Looking to the future: Predicting renal replacement outcomes in a large community cohort with chronic kidney disease

Nephrology Dialysis Transplantation

Volumn 30, Issue 9, 2015, Pages 1507-1517

  Marks, Angharad ^a,b   Fluck, Nicholas ^b   Prescott, Gordon J ^a   Robertson, Lynn ^a   Simpson, William G ^b   Cairns Smith, William ^a   Black, Corri ^a,b  

^a UNIVERSITY OF ABERDEEN   (United Kingdom)

^b NHS GRAMPIAN   (United Kingdom)

Author keywords

Chronic kidney disease; outcome; risk prediction

Indexed keywords

ADOLESCENT; ADULT; AGE DISTRIBUTION; AGED; ARTICLE; CHRONIC KIDNEY DISEASE; COHORT ANALYSIS; FEMALE; HIGH RISK PATIENT; HUMAN; KIDNEY FAILURE; MAJOR CLINICAL STUDY; MALE; MIDDLE AGED; PREDICTION; PRIORITY JOURNAL; PROTEINURIA; RENAL REPLACEMENT THERAPY; RISK ASSESSMENT; SEX DIFFERENCE; THERAPY EFFECT; TREATMENT OUTCOME; URINARY EXCRETION; VERY ELDERLY; YOUNG ADULT; CALIBRATION; DISEASE COURSE; FOLLOW UP; GLOMERULUS FILTRATION RATE; KIDNEY FUNCTION TEST; OUTCOME ASSESSMENT; PROGNOSIS; RENAL INSUFFICIENCY, CHRONIC; RISK FACTOR; SURVIVAL RATE; THEORETICAL MODEL;

ADOLESCENT; ADULT; AGED; AGED, 80 AND OVER; CALIBRATION; COHORT STUDIES; DISEASE PROGRESSION; FEMALE; FOLLOW-UP STUDIES; GLOMERULAR FILTRATION RATE; HUMANS; KIDNEY FUNCTION TESTS; MALE; MIDDLE AGED; MODELS, THEORETICAL; OUTCOME ASSESSMENT (HEALTH CARE); PROGNOSIS; RENAL INSUFFICIENCY, CHRONIC; RENAL REPLACEMENT THERAPY; RISK FACTORS; SURVIVAL RATE; YOUNG ADULT;

EID: 84940650546     PISSN: 09310509     EISSN: 14602385     Source Type: Journal    
DOI: 10.1093/ndt/gfv089     Document Type: Article

References (31)

