Estimation of the Combined Response to treatment in Multicentre Trials
Estimation of the Combined Response to Treatment in Multicentre Trials
Vladimir Dragalin, Valerii Fedorov, Byron Jones and Frank Rockhold
Abstract. Analyses of multicentre trials consider the estimated treatment effect differences of the individual centres and combine them in an estimate of the overall treatment effect. There has been much debate in the literature concerning the best way to combine these treatment effect differences. We emphasize that first of all one should define the combined response to treatment (CRT), the object that has to be estimated from the results of a multicentre clinical trial. Having the defined target in mind, the least squares estimators of the CRT under three possible models of increasing complexity for multicentre data are derived. We compare these estimators in terms of their mean squared errors. It is shown that the choice of CRT determines not only the best estimator, but also the allocation of patients among the centres that minimizes the MSE. A new estimator of the CRT is proposed that is based on a preliminary clustering of the centres and the use of a weighted average of the Type I estimators obtained from within each cluster. The clustering aims to minimize the bias of the combined estimator. We show via a simulation study that the simple clustering procedure provides a reasonably improved estimator. The clustering can be done on unblinded data, as long as the numbers of patients on each treatment arm in each centre are known.
