Misspecification of Cox regression models with composite endpoints

Statistics in Medicine

Volumn 31, Issue 28, 2012, Pages 3545-3562

  Wu, Longyang ^a   Cook, Richard J ^a  

^a UNIVERSITY OF WATERLOO   (Canada)

Author keywords

Composite endpoint; Copula; Cox regression; Model misspecification; Randomized clinical trial

Indexed keywords

ARTICLE; ASTHMA; CLINICAL EFFECTIVENESS; HAZARD RATIO; HUMAN; INTERMETHOD COMPARISON; MATHEMATICAL ANALYSIS; MATHEMATICAL COMPUTING; NORMAL DISTRIBUTION; PARAMETRIC TEST; PROBABILITY; PROCESS MODEL; PROPORTIONAL HAZARDS MODEL; SAMPLE SIZE; SENSITIVITY ANALYSIS; SYSTEMATIC ERROR; UNCERTAINTY;

ASTHMA; BIAS (EPIDEMIOLOGY); COMPUTER SIMULATION; DISEASE PROGRESSION; ENDPOINT DETERMINATION; HUMANS; MULTICENTER STUDIES AS TOPIC; MULTIVARIATE ANALYSIS; OUTCOME ASSESSMENT (HEALTH CARE); PROPORTIONAL HAZARDS MODELS; RANDOMIZED CONTROLLED TRIALS AS TOPIC; RESEARCH DESIGN;

EID: 84870248759     PISSN: 02776715     EISSN: 10970258     Source Type: Journal    
DOI: 10.1002/sim.5436     Document Type: Article

References (37)

