Creatinine versus cystatin C for renal function-based mortality prediction in an elderly cohort: The Northern Manhattan Study


Autoři: Joshua Z. Willey aff001;  Yeseon Park Moon aff001;  S. Ali Husain aff002;  Mitchell S. V. Elkind aff001;  Ralph L. Sacco aff004;  Myles Wolf aff005;  Ken Cheung aff006;  Clinton B. Wright aff004;  Sumit Mohan aff002
Působiště autorů: Division of Nephrology, Vagelos College of Physicians and Surgeons, Columbia University Medical Center, New York, NY, United States of America aff001;  Department of Neurology, Vagelos College of Physicians and Surgeons, Columbia University, New York, NY, United States of America aff002;  Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY, United States of America aff003;  Departments of Neurology and Public Health Sciences, Leonard M. Miller School of Medicine, the McKnight Brain Institute and the Neuroscience Program, University of Miami, Miami, FL, United States of America aff004;  Division of Nephrology, Department of Medicine, Duke University School of Medicine, Durham, NC, United States of America aff005;  Department of Biostatistics, Mailman School of Public Health, Columbia University, New York, NY, United States of America aff006
Vyšlo v časopise: PLoS ONE 15(1)
Kategorie: Research Article
doi: 10.1371/journal.pone.0226509

Souhrn

Background

Estimated glomerular filtration rate (eGFR) is routinely utilized as a measure of renal function. While creatinine-based eGFR (eGFRcr) is widely used in clinical practice, the use of cystatin-C to estimate GFR (eGFRcys) has demonstrated superior risk prediction in various populations. Prior studies that derived eGFR formulas have infrequently included high proportions of elderly, African-Americans, and Hispanics.

Objective

Our objective as to compare mortality risk prediction using eGFRcr and eGFRcys in an elderly, race/ethnically diverse population.

Design

The Northern Manhattan Study (NOMAS) is a multiethnic prospective cohort of elderly stroke-free individuals consisting of a total of 3,298 participants recruited between 1993 and 2001, with a median follow-up of 18 years.

Participants

We included all Northern Manhattan Study (NOMAS) participants with concurrent measured creatinine and cystatin-C.

Main measures

The eGFRcr was calculated using the CKD-EPI 2009 equation. eGFRcys was calculated using the CKD-EPI 2012 equations. The performance of each eGFR formula in predicting mortality risk was tested using receiver-operating characteristics, calibration and reclassification. Net reclassification improvement (NRI) was calculated based on the Reynolds 10 year risk score from adjusted Cox models with mortality as an outcome. The primary hypothesis was that eGFRcys would better predict mortality than eGFRcr.

Results

Participants (n = 2988) had a mean age of 69±10.2 years and were predominantly Hispanic (53%), overweight (69%), and current or former smokers (53% combined). The mean eGFRcr (74.68±18.8 ml/min/1.73m2) was higher than eGFRcys (51.72±17.2 ml/min/1.73m2). During a mean of 13.0±5.6 years of follow-up, 53% of the cohort had died. The AUC of eGFRcys (0.73) was greater than for eGFRcr (0.67, p for difference<0.0001). The proportions of correct reclassification (NRI) based on 10 year mortality for the model with eGFRcys compared to the model with eGFRcr were 4.2% (p = 0.002).

Conclusions

In an elderly, race/ethnically diverse cohort low eGFR is associated with risk of all-cause mortality. Estimated GFR based on serum cystatin-C, in comparison to serum creatinine, was a better predictor of all-cause mortality.

Klíčová slova:

Creatinine – Curve fitting – Elderly – Geriatric nephrology – Geriatrics – Glomerular filtration rate – Hispanic people – Chronic kidney disease


Zdroje

1. Coresh J, Selvin E, Stevens LA, Manzi J, Kusek JW, Eggers P, et al. Prevalence of chronic kidney disease in the United States. Journal of the American Medical Association. 2007;298(17):2038–47. doi: 10.1001/jama.298.17.2038 17986697.

