Analysis of dose-response in flexible dose titration clinical studies

Assessing doseresponse from flexible-dose clinical trials (e.g., titration or dose escalation studies) is challenging and often problematic due to the selection bias caused by titration-to-response. We investigate the performance of a dynamic linear mixed-effects (DLME) model and marginal structural model (MSM) in evaluating doseresponse from flexible-dose titration clinical trials via simulations. The simulation results demonstrated that DLME models with previous exposure as a time-varying covariate may provide an unbiased and efficient estimator to recover exposureresponse relationship from flexible-dose clinical trials. Although the MSM models with independent and exchangeable working correlations appeared to be able to recover the right direction of the doseresponse relationship, it tended to over-correct selection bias and overestimated the underlying true doseresponse. The MSM estimators were also associated with large variability in the parameter estimates. Therefore, DLME may be an appropriate modeling option in identifying doseresponse when data from fixed-dose studies are absent or a fixed-dose design is unethical to be implemented. Copyright (c) 2012 John Wiley & Sons, Ltd.