Antibiotics, Antineoplastic/therapeutic use; Clinical Trials, Phase III as Topic/methods; Data Interpretation, Statistical; Humans; *Longitudinal Studies; Male; Mitomycin/therapeutic use; *Models, Biological; *Models, Statistical; Orchiectomy; *Patient Dropouts; Prostatic Neoplasms/drug therapy/surgery; *Quality of Life
Abstract :
[en] Analysing quality of life data (QOL) may be complicated for several reasons. Quality of life data not only involves repeated measures but is also usually collected on ordered categorical responses. In addition, it is evident that not all patients provide the same number of assessments, due to attrition caused by death or other medical reasons. In the recent statistical literature, increasing attention is given to methods which can handle non-continuous outcomes in the presence of missing data. The aim of this paper is to investigate the effect on statistical conclusions of applying different modelling techniques to QOL data generated from an EORTC phase III trial. Treatment effects and treatment differences are of major concern. First, a random-effects model is fitted, relating a binary longitudinal response (derived from the physical functioning scale of the QLQ-C30) to several covariates. In a second approach, marginal models are fitted, retaining the response variable and the mean structure used before. The fitted marginal models only differ with respect to the considered estimation procedure: generalized estimating equations (GEE); weighted generalized estimating equations (WGEE), and maximum likelihood (ML).
Disciplines :
General & internal medicine
Author, co-author :
Van Steen, Kristel ; Université de Liège - ULiège > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Bioinformatique
Curran, D.
Molenberghs, G.
Language :
English
Title :
Sensitivity analysis of longitudinal binary quality of life data with drop-out: an example using the EORTC QLQ-C30
Publication date :
2001
Journal title :
Statistics in Medicine
ISSN :
0277-6715
eISSN :
1097-0258
Publisher :
John Wiley & Sons, Hoboken, United States - New Jersey
Aaronson, N.K., Ahmedzai, S., Bergman, B., Bullinger, M., Cull, A., Duez, N.J., Filiberti, A., Takeda, F., The European Organization for Research and Treatment of Cancer QLQ-C30: A quality-of-life instrument for use in international clinical trials in oncology (1993) Journal of the National Cancer Institute, 85, pp. 365-376
McCullagh, P., Nelder, J.A., (1989) Generalized Linear Models, , Chapman and Hall: London
Little, R.J.A., Modelling the drop-out mechanism in repeated-measures studies (1995) Journal of the American Statistical Society, 90, p. 431
Hogan, J.W., Laird, N.M., Mixture models for the joint distribution of repeated measures and event times (1997) Statistics in Medicine, 16 (1-3), pp. 239-257
Curran, D., Pignatti, F., Molengberghs, G., Milk protein trial: Missing data or stratified analysis (1999) JABES, , (submitted)
Molenberghs, G., Lesaffre, E., Marginal modelling of correlated ordinal data using a multivariate Plackett distribution (1994) Journal of the American Statistical Association, 89, pp. 633-644
Curran, D., Bacchi, M., Schmitz, F.H., Molenberghs, G., Sylvester, R.J., Identifying the types of missingness in quality of life data from clinical trials (1998) Statistics in Medicine, 17, pp. 739-756
Rubin, D.B., Inference and missing data (1976) Biometrika, 63, pp. 581-592
Liang, K.-Y., Zeger, S.L., Longitudinal data analysis using generalized linear models (1986) Biometrika, 73, pp. 13-22
Zeger, S.L., Liang, K.-Y., Longitudinal data analysis for discrete and continuous outcomes (1986) Biometrics, 42, pp. 121-130
Zeger, S.L., Liang, K.-Y., Albert, P.S., Models for longitudinal data: A generalized estimating equation approach (1988) Biometrics, 44, pp. 1049-1060