2. Stevens LA, Li S, Wang C, Huang C, Becker BN, Bomback AS, et al. Prevalence of CKD and comorbid illness in elderly patients in the United States: results from the Kidney Early Evaluation Program (KEEP). Am J Kidney Dis. 2010;55(3 Suppl 2):S23–33. doi: 10.1053/j.ajkd.2009.09.035 20172445; PubMed Central PMCID: PMC4574484.

3. Benjamin EJ, Blaha MJ, Chiuve SE, Cushman M, Das SR, Deo R, et al. Heart Disease and Stroke Statistics-2017 Update: A Report From the American Heart Association. Circulation. 2017;135(10):e146–e603. doi: 10.1161/CIR.0000000000000485 28122885; PubMed Central PMCID: PMC5408160.

4. Fox CS, Matsushita K, Woodward M, Bilo HJ, Chalmers J, Heerspink HJ, et al. Associations of kidney disease measures with mortality and end-stage renal disease in individuals with and without diabetes: a meta-analysis. Lancet. 2012;380(9854):1662–73. doi: 10.1016/S0140-6736(12)61350-6 23013602; PubMed Central PMCID: PMC3771350.

5. Bansal N, Katz R, Robinson-Cohen C, Odden MC, Dalrymple L, Shlipak MG, et al. Absolute Rates of Heart Failure, Coronary Heart Disease, and Stroke in Chronic Kidney Disease: An Analysis of 3 Community-Based Cohort Studies. JAMA Cardiol. 2017;2(3):314–8. doi: 10.1001/jamacardio.2016.4652 28002548.

6. Fukui S, Imazeki R, Amano Y, Kudo Y, Amari K, Yamamoto M, et al. Common and specific risk factors for ischemic stroke in elderly: Differences based on type of ischemic stroke and aging. Journal of the neurological sciences. 2017;380:85–91. doi: 10.1016/j.jns.2017.07.001 28870596.

7. Anand S, Johansen KL, Kurella Tamura M. Aging and chronic kidney disease: the impact on physical function and cognition. The journals of gerontology. 2014;69(3):315–22. doi: 10.1093/gerona/glt109 23913934; PubMed Central PMCID: PMC4017829.

8. Helmer C, Stengel B, Metzger M, Froissart M, Massy ZA, Tzourio C, et al. Chronic kidney disease, cognitive decline, and incident dementia: the 3C Study. Neurology. 2011;77(23):2043–51. doi: 10.1212/WNL.0b013e31823b4765 22116945.

9. Joosten H, Izaks GJ, Slaets JP, de Jong PE, Visser ST, Bilo HJ, et al. Association of cognitive function with albuminuria and eGFR in the general population. Clin J Am Soc Nephrol. 2011;6(6):1400–9. doi: 10.2215/CJN.05530610 21566108; PubMed Central PMCID: PMC3109938.

10. Greco A, Paroni G, Seripa D, Addante F, Dagostino MP, Aucella F. Frailty, disability and physical exercise in the aging process and in chronic kidney disease. Kidney Blood Press Res. 2014;39(2–3):164–8. doi: 10.1159/000355792 25117919.

11. Wilhelm-Leen ER, Hall YN, M KT, Chertow GM. Frailty and chronic kidney disease: the Third National Health and Nutrition Evaluation Survey. The American journal of medicine. 2009;122(7):664–71 e2. doi: 10.1016/j.amjmed.2009.01.026 19559169; PubMed Central PMCID: PMC4117255.

12. Afkarian M, Katz R, Bansal N, Correa A, Kestenbaum B, Himmelfarb J, et al. Diabetes, Kidney Disease, and Cardiovascular Outcomes in the Jackson Heart Study. Clin J Am Soc Nephrol. 2016;11(8):1384–91. doi: 10.2215/CJN.13111215 27340284; PubMed Central PMCID: PMC4974894.

