Analysis of a composite endpoint with longitudinal and time-to-event data

Statistics in Medicine

Volumn 30, Issue 9, 2011, Pages 1018-1027

  Tseng, Chi hong ^a   Wong, Weng Kee ^a  

^a UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

Joint modeling; Level crossing; Multiple outcomes; Scleroderma

Indexed keywords

ALGORITHM; ARTICLE; HUMAN; INTERMETHOD COMPARISON; JOINT OUTCOME NONPARAMETRIC ANALYSIS; LEVEL CROSSING APPROACH; LONGITUDINAL STUDY; MATHEMATICAL ANALYSIS; MATHEMATICAL MODEL; NONPARAMETRIC TEST; POWER ANALYSIS; SAMPLE SIZE; SCLERODERMA; SIMULATION; STATISTICAL ANALYSIS;

COMPUTER SIMULATION; DATA INTERPRETATION, STATISTICAL; HUMANS; LONGITUDINAL STUDIES; PENICILLAMINE; QUESTIONNAIRES; RANDOMIZED CONTROLLED TRIALS AS TOPIC; SCLERODERMA, DIFFUSE; SURVIVAL ANALYSIS; TREATMENT OUTCOME;

EID: 79953750430     PISSN: 02776715     EISSN: 10970258     Source Type: Journal    
DOI: 10.1002/sim.4199     Document Type: Article

References (26)

1. Freemantle M, Calvert J, Wood J, Eastaugh J, Griffin C. A composite outcomes in randomized trials: greater precision but with greater uncertainty? Journal of the American Medical Association 2003; 289:2554-2559.
2. van Leth F, Lange JMA. Use of composite end points to measure clinical events. Journal of the American Medical Association 2003; 290:1456-1457.
3. International Conference on Harmonization, Guideline E9. Statistical Principles for Clinical Trials. (accessed 16 December 2005).
4. Committee For Proprietary Medicinal Products (CPMP). Points to Consider on Multiplicity Issues in Clinical Trials. Available from: (accessed 16 December 2005).
5. Elashoff RM, Li G, Li N. An approach to joint analysis of longitudinal measurements and competing risks failure time data. Statistics in Medicine 2007; 26:2813-2835.
6. Wu M, Carroll R. Estimation and comparison of change in the presence of informative right censoring by modeling the censoring process. Biometrics 1988; 44:175-188.
7. Robins J, Rotnitzky A, Zhao L. Analysis of semiparametric regression-models for repeated outcomes in the presence of missing data. Journal of the American Statistical Association 1995; 90:106-121.
8. Wu L. Exact and approximate inferences for nonlinear mixed-effects models with missing covariates. Journal of the American Statistical Association 2004; 99:700-709.
9. Liu M, Ying Z. Joint analysis of longitudinal data with informative right censoring. Biometrics 2007; 63:363-371.
10. OBrien P. Procedures for comparing samples with multiple endpoints. Biometrics 1984; 40:1079-1087.
11. Henderson R, Diggle P, Dobson A. Joint modeling of longitudinal measurements and event time data. Biostatistics 2000; 1:465-480.
12. Verbeke G, Lesaffre E. The effect of misspecifying the random-effects distribution in linear mixed models for longitudinal data. Computational Statistics and Data Analysis 1997; 23:541-556.
13. Heagerty P, Kurland B. Misspecified maximum likelihood estimates and generalised linear mixed models. Biometrika 2001; 88:973-985.
14. Moye L, Davis B, Hawkins C. Analysis of a clinical trial involving a combined mortality and adherence dependent interval censored endpoint. Statistics in Medicine 1992; 11:1705-1717.
15. Hoeffding W. A class of statistics with asymptotically normal distribution. Annals of Mathematical Statistics 1948; 19:239-325.
16. Finkelstein D, Schoenfeld D. Combining mortality and longitudinal measures in clinical trials. Statistics in Medicine 1999; 18:1341-1354.
17. Gehan E. A generalized Wilcoxon test for comparing arbitrarily singly censored samples. Biometrika 1965; 52:203-223.
18. Reilly C. A nonparametric approach to the analysis of longitudinal data via a set of level crossing problems with application to the analysis of micro-array time course experiments. Biostatistics 2005; 6:271-278.
19. Bjorling L, Hodges J. Rule-based ranking schemes for antiretroviral trial. Statistics in Medicine 1997; 16:1175-1191.
20. Clements PJ, Furst DE, Wong WK, Mayes M, White B, Wigley F, Weisman MH, Barr W, Moreland L, Medsger T, Steen VJ, Martin R, Collier D, Weinstein A, Lally E, Varga J, Weiner S, Andrews B, Abeles M, Seibold JR. High-dose versus low-dose d-penicillamine in early diffuse systemic sclerosis. Arthritis and Rheumatism 1999; 42:1194-1203.
21. Clements PJ, Wong WK, Hurwitz EL, Furst DE, Mayes M, White B, Wigley F, Weisman MH, Barr W, Moreland L, Medsger TA, Steen V, Martin RW, Collier D, Weinstein A, Lally E, Varga J, Weiner S, Andrews B, Abeles M, Seibold JR. Correlates of the disability index of the health assessment questionnaire: a measure of functional impairment in systemic sclerosis (ssc). Arthritis and Rheumatism 1999; 42:2372-2380.
22. Marco P, Weisman M, Seibold J, Furst D, Wong W, Hurwitz E, Mayes M, White B, Wigley F, Barr W, Moreland L, Medsger TJ, Steen V, Martin R, Collier D, Weinstein A, Lally E, Varga J, Weiner S, Andrews B, Abeles M, Clements P. Predictors and outcomes of scleroderma renal crisis: the high-dose versus low-dose d-penicillamine in early diffuse systemic sclerosis trial. Arthritis and Rheumatism 2002; 46:2983-2989.
23. Postlethwaite AE, Wong WK, Clements P, Chatterjee S, Fessler BJ, Kang AH, Korn J, Mayes M, Merkel PA, Molitor J, Moreland L, Rothfield A, Simm RW, Smith EA, Spiera R, Steen V, Warrington K, White B, Wigley F, Furst DE. Oral collagen i in diffuse systemic sclerosis: I. Oral ci does not improve skin in all patients but may improve skin in late disease. Arthritis and Rheumatism 2008; 58:1810-1822.
24. Wong WK, Boscardin JW, Furst DE, Postlethwatie AE. Handling missing data in clinical trials for rheumatic diseases. 2008; Under Review.
25. Wong WK, Furst DE, Clements PJ, Streisand J. Assessing disease progression using a composite endpoint. Statistical Methods in Medical Research 2006; 16:13-50.
26. Fransen J, Kavanaugh A, Borm GF. Desirability scores for assessing multiple outcomes in systemic rheumatic diseases. Communications in Statistics-Theory and Methods 2009; 38:3461-3471.