Volume 22, Issue 5
Research Article

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

Peter F. Thall

Corresponding Author

E-mail address: rex@manderson.org

Department of Biostatistics, Box 447, University of Texas, M.D. Anderson Cancer Center, Houston, Texas, U.S.A.

Department of Biostatistics, Box 447, University of Texas, M.D. Anderson Cancer Center, Houston, TX 77030‐4095, U.S.A.Search for more papers by this author
J. Kyle Wathen

Department of Biostatistics, Box 447, University of Texas, M.D. Anderson Cancer Center, Houston, Texas, U.S.A.

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B. Nebiyou Bekele

Department of Biostatistics, Box 447, University of Texas, M.D. Anderson Cancer Center, Houston, Texas, U.S.A.

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Richard E. Champlin

Department of Blood and Marrow Transplantation, Box 423, University of Texas, M.D. Anderson Cancer Center, Houston, Texas, U.S.A.

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Laurence H. Baker

University of Michigan Comprehensive Cancer Center, 1500 East Medical Drive, 7216 CCGC, Ann Arbor, Michigan 48109‐0948, U.S.A.

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Robert S. Benjamin

Department of Sarcoma Medical Oncology, Box 450, University of Texas, M.D. Anderson Cancer Center, 1515 Holcombe Boulevard, Houston, Texas 77030, U.S.A.

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First published: 05 February 2003
Citations: 83

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. Copyright © 2003 John Wiley & Sons, Ltd.

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