13. Rogan A, McCarthy K, McGregor G, Hamborg T, Evans G, Hewins S, et al. Quality of life measures predict cardiovascular health and physical performance in chronic renal failure patients. PloS one. 2017;12(9):e0183926. doi: 10.1371/journal.pone.0183926 28910330; PubMed Central PMCID: PMC5598960.

14. Diamantidis CJ, Seliger SL, Zhan M, Walker L, Rattinger GB, Hsu VD, et al. A varying patient safety profile between black and nonblack adults with decreased estimated GFR. Am J Kidney Dis. 2012;60(1):47–53. doi: 10.1053/j.ajkd.2012.01.023 22483674.

15. Thorpe JM, Thorpe CT, Kennelty KA, Gellad WF, Schulz R. The impact of family caregivers on potentially inappropriate medication use in noninstitutionalized older adults with dementia. Am J Geriatr Pharmacother. 2012;10(4):230–41. doi: 10.1016/j.amjopharm.2012.05.001 22683399; PubMed Central PMCID: PMC3413778.

16. Husain SA WJ, Moon YP, Elkind MS, Sacco RL, Wolf MS, Cheung K, Wright C, Mohan S. Creatinine based renal function assessment underestimates chronic kidney disease prevalence. J Am Soc Nephrol. 2016;27:525A.

17. Willey JZ, Moon YP, Paik MC, Boden-Albala B, Sacco RL, Elkind MS. Physical activity and risk of ischemic stroke in the Northern Manhattan Study. Neurology. 2009;73(21):1774–9. doi: 10.1212/WNL.0b013e3181c34b58 19933979.

18. Stevens LA, Manzi J, Levey AS, Chen J, Deysher AE, Greene T, et al. Impact of creatinine calibration on performance of GFR estimating equations in a pooled individual patient database. Am J Kidney Dis. 2007;50(1):21–35. doi: 10.1053/j.ajkd.2007.04.004 17591522.

19. Kurella Tamura M, Wadley V, Yaffe K, McClure LA, Howard G, Go R, et al. Kidney function and cognitive impairment in US adults: the Reasons for Geographic and Racial Differences in Stroke (REGARDS) Study. Am J Kidney Dis. 2008;52(2):227–34. doi: 10.1053/j.ajkd.2008.05.004 18585836; PubMed Central PMCID: PMC2593146.

20. Levey AS, Stevens LA, Schmid CH, Zhang YL, Castro AF 3rd, Feldman HI, et al. A new equation to estimate glomerular filtration rate. Annals of internal medicine. 2009;150(9):604–12. doi: 10.7326/0003-4819-150-9-200905050-00006 19414839; PubMed Central PMCID: PMC2763564.

21. Inker LA, Schmid CH, Tighiouart H, Eckfeldt JH, Feldman HI, Greene T, et al. Estimating glomerular filtration rate from serum creatinine and cystatin C. The New England journal of medicine. 2012;367(1):20–9. doi: 10.1056/NEJMoa1114248 22762315; PubMed Central PMCID: PMC4398023.

22. Ridker PM, Buring JE, Rifai N, Cook NR. Development and validation of improved algorithms for the assessment of global cardiovascular risk in women: the Reynolds Risk Score. Journal of the American Medical Association. 2007;297(6):611–9. Epub 2007/02/15. doi: 10.1001/jama.297.6.611 17299196.

23. Ridker PM, Paynter NP, Rifai N, Gaziano JM, Cook NR. C-reactive protein and parental history improve global cardiovascular risk prediction: the Reynolds Risk Score for men. Circulation. 2008;118(22):2243–51, 4p following 51. Epub 2008/11/11. doi: 10.1161/CIRCULATIONAHA.108.814251 18997194; PubMed Central PMCID: PMC2752381.