1. POISE Study Group. Effects of extended-release metoprolol succinate in patients undergoing non-cardiac surgery (POISE trial): a randomised controlled trial. Lancet 2008; 371:1839-1847.
2. Barnett HJM, Taylor DW, Eliasziw M, Fox AJ, Ferguson GG, Haynes RB, Rankin RN, Clagett GP, Hachinski VC, Sackett DL, Thorpe KE, Meldrum HE for the North American Symptomatic Carotid Endarterectomy Trial Collaborators. Benefit of carotid arterectomy in patients with symptomatic moderate or severe stenosis. The New England Journal of Medicine 1998; 339(14):1415-1425.
3. Carlson RH. Prostate cancer: composite endpoint trips up satraplatin trial. Oncology Times 2007; 24:44-47.
4. Hortobagyi GN, Theriault RL, Porter L, Blayney D, Lipton A, Sinoff C, Wheeler H, Simeone JF, Seaman J, Knight RD, Heffernan M, Reitsma DJ, Kennedy I, Allan SG, Mellars K for the Protocol 19 Aredia Breast Cancer Study Group. Efficacy of pamidronate in reducing skeletal complications in patients with breast cancer and lytic bone metastases. The New England Journal of Medicine 1996; 335(24):1785-1792.
5. Benjamini Y, Hochberg Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. Journal of the Royal Statistical Society, Series B (Methodological) 1995; 57(1):125-133.
6. Sankoh AJ, D'Agostino Sr RB, Huque MF. Efficacy endpoint selection and multiplicity adjustment methods in clinical trials with inherent multiple endpoint issues. Statistics in Medicine 2003; 22(20):3133-3150.
7. Proschan MA, Waclawiw MA. Practical guidelines for multiplicity adjustment in clinical trials. Controlled Clinical Trials 2000; 21(6):527-539.
8. Ferreira-González I, Permanyer-Miralda G, Busse JW, Bryant DM, Montori VM, Alonso-Coello P, Walter SD, Guyatt GH. Composite endpoints in clinical trials: the trees and the forest. Journal of Clinical Epidemiology 2007; 60(7):660-661.
9. Cannon CP. Clinical perspectives on the use of composite endpoints. Controlled clinical trials 1997; 18:517-529.
10. Freemantle N, Calvert M, Wood J, Eastaugh J, Griffin C. Composite outcomes in randomized trials: greater precision but with greater uncertainty? Journal of the American Medical Association 2003; 289(19):2554-2559.
11. Montori VM, Permanyer-Miralda G, Ferreira-González I, Busse JW, Pacheco-Huergo V, Bryant D, Alons J, Akl EA, Domingo-Salvany A, Mills E, Wu P, Schünemann HJ, Jaeschke R, Guyatt GH. Validity of composite end points in clinical trials. British Medical Journal 2005; 330(7491):594-596.
12. Chi GYH. Some issues with composite endpoints in clinical trials. Fundamental & Clinical Pharmacology 2005; 19:609-619.
13. Ferreira-González I, Permanyer-Miralda G, Busse JW, Bryant DM, Montori VM, Alonso-Coello P, Walter SD, Guyatt GH. Methodologic discussions for using and interpreting composite endpoints are limited, but still identify major concerns. Journal of Clinical Epidemiology 2007; 60(7):651-657.
14. Soria JC, Massard C, Le Chevalier T. Should progression-free survival be the primary measure of efficacy for advanced NSCLC therapy? Annals of Oncology 2010; 21(12):2324-2332.
15. DeMets DL, Califf RM. Lessons learned from recent cardiovascular clinical trials: part I. Circulation 2002; 106:746-751.
16. Neaton JD, Gray G, Zuckerman BD, Konstam M. Key issues in end point selection for heart failure trials: composite end points. Journal of Cardiac Failure 2005; 11(8):567-575.
17. Lim E, Brown A, Helmy A, Mussa S, Altman DG. Composite outcomes in cardiovascular research: a survey of randomized trials. Annals of Internal Medicine 2008; 149:612-617.
18. Ferreira-González I, Busse JW, Heels-Ansdell D, Montori VM, Akl EA, Bryant DM, Alonso-Coello P, Alonso J, Worster A, Upadhye S, Jaeschke R, Schünemann HJ, Permanyer-Miralda G, Pacheco-Huergo V, Domingo-Salvany A, Wu P, Mills EJ, Guyatt GH. Problems with use of composite end points in cardiovascular trials: systematic review of randomised controlled trials. British Medical Journal 2007; 334(7597):786-792.
19. Bethel MA, Holman R, Haffner SM, Califf RM, Huntsman-Labed A, Hua TA, McMurray J. Determining the most appropriate components for a composite clinical trial outcome. American Heart Journal 2008; 156(4):633-640.
20. Wei LJ, Lin DY, Weissfeld L. Regression analysis of multivariate incomplete failure time data by modeling marginal distributions. Journal of American Statistical Association 1989; 84:1065-1073.
21. Genest C, MacKay J. The joy of copulas: bivariate distributions with uniform marginals. The American Statistician 1986; 40(4):280-283.
22. Nelsen RB. An Introduction to Copulas. Springer: New York, 2006.
23. Joe H. Multivariate Models and Dependence Concepts. Chapman and Hall: London, 1997.
24. Clayton DG.A model for association in bivariate life tables and its application in epidemiological studies of familial tendency in chronic disease incidence. Biometrika 1978; 65:141-151.
25. Genest C. Frank's family of bivariate distributions. Biometrika 1987; 74:549-550.
26. Gumbel E. Distributions des valeurs extrèmes en plusieurs dimensions. Publications de l'Institut de statistique de l'Univerisitè de Paris 1960; 9:171-173.
27. Cox DR. Regression models with lifetables (with discussion). Journal of the Royal Statistical Society, Series B 1972; 34:187-220.
28. Cox DR. Partial likelihood. Biometrika 1975; 62:269-276.
29. Cox DR. Tests of separate family of hypotheses. Proceedings of the Berkeley Symposium on Mathematical Statistics and Probability 1961; 105-123.
30. White H. Maximum likelihood estimation of misspecified models. Econometrica 1982; 30:1-25.
31. Struthers CA, Kalbfleisch JD. Misspecified proportional hazard models. Biometrika 1986; 73:363-369.
32. Therneau TM, Grambsch PM. Modeling Survival Data: Extending the Cox Model. Springer: New York, 2000.
33. Jayaram L, Pizzichini MM, Cook RJ, Boulet L-P, Lemiére C, Pizzichini E, Cartier A, Hussack P, Goldsmith CH, Laviolette M, Parameswaran K, Hargreave FE. Determining asthma treatment by monitoring sputum cell counts: effect on exacerbations. European Journal of Respirology 2006; 27:483-494.
34. Sheehe PR. Composite end points in clinical trials. Journal of the American Medical Association 2010; 303:1698.
35. Andersen PK, Gill RD. Cox regression model for counting processes: a large sample study. The Annals of Statistics 1982; 10:1100-1120.
36. Fleming TR, Harrington DP. Counting Processes and Survival Analysis. John Wiley and Sons: New York, 1991.
37. Prentice RL, Cai J. Covariance and survivor function estimation using censored multivariate failure time data. Biometrika 1992; 79(3):495-512.