Hierarchical Bayesian approaches to phase II trials in diseases with multiple subtypes

Abstract

We propose a methodology for conducting phase II clinical trials in settings where the disease is categorized into multiple subtypes. A hierarchical Bayesian model is assumed for treatment effects within the subtypes. The hierarchical model, which is tailored to each particular application, allows treatment effects to differ across subtypes while assuming a priori that the effects are exchangeable and correlated. Two applications are described. The first is a trial of imatinib for sarcoma in which treatment activity is characterized by a binary indicator of tumour response. The second is a phase II trial of a new preparative regimen for allogeneic bone marrow transplantation in patients with haematologic malignancies, with treatment effect characterized by the mean time from transplant to disease progression or death. The applications illustrate how the hierarchical Bayesian model borrows strength across subtypes.