Simplified hierarchical linear models for the evaluation of surrogate endpoints

Journal of Statistical Computation and Simulation

Volumn 73, Issue 9, 2003, Pages 643-658

  Tibaldi, Fabián S ^a   Abrahantes, José Cortiñas ^a   Molenberghs, Geert ^a   Renard, Didier ^a   Burzykowski, Tomasz ^a   Buyse, Marc ^b   Parmar, Max ^c   Stijnen, Theo ^d   Wolfinger, Russ ^e  

^a HASSELT UNIVERSITY   (Belgium)

^b INTERNATIONAL DRUG DEVELOPMENT INSTITUTE   (Belgium)

^c UNIVERSITY OF CAMBRIDGE   (United Kingdom)

^d ERASMUS UNIVERSITY ROTTERDAM   (Netherlands)

^e SAS INSTITUTE INC   (United States)

Author keywords

Linear mixed model; Macular degeneration; Meta analytic approach; Oncology; Random effects; Surrogate endpoint

Indexed keywords

EID: 0041417500     PISSN: 00949655     EISSN: None     Source Type: Journal    
DOI: 10.1080/0094965031000062177     Document Type: Article

References (31)

1. Alonso, A., Geys, H., Molenberghs, G. and Vangeneugden, T. (2001). Investigating the criterion validity of psychiatric symptom scales using surrogate marker validation methodology (Submitted for publication).
2. Arnold, B. C. and Strauss, D. (1991). Pseudolikelihood estimation: Some examples. Sankhya B, 53, 233-243.
3. Boissel, J. P., Collet, J. P., Moleur, P., and Haugh, M. (1992). Surrogate endpoints: A basis for a rational approach. European Journal of Clinical Pharmacology, 43, 235-244.
4. Breslow, N. E. and Clayton, D. C. (1993). Approximate inference in generalized linear mixed models. Journal of the American Statistical Society, 88, 9-25.
5. Burzykowski, T., Molenberghs, G. and Buyse, M. (2001). The validation of surrogate endpoints using data from randomized clinical trials: A case study in advanced colorectal cancer (Submitted for publication).
6. Burzykowski, T., Molenberghs, C., Buyse, B., Geys, H. and Renard, D. (2001) Validation of surrogate endpoints in multiple randomized clinical trials with failure-time endpoints. Applied Statistic, 50, 405-422.
7. Buyse, M. and Molenberghs, G. (1998). The validation of surrogate endpoints in randomized experiments. Biometrics, 54, 186-201.
8. Buyse, M., Molenberghs, G., Burzykowski, T., Renard, D. and Geys, H. (2000a). The validation of surrogate endpoints in meta-analyses of randomized experiments. Biostatistics, 1, 1-19.
9. Buyse, M., Thirion, P., Carlson, R. W., Burzykowski, T., Molenberghs, G. and Piedbois, P. (2000b). Tumour response to first line chemotherapy improves the survival of patients with advanced colorectal cancer. Lancet, 356, 373-378.
10. Chuang-Stein, C. and DeMasi, R. (1998). Surrogate endpoints in AIDS drug development: Current status (with discussion). Drug Information Journal, 32, 439-459.
11. Corfu-A Study Group (1995). Phase III randomized study of two fluorouracil combinations with either Interferon alfa-2a or leucovorin for advanced colorectal cancer. Journal of Clinical Oncology, 13, 921-928.
12. Daniels, M. J. and Hughes, M. D. (1997). Meta-analysis for the evaluation of potential surrogate markers. Statistics in Medicine, 16, 1965-1982.
13. De Gruttola, V., Fleming, T. R., Lin, D. Y. and Coombs, R. (1997). Validating surrogate markers - are we being naive? Journal of Infectious Diseases, 175, 237-246.
14. Fleming, T. R. and DeMets D. L. (1996). Surrogate endpoints in clinical trials: Are we being misled? Annals of Internal Medicine, 125, 605-613.
15. Flandre, P. and Saidi, Y. (1999). Letters to the editor: Estimating the proportion of treatment effect explained by a surrogate marker. Statistics in Medicine, 18, 107-115.
16. Freedman, L. S., Graubard, B. I. and Schatzkin, A. (1992). Statistical validation of intermediate end-points for chronic diseases. Statistics in Medicine, 11, 167-178.
17. Gail, M. H., Pfeiffer, R., Van Houwelingen, H. C. and Carroll, R. (2000). On meta-analytic assessment of surrogate outcomes. Biostatistics, 1, 231-246.
18. Goldstein, H. (1991). Nonlinear multilevel models, with an application to discrete response data. Biometrika, 73, 43-56.
19. Goldstein, H. (1995). Multilevel Statistical Models, 2nd ed. Edward Arnold, London.
20. Goldstein, H. and Rasbash, J. (1996). Improved approximations for multilevel models with binary responses. Journal of the Royal Statistical Society A, 159, 505-513.
21. Goldstein, H., Rasbash, J., Plewis, I., Draper, D., Browne, W., Yang, M. et al. (1998). A User's Guide to ML wiN. Institute of Education, London.
22. Greco, F. A., Figlin, R., York, M., Einhorn, L., Schilsky, R., Marshall, E. M., et al. (1996). Phase III randomized study to compare Interferon alfa-2a in combination with fluorouracil versus fluorouracil alone in patients with advanced colorectal cancer. Journal of Clinical Oncology, 14, 2674-2681.
23. Johnson, R. A. and Wichern, D. W. (1992). Applied Multivariate Statistical Analysis, 3rd ed. Prentice-Hall, Englewood Cliffs.
24. Le Cessie, S. and Van Houwelingen, J. C. (1994). Logistic regression for correlated binary data. Applied Statistics, 43, 95-108.
25. Lehmann, E. L. (1983). Theory of Point Estimation. Wiley, New-York.
26. Molenberghs, G., Buyse, M., Geys, H., Renard, D., Burzykowski, T. and Alonso, A. (2002). Statistical challenges in the evaluation of surrogate endpoints in randomized trials. Controlled Clinical Trials, (Submitted for publication).
27. Prentice, R. L. (1989). Surrogate endpoints in clinical trials: Definitions and operational criteria. Statistics in Medicine, 8, 431-440.
28. Rodríguez, G. and Goldman, N. (1995). An assessment of estimation procedures for multilevel models with binary responses. Journal of the American Statistical Society, 158, 73-89.
29. Van Houwelingen, J. C., Arends, L. A. and Stijnen, T. (2001). Advanced methods for meta-analysis. Statistics in Medicine (to appear).
30. Verbeke, G. and Molenberghs, G. (2000). Linear Mixed Model for Longitudinal Data. Springer-Verlag, New York.
31. Wolfinger, R., and O'Connell, M. (1993). Generalized linear mixed models: A pseudo-likelihood approach. Journal of Statistical Computation and Simulation, 48, 233-243.