Prognostic models with competing risks methods and application to coronary risk prediction

Epidemiology

Volumn 20, Issue 4, 2009, Pages 555-561

  Wolbers, Marcel ^c   Koller, Michael T ^a,b   Witteman, Jacqueline C M ^b   Steyerberg, Ewout W ^b  

^a UNIVERSITY HOSPITAL BASEL   (Switzerland)

^b ERASMUS MEDICAL CENTER   (Netherlands)

^c OXFORD UNIVERSITY CLINICAL RESEARCH UNIT   (Viet Nam)

Author keywords

[No Author keywords available]

Indexed keywords

ADULT; AGED; ARTICLE; CLINICAL DECISION MAKING; CONTROLLED STUDY; CORONARY RISK; FEMALE; FRAIL ELDERLY; HUMAN; ISCHEMIC HEART DISEASE; MAJOR CLINICAL STUDY; PREDICTION; PRIORITY JOURNAL; PROGNOSIS; PROPORTIONAL HAZARDS MODEL;

EID: 67651061641     PISSN: 10443983     EISSN: None     Source Type: Journal    
DOI: 10.1097/EDE.0b013e3181a39056     Document Type: Article

References (40)

1. Jackson R, Lawes CM, Bennett DA, Milne RJ, Rodgers A. Treatment with drugs to lower blood pressure and blood cholesterol based on an individual's absolute cardiovascular risk. Lancet. 2005;365:434-441.
2. Third Report of the National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III) final report. Circulation. 2002;106:3143-3421.
3. De Backer G, Ambrosioni E, Borch-Johnsen K, et al. European guidelines on cardiovascular disease prevention in clinical practice. Third Joint Task Force of European and other Societies on Cardiovascular Disease Prevention in Clinical Practice (constituted by representatives of eight societies and by invited experts). Atherosclerosis. 2004;173:381-391.
4. Chobanian AV, Bakris GL, Black HR, et al. The Seventh Report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure: the JNC 7 report. JAMA. 2003;289:2560-2572.
5. Wilson PW, D'Agostino RB, Levy D, et al. Prediction of coronary heart disease using risk factor categories. Circulation. 1998;97:1837-1847.
6. Assmann G, Cullen P, Schulte H. Simple scoring scheme for calculating the risk of acute coronary events based on the 10-year follow-up of the prospective cardiovascular Munster (PROCAM) study. Circulation. 2002;105:310-315.
7. Conroy RM, Pyorala K, Fitzgerald AP, et al. Estimation of ten-year risk of fatal cardiovascular disease in Europe: the SCORE project. Eur Heart J. 2003;24:987-1003.
8. D'Agostino RB Sr, Vasan RS, Pencina MJ, et al. General cardiovascular risk profile for use in primary care: the Framingham Heart Study. Circulation. 2008;117:743-753.
9. Putter H, Fiocco M, Geskus RB. Tutorial in biostatistics: competing risks and multi-state models. Stat Med. 2007;26:2389-2430.
10. Kalbfleisch JD, Prentice RL. The Statistical Analysis of Failure Time Data. Hoboken, NJ: John Wiley and Sons; 2002.
11. Gooley TA, Leisenring W, Crowley J, Storer BE. Estimation of failure probabilities in the presence of competing risks: new representations of old estimators. Stat Med. 1999;18:695-706.
12. Koller MT, Schaer B, Wolbers M, Sticherling C, Bucher HC, Osswald S. Death without prior appropriate implantable cardioverter-defibrillator therapy: a competing risk study. Circulation. 2008;117:1918-1926.
13. Grunkemeier GL, Jin R, Eijkemans MJ, Takkenberg JJ. Actual and actuarial probabilities of competing risks: apples and lemons. Ann Thorac Surg. 2007;83:1586-1592.
14. Grunkemeier GL, Anderson RP, Miller DC, Starr A. Time-related analysis of nonfatal heart valve complications: cumulative incidence (actual) versus Kaplan-Meier (actuarial). Circulation. 1997;96(suppl 9):II-4.
15. Tsiatis A. A nonidentifiability aspect of the problem of competing risks. Proc Natl Acad Sci USA. 1975;72:20-22.