24. Shlipak MG, Sarnak MJ, Katz R, Fried LF, Seliger SL, Newman AB, et al. Cystatin C and the risk of death and cardiovascular events among elderly persons. The New England journal of medicine. 2005;352(20):2049–60. doi: 10.1056/NEJMoa043161 15901858.

25. Shlipak MG, Matsushita K, Arnlov J, Inker LA, Katz R, Polkinghorne KR, et al. Cystatin C versus creatinine in determining risk based on kidney function. The New England journal of medicine. 2013;369(10):932–43. doi: 10.1056/NEJMoa1214234 24004120; PubMed Central PMCID: PMC3993094.

26. Delanaye P, Cavalier E, Saint-Remy A, Lutteri L, Krzesinski JM. Discrepancies between creatinine-based and cystatin C-based equations in estimating prevalence of stage 3 chronic kidney disease in an elderly population. Scand J Clin Lab Invest. 2009;69(3):344–9. doi: 10.1080/00365510802609856 19051098.

27. Peralta CA, Lee A, Odden MC, Lopez L, Zeki Al Hazzouri A, Neuhaus J, et al. Association between chronic kidney disease detected using creatinine and cystatin C and death and cardiovascular events in elderly Mexican Americans: the Sacramento Area Latino Study on Aging. Journal of the American Geriatrics Society. 2013;61(1):90–5. doi: 10.1111/jgs.12040 23252993; PubMed Central PMCID: PMC3545054.

28. Rothenbacher D, Klenk J, Denkinger M, Karakas M, Nikolaus T, Peter R, et al. Prevalence and determinants of chronic kidney disease in community-dwelling elderly by various estimating equations. BMC public health. 2012;12:343. doi: 10.1186/1471-2458-12-343 22574773; PubMed Central PMCID: PMC3490787.

29. Matsushita K, Mahmoodi BK, Woodward M, Emberson JR, Jafar TH, Jee SH, et al. Comparison of risk prediction using the CKD-EPI equation and the MDRD study equation for estimated glomerular filtration rate. Journal of the American Medical Association. 2012;307(18):1941–51. doi: 10.1001/jama.2012.3954 22570462; PubMed Central PMCID: PMC3837430.

30. Shafi T, Matsushita K, Selvin E, Sang Y, Astor BC, Inker LA, et al. Comparing the association of GFR estimated by the CKD-EPI and MDRD study equations and mortality: the third national health and nutrition examination survey (NHANES III). BMC Nephrol. 2012;13:42. doi: 10.1186/1471-2369-13-42 22702805; PubMed Central PMCID: PMC3447668.

31. Foley RN, Wang C, Ishani A, Collins AJ, Murray AM. Kidney function and sarcopenia in the United States general population: NHANES III. Am J Nephrol. 2007;27(3):279–86. doi: 10.1159/000101827 17440263.

32. Fried LF, Lee JS, Shlipak M, Chertow GM, Green C, Ding J, et al. Chronic kidney disease and functional limitation in older people: health, aging and body composition study. Journal of the American Geriatrics Society. 2006;54(5):750–6. doi: 10.1111/j.1532-5415.2006.00727.x 16696739.

33. Shlipak MG, Wassel Fyr CL, Chertow GM, Harris TB, Kritchevsky SB, Tylavsky FA, et al. Cystatin C and mortality risk in the elderly: the health, aging, and body composition study. J Am Soc Nephrol. 2006;17(1):254–61. doi: 10.1681/ASN.2005050545 16267155.

34. Wasen E, Isoaho R, Mattila K, Vahlberg T, Kivela SL, Irjala K. Estimation of glomerular filtration rate in the elderly: a comparison of creatinine-based formulae with serum cystatin C. J Intern Med. 2004;256(1):70–8. doi: 10.1111/j.1365-2796.2004.01340.x 15189368.

