RJ, et al.: Family history of end-stage renal disease does not predict dialytic survival. Am J Kidney Dis 2001, 38:547-552.
  • [29]Forsblom C, Harjutsalo V, Thorn LM, Waden J, Tolonen N, Saraheimo M, et al.: Competing-risk analysis of ESRD and death among patients with type 1 diabetes and macroalbuminuria. J Am Soc Nephrol 2011, 22:537-544.
  • [30]Packham DK, Alves TP, Dwyer JP, Atkins R, de Zeeuw D, Cooper M, et al.: Relative incidence of ESRD versus cardiovascular mortality in proteinuric type 2 diabetes and nephropathy: results from the DIAMETRIC (Diabetes Mellitus Treatment for Renal Insufficiency Consortium) database. Am J Kidney Dis 2012, 59:75-83.
  • [31]Skupien J, Warram JH, Smiles AM, Niewczas MA, Gohda T, Pezzolesi MG, et al.: The early decline in renal function in patients with type 1 diabetes and proteinuria predicts the risk of end-stage renal disease. Kidney Int 2012, 82:589-597.
  • [32]Adler AI, Stevens RJ, Manley SE, Bilous RW, Cull CA, Holman RR, et al.: Development and progression of nephropathy in type 2 diabetes: The United Kingdom Prospective Diabetes Study (UKPDS 64). Kidney Int 2003, 63:225-232.
  • [33]Niewczas MA, Gohda T, Skupien J, Smiles AM, Walker WH, Rosetti F, et al.: Circulating TNF Receptors 1 and 2 Predict ESRD in Type 2 Diabetes. J Am Soc Nephrol 2012, 23:507-515.
  • [34]Lemley KV, Boothroyd DB, Blouch KL, Nelson RG, Jones LI, Olshen RA, et al.: Modeling GFR trajectories in diabetic nephropathy. Am J Physiol Renal Physiol 2005, 289:F863-F870.
  • [35]Hsu CY, Propert K, Xie D, Hamm L, He J, Miller E, et al.: Measured GFR does not outperform estimated GFR in predicting CKD-related complications. J Am Soc Nephrol 2011, 22:1931-1937.
  • [36]Padala S, Tighiouart H, Inker LA, Contreras G, Beck GJ, Lewis J, et al.: Accuracy of a GFR estimating equation over time in people with a wide range of kidney function. Am J Kidney Dis 2012, 60:217-224.
  • [37]Brick JM, Kalton G: Handling missing data in survey research. Stat Methods Med Res 1996, 5:215-238.
  文献评价指标  
  下载次数:26次 浏览次数:5次