Development and validation of a model to predict 5-year risk of death without ESRD among older adults with CKD

Clinical Journal of the American Society of Nephrology

Volumn 10, Issue 3, 2015, Pages 363-371

  Bansal, Nisha ^a   Katz, Ronit ^a   De Boer, Ian H ^a   Peralta, Carmen A ^b   Fried, Linda F ^c   Siscovick, David S ^d   Rifkin, Dena E ^e   Hirsch, Calvin ^f   Cummings, Steven R ^g   Harris, Tamara B ^h   Kritchevsky, Stephen B ^h   Sarnak, Mark J ⁱ   Shlipak, Michael G ^b   Ix, Joachim H ^e  

^a UNIVERSITY OF WASHINGTON SCHOOL OF MEDICINE   (United States)

^b UNIVERSITY OF CALIFORNIA   (United States)

^c UNIVERSITY OF PITTSBURGH SCHOOL OF MEDICINE   (United States)

^d NEW YORK ACADEMY OF MEDICINE   (United States)

^e UNIVERSITY OF CALIFORNIA   (United States)

^f UNIVERSITY OF CALIFORNIA   (United States)

^g CALIFORNIA PACIFIC MEDICAL CENTER   (United States)

^h WAKE FOREST SCHOOL OF MEDICINE   (United States)

ⁱ TUFTS MEDICAL CENTER   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ALBUMIN; CHOLESTEROL; CREATININE;

AGE; AGED; ARTICLE; CEREBROVASCULAR ACCIDENT; CHRONIC KIDNEY DISEASE; CLINICAL DECISION MAKING; CLINICAL EVALUATION; COHORT ANALYSIS; CONTROLLED STUDY; DEATH; DIABETES MELLITUS; DRUG USE; END STAGE RENAL DISEASE; FEMALE; FOLLOW UP; GENDER; GLOMERULUS FILTRATION RATE; HEART FAILURE; HUMAN; INCIDENCE; ISCHEMIC HEART DISEASE; LONGITUDINAL STUDY; MAJOR CLINICAL STUDY; MALE; MORTALITY; OUTCOME ASSESSMENT; PHYSICAL ACTIVITY; PHYSICAL EXAMINATION; PREDICTION; PROSPECTIVE STUDY; RACE; SELF REPORT; SENSITIVITY ANALYSIS; TOBACCO USE; VALIDATION PROCESS; ALBUMINURIA; ANCESTRY GROUP; CHRONIC KIDNEY FAILURE; PROPORTIONAL HAZARDS MODEL; REGRESSION ANALYSIS; RISK FACTOR; SEX DIFFERENCE; SMOKING; STROKE; URINE; VALIDATION STUDY; VERY ELDERLY;

AGE FACTORS; AGED; AGED, 80 AND OVER; ALBUMINURIA; CONTINENTAL POPULATION GROUPS; CREATININE; DIABETES MELLITUS; FEMALE; GLOMERULAR FILTRATION RATE; HEART FAILURE; HUMANS; MALE; PROPORTIONAL HAZARDS MODELS; REGRESSION ANALYSIS; RENAL INSUFFICIENCY, CHRONIC; RISK FACTORS; SEX FACTORS; SMOKING; STROKE;

EID: 84924356846     PISSN: 15559041     EISSN: 1555905X     Source Type: Journal    
DOI: 10.2215/CJN.04650514     Document Type: Article

References (27)