35. Bhavsar NA, Appel LJ, Kusek JW, Contreras G, Bakris G, Coresh J, et al. Comparison of measured GFR, serum creatinine, cystatin C, and beta-trace protein to predict ESRD in African Americans with hypertensive CKD. Am J Kidney Dis. 2011;58(6):886–93. Epub 2011/09/29. doi: 10.1053/j.ajkd.2011.07.018 21944667; PubMed Central PMCID: PMC3221777.

36. 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. Journal of the American Medical Association. 2011;305(15):1545–52. Epub 2011/04/13. doi: 10.1001/jama.2011.468 21482744; PubMed Central PMCID: PMC3697771.

37. Stevens LA, Coresh J, Greene T, Levey AS. Assessing kidney function—measured and estimated glomerular filtration rate. The New England journal of medicine. 2006;354(23):2473–83. doi: 10.1056/NEJMra054415 16760447.

38. Cockcroft DW, Gault MH. Prediction of creatinine clearance from serum creatinine. Nephron. 1976;16(1):31–41. doi: 10.1159/000180580 1244564.

39. Levey AS, Bosch JP, Lewis JB, Greene T, Rogers N, Roth D. A more accurate method to estimate glomerular filtration rate from serum creatinine: a new prediction equation. Modification of Diet in Renal Disease Study Group. Annals of internal medicine. 1999;130(6):461–70. doi: 10.7326/0003-4819-130-6-199903160-00002 10075613.

40. Stevens LA, Coresh J, Schmid CH, Feldman HI, Froissart M, Kusek J, et al. Estimating GFR using serum cystatin C alone and in combination with serum creatinine: a pooled analysis of 3,418 individuals with CKD. Am J Kidney Dis. 2008;51(3):395–406. doi: 10.1053/j.ajkd.2007.11.018 18295055; PubMed Central PMCID: PMC2390827.

41. Anderson AH, Yang W, Hsu CY, Joffe MM, Leonard MB, Xie D, et al. Estimating GFR among participants in the Chronic Renal Insufficiency Cohort (CRIC) Study. Am J Kidney Dis. 2012;60(2):250–61. doi: 10.1053/j.ajkd.2012.04.012 22658574; PubMed Central PMCID: PMC3565578.

42. Juraschek SP, Coresh J, Inker LA, Levey AS, Kottgen A, Foster MC, et al. Comparison of serum concentrations of beta-trace protein, beta2-microglobulin, cystatin C, and creatinine in the US population. Clin J Am Soc Nephrol. 2013;8(4):584–92. doi: 10.2215/CJN.08700812 23335043; PubMed Central PMCID: PMC3613960.

43. Foster MC, Levey AS, Inker LA, Shafi T, Fan L, Gudnason V, et al. Non-GFR Determinants of Low-Molecular-Weight Serum Protein Filtration Markers in the Elderly: AGES-Kidney and MESA-Kidney. Am J Kidney Dis. 2017;70(3):406–14. doi: 10.1053/j.ajkd.2017.03.021 28549536; PubMed Central PMCID: PMC5572311.

44. Knight EL, Verhave JC, Spiegelman D, Hillege HL, de Zeeuw D, Curhan GC, et al. Factors influencing serum cystatin C levels other than renal function and the impact on renal function measurement. Kidney Int. 2004;65(4):1416–21. Epub 2004/04/17. doi: 10.1111/j.1523-1755.2004.00517.x 15086483.

45. Estrella MM, Parekh RS, Astor BC, Bolan R, Evans RW, Palella FJ Jr., et al. Chronic kidney disease and estimates of kidney function in HIV infection: a cross-sectional study in the multicenter AIDS cohort study. J Acquir Immune Defic Syndr. 2011;57(5):380–6. Epub 2011/06/08. doi: 10.1097/QAI.0b013e318222f461 21646913; PubMed Central PMCID: PMC3159728.


Článek vyšel v časopise

PLOS One


2020 Číslo 1