16. Beyersmann J, Dettenkofer M, Bertz H, Schumacher M. A competing risks analysis of bloodstream infection after stem-cell transplantation using subdistribution hazards and cause-specific hazards. Stat Med.2007;26: 5360-5369.
17. Fine JP, Gray RJ. A proportional hazards model for the subdistribution of a competing risk. J Am Stat Assoc. 1999;94:496-509.
18. Fine JP. Regression modeling of competing crude failure probabilities.Biostatistics. 2001;2:85-97.
19. Scheike TH, Zhang M, Gerds TA. Predicting cumulative incidence probability by direct binomial regression. Biometrika. 2008;95:205-220.
20. Harrell FE. Regression Modeling Strategies With Applications to Linear Models, Logistic Regression, and Survival Analysis. New York: Springer; 2001.
21. Steyerberg EW. Clinical Prediction Models: A Practical Approach to Development Validation and Updating. New York: Springer; 2008.
22. Harrell FE Jr, Lee KL, Mark DB. Multivariable prognostic models: issues in developing models, evaluating assumptions and adequacy, and measuring and reducing errors. Stat Med. 1996;15:361-387.
23. Justice AC, Covinsky KE, Berlin JA. Assessing the generalizability of prognostic information. Ann Intern Med. 1999;130:515-524.
24. Harrell FE Jr, Califf RM, Pryor DB, Lee KL, Rosati RA. Evaluating the yield of medical tests. JAMA. 1982;247:2543-2546.
25. Antolini L, Boracchi P, Biganzoli E. A time-dependent discrimination index for survival data. Stat Med. 2005;24:3927-3944.
26. Royston P, Sauerbrei W. A new measure of prognostic separation in survival data. Stat Med. 2004;23:723-748.
27. 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. JAMA. 2007;297:611-619.
28. Hofman A, Grobbee DE, de Jong PT, van den Ouweland FA. Determinants of disease and disability in the elderly: the Rotterdam Elderly Study. Eur J Epidemiol. 1991;7:403-422.
29. Koller MT, Steyerberg EW, Wolbers M, et al. Validity of the Framing-ham point scores in the elderly: results from the Rotterdam study. Am Heart J. 2007;154:87-93.
30. Clark TG, Altman DG, De Stavola BL. Quantification of the completeness of follow-up. Lancet. 2002;359:1309-1310.
31. Gail MH, Pfeiffer RM. On criteria for evaluating models of absolute risk. Biostatistics. 2005;6:227-239.
32. Latouche A, Boisson V, Chevret S, Porcher R. Misspecified regression model for the subdistribution hazard of a competing risk. Stat Med. 2007;26:965-974.
33. Gonen M, Heller G. Concordance probability and discriminatory power in proportional hazards regression. Biometrika. 2005;92:965-970.
34. Pencina MJ, D'Agostino RBSr, D'Agostino RBJr, Vasan RS. 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.
35. Cook NR. Statistical evaluation of prognostic versus diagnostic models: beyond the ROC curve. Clin Chem. 2008;54:17-23.
36. Schemper M, Stare J. Explained variation in survival analysis. Stat Med. 1996;15:1999-2012.
37. Graf E, Schmoor C, Sauerbrei W, Schumacher M. Assessment and comparison of prognostic classification schemes for survival data. Stat Med. 1999;18:2529-2545.
38. Liu Y, Coresh J, Eustace JA, et al. Association between cholesterol level and mortality in dialysis patients: role of inflammation and malnutrition. JAMA. 2004;291:451-459.
39. R Development Core Team. R: A Language and Environment for Statistical Computing (v 2.5.1). R Foundation for Statistical Computing. Available at: http://www.R-project.org. Accessed November 12, 2008.
40. Gray B. Subdistribution Analysis of Competing Risks. The cmprsk library (v 2.1-7). Available at: http://cran.r-project.org. Accessed November 12, 2008.