1. Keith DS, Nichols GA, Gullion CM, Brown JB, Smith DH: Longitudinal follow-up and outcomes among a population with chronic kidney disease in a large managed care organization. Arch Intern Med 164: 659–663, 2004.
2. 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 351: 1296–1305, 2004.
3. O’Hare AM, Choi AI, Bertenthal D, Bacchetti P, Garg AX, Kaufman JS, Walter LC, Mehta KM, Steinman MA, Allon M, McClellan WM, Landefeld CS: Age affects outcomes in chronic kidney disease. J Am Soc Nephrol 18: 2758–2765, 2007.
4. Hallan SI, Matsushita K, Sang Y, Mahmoodi BK, Black C, Ishani A, Kleefstra N, Naimark D, Roderick P, Tonelli M, Wetzels JF, Astor BC, Gansevoort RT, Levin A, Wen CP, Coresh J; Chronic Kidney Disease Prognosis Consortium: Age and association of kidney measures with mortality and end-stage renal disease. JAMA 308: 2349–2360, 2012.
5. Fried LP, Borhani NO, Enright P, Furberg CD, Gardin JM, Kronmal RA, Kuller LH, Manolio TA, Mittelmark MB, Newman A: The Cardiovascular Health Study: Design and rationale. Ann Epidemiol 1: 263–276, 1991.
6. Levey AS, Stevens LA, Schmid CH, Zhang YL, Castro AF 3rd, Feldman HI, Kusek JW, Eggers P, Van Lente F, Greene T, Coresh J; CKD-EPI (Chronic Kidney Disease Epidemiology Collaboration): A new equation to estimate glomerular filtration rate. Ann Intern Med 150: 604–612, 2009.
7. Dalrymple LS, Katz R, Kestenbaum B, Shlipak MG, Sarnak MJ, Stehman-Breen C, Seliger S, Siscovick D, Newman AB, Fried L: Chronic kidney disease and the risk of end-stage renal disease versus death. J Gen Intern Med 26: 379–385, 2011.
8. Shlipak MG, Fried LF, Cushman M, Manolio TA, Peterson D, Stehman-Breen C, Bleyer A, Newman A, Siscovick D, Psaty B: Cardiovascular mortality risk in chronic kidney disease: Comparison of traditional and novel risk factors. JAMA 293: 1737–1745, 2005.
9. Butler J, Rodondi N, Zhu Y, Figaro K, Fazio S, Vaughan DE, Satterfield S, Newman AB, Goodpaster B, Bauer DC, Holvoet P, Harris TB, de Rekeneire N, Rubin S, Ding J, Kritchevsky SB; Health ABC Study: Metabolic syndrome and the risk of cardiovascular disease in older adults. J AmColl Cardiol 47: 1595–1602, 2006.
10. Rifkin DE, Shlipak MG, Katz R, Fried LF, Siscovick D, Chonchol M, Newman AB, Sarnak MJ: Rapid kidney function decline and mortality risk in older adults. Arch Intern Med 168: 2212–2218, 2008.
11. Ives DG, Fitzpatrick AL, Bild DE, Psaty BM, Kuller LH, Crowley PM, Cruise RG, Theroux S: Surveillance and ascertainment of cardiovascular events. The Cardiovascular Health Study. Ann Epidemiol 5: 278–285, 1995.
12. Kritchevsky SB, Tooze JA, Neiberg RH, Schwartz GG, Hausman DB, Johnson MA, Bauer DC, Cauley JA, Shea MK, Cawthon PM, Harris TB, Rubin SM, Tylavsky FA, Houston DK; Health ABC Study: 25-Hydroxyvitamin D, parathyroid hormone, and mortality in black and white older adults: The health ABC study. J Clin Endocrinol Metab 97: 4156–4165, 2012.
13. Peduzzi P, Concato J, Kemper E, Holford TR, Feinstein AR: A simulation study of the number of events per variable in logistic regression analysis. J Clin Epidemiol 49: 1373–1379, 1996.
14. Efron BTT: An Introduction to the Bootstrap, London, Chapman and Hall, 1993.
15. D’Agostino RB Sr., Grundy S, Sullivan LM, Wilson P; CHD Risk Prediction Group: Validation of the Framingham coronary heart disease prediction scores: Results of a multiple ethnic groups investigation. JAMA 286: 180–187, 2001.
16. Hosmer DW, Hosmer T, Le Cessie S, Lemeshow S: A comparison of goodness-of-fit tests for the logistic regression model. Stat Med 16: 965–980, 1997.
17. Harrell F: Regression Modeling Strategies: With Applications to Linear Models, Logistic Regression, and Survival Analysis, Springer, New York, 2001.
18. Sullivan LM, Massaro JM, D’Agostino RB Sr.: Presentation of multivariate data for clinical use: The Framingham Study risk score functions. Stat Med 23: 1631–1660, 2004.
19. Shlipak MG, Katz R, Kestenbaum B, Siscovick D, Fried L, Newman A, Rifkin D, Sarnak MJ: Rapid decline of kidney function increases cardiovascular risk in the elderly. J AmSoc Nephrol 20: 2625–2630, 2009.
20. Fried LP, Kronmal RA, Newman AB, Bild DE, Mittelmark MB, Polak JF, Robbins JA, Gardin JM: Risk factors for 5-year mortality in older adults: The Cardiovascular Health Study. JAMA 279: 585–592, 1998.
21. Tangri N, Kitsios GD, Inker LA, Griffith J, Naimark DM, Walker S, Rigatto C, Uhlig K, Kent DM, Levey AS: Risk prediction models for patients with chronic kidney disease: A systematic review. Ann Intern Med 158: 596–603, 2013.
22. Berthoux F, Mohey H, Laurent B, Mariat C, Afiani A, Thibaudin L: Predicting the risk for dialysis or death in IgA nephropathy. J Am Soc Nephrol 22: 752–761, 2011.
23. Keane WF, Zhang Z, Lyle PA, Cooper ME, de Zeeuw D, Grunfeld JP, Lash JP, McGill JB, Mitch WE, Remuzzi G, Shahinfar S, Snapinn SM, Toto R, Brenner BM; RENAAL Study Investigators: Risk scores for predicting outcomes in patients with type 2 diabetes and nephropathy: The RENAAL study. Clin J Am Soc Nephrol 1: 761–767, 2006.
24. Desai AS, Toto R, Jarolim P, Uno H, Eckardt KU, Kewalramani R, Levey AS, Lewis EF, McMurray JJ, Parving HH, Solomon SD, Pfeffer MA: Association between cardiac biomarkers and the development of ESRD in patients with type 2 diabetes mellitus, anemia, and CKD. Am J Kidney Dis 58: 717–728, 2011.
25. Johnson ES, Thorp ML, Yang X, Charansonney OL, Smith DH: Predicting renal replacement therapy andmortality in CKD. Am J Kidney Dis 50: 559–565, 2007.
26. Landray MJ, Emberson JR, Blackwell L, Dasgupta T, Zakeri R, Morgan MD, Ferro CJ, Vickery S, Ayrton P, Nair D, Dalton RN, Lamb EJ, Baigent C, Townend JN, Wheeler DC: Prediction of ESRD and death among people with CKD: The Chronic Renal Impairment in Birmingham(CRIB) prospective cohort study.AmJ Kidney Dis 56: 1082–1094, 2010.
27. Collins GS, Omar O, Shanyinde M, Yu LM: A systematic review finds prediction models for chronic kidney disease were poorly reported and often developed using inappropriate methods. J Clin Epidemiol 66: 268–277, 2013.