Zhao, L.P., Prentice, R.L., Correlated binary regression using a quadratic exponential model (1990) Biometrika, 77, pp. 642-648
Liang, K.Y., Zeger, S.L., Qadish, B., Multivariate regression analyses for categorical data (1992) Journal of the Royal Statistical Society, Series B, 54, pp. 3-40. , (with discussion)
Lipsitz, S.R., Kim, K., Zhao, L., Analysis of repeated categorical data using generalized estimating equations (1994) Statistics in Medicine, 13, pp. 1149-1163
Robins, J.M., Rotnitzky, A., Zhao, L.P., Analysis of semiparametric regression models for repeated outcomes in the presence of missing data (1995) Journal of the American Statistical Association, 90, pp. 106-121
Troxel, A.B., Lipstiz, S.R., Troyen, A.B., Weighted estimating equations with nonignorably missing response data (1997) Biometrics, 53, pp. 857-869
Wu, M.C., Caroll, R.J., Estimation and comparison of changes in the presence of informative right censoring by modelling the censoring mechanism (1988) Biometrics, 44, pp. 175-188
Wu, M.C., Bailey, K.R., Estimation and comparison of changes in the presence of informative right censoring: Conditional linear model (1989) Biometrics, 45, pp. 939-955
Wu, M.C., Hunsberger, S., Zucker, D., Testing for differences in changes in the presence of censoring: Parametric and non-parametric methods (1994) Statistics in Medicine, 13, pp. 635-646
Wei, L.J., Lachin, J.M., Two sample asymptotically distribution-free tests for incomplete multivariate observations (1984) Journal of the American Statistical Association, 79 (387), pp. 653-669
Pulkstenis, E.P., Ten Have, T.R., Landis, J.R., Model for the analysis of binary longitudinal pain data subject to informative dropout through remedication (1998) Journal of the American Statistical Society, 93, pp. 438-450
Plackett, R.L., A class of bivariate distributions (1965) Journal of the American Statistical Society, 60, pp. 516-522
Dale, J.R., Global cross-ratio models for bivariate, discrete, ordered responses (1986) Biometrics, 42, pp. 909-917
Kenward, M.G., Lesaffre, E., Molenberghs, G., An application of maximum likelihood and generalized estimating equations to the analysis of ordinal data from a longitudinal study with cases missing at random (1994) Biometrics, 50, pp. 945-953
Molenberghs, G., Kenward, M.G., Lesaffre, E., The analysis of longitudinal ordinal data with non-random drop-out (1997) Biometrika, 84, pp. 33-44
Fitzmaurice, G.M., Laird, N.M., Lipsitz, S.R., Analysing incomplete longitudinal binary responses: A likelihood-based approach (1994) Biometrics, 50, pp. 601-612
Verbeke, G., Molenberghs, G., (1997) Linear Mixed Models in Practice, , Springer-Verlag: New York
Curran, D., Molenberghs, G., Aaronson, N.K., Fossa, S.D., Sylvester, R.J., Analyzing longitudinal continuous quality of life data with dropout (1999) Journal of Applied Statistics, , (submitted)
Ridout, M., Testing for random dropouts in repeated measurement data (1991) Biometrics, 47, pp. 1617-1621
Diggle, P., Kenward, M.G., Informative drop-out in longitudinal data analysis (1994) Applied Statistics, 43, pp. 49-93. , (with discussion)
Diggle, P.J., Testing for random dropouts in repeated measurement data (1989) Biometrics, 45, pp. 1255-1258
Breslow, N.E., Clayton, D.G., Approximate inference in generalized linear mixed model (1993) Journal of American Statistical Society, 88, pp. 9-25
Neuhaus, J., Statistical methods for longitudinal and clustered designs with binary responses (1992) Statistical Methods in Medical Research, 1, pp. 249-273
Zeger, S.L., Karim, M.R., Generalized linear models with random effects
a Gibbs sampling approach (1991) Journal of the American Statistical Association, 86, pp. 79-86
Molenberghs, G., Ritter, L.L., Methods for analyzing multivariate binary data, with association between outcomes of interest (1996) Biometrics, 52, pp. 1121-1133