1. Kerr M, Bray B, Medcalf J et al. Estimating the financial cost of chronic kidney disease to the NHS in England. Nephrol Dial Transplant 2012; 27: iii73-iii80
2. Coresh J, Selvin E, Stevens L et al. Prevalence of chronic kidney disease in the United States. JAMA 2007; 298: 2038-2047
3. Cukor D, Kimmel PL. Education and end of life in chronic kidney disease: disparities in black and white. Clin J Am Soc Nephrol 2010; 5: 163-166
4. Eckardt KU, Coresh J, Devuyst O et al. Evolving importance of kidney disease: from subspecialty to global health burden. Lancet 2013; 382: 158-169
5. Chronic Kidney Disease Prognosis Consortium (CKD-PC). Matsushita K, van der Velde M, Astor BC 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
6. McCullough PA, Li S, Jurkovitz CTet al. Chronic kidney disease, prevalence of premature cardiovascular disease, and relationship to short-term mortality. Am Heart J 2008; 156: 277-283
7. Hingorani AD, Windt DA, Riley RD et al. Prognosis research strategy (PROGRESS) 4: stratified medicine research. BMJ 2013; 346: e5793
8. Tangri N, Kitsios GD, Inker LA et al. Risk prediction models for patients with chronic kidney disease: a systematic review. Ann Intern Med 2013; 158: 596-603
9. Echouffo-Tcheugui JB, Kengne AP. Risk models to predict chronic kidney disease and its progression: a systematic review. PLoS Med 2012; 9: e1001344
10. Tripepi G, Heinze G, Jager KJ et al. Risk prediction models. Nephrol Dial Transplant 2013; 28: 1975-1980
11. Hallan SI, Ritz E, Lydersen S et al. Combining GFR and albuminuria to classify CKD improves prediction of ESRD. J. Am. Soc. Nephrol. 2009; 20: 1069-1077
12. Johnson ES, Thorp ML, Platt RW et al. Predicting the risk of dialysis and transplant among patients with CKD: a retrospective cohort study. Am J Kidney Dis 2008; 52: 653-660
13. Acedillo RR, Tangri N, Garg AX. The kidney failure risk equation: on the road to being clinically useful? Nephrol Dial Transplant 2013; 28: 1623-1624
14. Peeters MJ, van Zuilen AD, van den Brand JA et al. Validation of the kidney failure risk equation in European CKD patients. Nephrol Dial Transplant 2013; 28: 1773-1779
15. Tangri N, Stevens LA, Griffith J et al. A predictive model for progression of chronic kidney disease to kidney failure. JAMA 2011; 305: 1553-1559
16. Marks A, Black C, Fluck N et al. Translating chronic kidney disease epidemiology into patient care: the individual/public health risk paradox. Nephrol Dial Transplant 2012; 27 (Suppl 3): iii65-iii72
17. Marks A, Macleod C, McAteer A et al. Chronic kidney disease, a useful trigger for proactive primary care? Mortality results from a large UK cohort. Fam Pract 2013; 30: 282-289
18. Marks A, Fluck N, Prescott GJ et al. Definitions of progression in chronic kidney disease: predictors and relationship to renal replacement therapy in a population cohort with 6 years follow-up. Nephrol Dial Transplant 2014; 29: 333
19. Bang H, Vupputuri S, Shoham DA et al. Screening for occult renal disease (SCORED): a simple prediction model for chronic kidney disease. Arch. Intern. Med. 2007; 167: 374-381
20. Bash LD, Coresh J, Kottgen A et al. Defining incident chronic kidney disease in the research setting: the ARIC study. Am J Epidemiol 2009; 170: 414-424
21. Soo M, Robertson LM, Ali T et al. Approaches to ascertaining comorbidity information: validation of routine hospital episode data with clinicianbased case note review. BMC Res Notes 2014; 7: 253
22. Cleves M, Gould W, Gutierrez RG et al. An Introduction to Survival Analysis Using Stata. College Station, TX: Stata Press, 2010
23. Steyerberg EW. Chapter 15-evaluation of performance. In: Gail M, Tsiatis A, Krickeberg K, Wong W, Sarnet J (eds). Clinical Prediction Models: A Practical Approach to Development, Validation, and Updating. New York, NY: Springer, 2009, pp. 255-280
24. Pencina MJ, D'Agostino RB S, D'Agostino RB, Jr et al. Evaluating the added predictive ability of a new marker: from area under the ROC curve to reclassification and beyond. Stat Med 2008; 27: 157-172. Discussion 207-12
25. Kerr KF, Wang Z, Janes H et al. Net reclassification indices for evaluating risk prediction instruments: a critical review. Epidemiology 2014; 25: 114-121
26. Pencina MJ, D'Agostino RB S, Steyerberg EW. Extensions of net reclassification improvement calculations to measure usefulness of new biomarkers. Stat Med 2011; 30: 11-21
27. McCullough K, Sharma P, Ali T et al. Measuring the population burden of chronic kidney disease: a systematic literature review of the estimated prevalence of impaired kidney function. Nephrol Dial Transplant 2012; 27: 1812
28. Landray MJ, Emberson JR, Blackwell L et al. Prediction of ESRD and death among people with CKD: the chronic renal impairment in Birmingham (CRIB) prospective cohort study. Am J Kidney Dis 2010; 56: 1082-1094
29. Desai AS, Toto R, Jarolim P et al. Association between cardiac biomarkers and the development of ESRD in patients with type 2 diabetes mellitus, anemia, and CKD. Am J Kidney Dis 2011; 58: 717-728
30. Steyerberg EW, Moons KG, van der Windt DA et al. Prognosis research strategy (PROGRESS) 3: prognostic model research. PLoS Med 2013; 10: e1001381
31. Kidney Disease: Improving Global Outcomes (KDIGO) CKDWork Group. KDIGO 2012 clinical practice guideline for the evaluation and management of chronic kidney disease. Kidney Int Suppl 2013; 3: 1-150