Abstract

Validation of surrogate endpoints in multiple randomized clinical trials with discrete outcomess

Renard, D., Geys, H., Molenberghs, G., Burzykowski, T., and Buyse, M.

This article extends the work of Buyse et al. (2000) on the validation of surrogate endpoints in a meta-analytic setting to the case of two discrete outcomes, the focus being on binary endpoints. This approach entails fitting of a joint model for the surrogate and true endpoints that includes several random effects. We propose to fit this model using a pseudo-likelihood estimation procedure which seems better suited to the problem at hand than maximum likelihood or penalized quasi-likelihood estimation methods. The performance of the pseudo-likelihood estimator is evaluated on the grounds of limited simulations and the methodology is illustrated on data from a meta-analysis of five clinical trials comparing antipsychotic agents for the treatment of chronic schizophrenia.

  Last update: January, 24, 2003  - Contact : S. Malali