A Bayesian decision approach for sample size determination in phase II trials
Leung, D. H. Y. & Wang, Y-G. (2001) A Bayesian decision approach for sample size determination in phase II trials. Biometrics, 57(1), pp. 309-312.
Stallard (1998, Biometrics 54, 279-294) recently used Bayesian decision theory for sample-size determination in phase II trials. His design maximizes the expected financial gains in the development of a new treatment. However, it results in a very high probability (0.65) of recommending an ineffective treatment for phase III testing. On the other hand, the expected gain using his design is more than 10 times that of a design that tightly controls the false positive error (Thall and Simon, 1994, Biometrics 50, 337-349). Stallard's design maximizes the expected gain per phase II trial, but it does not maximize the rate of gain or total gain for a fixed length of time because the rate of gain depends on the proportion: of treatments forwarding to the phase III study. We suggest maximizing the rate of gain, and the resulting optimal one-stage design becomes twice as efficient as Stallard's one-stage design. Furthermore, the new design has a probability of only 0.12 of passing an ineffective treatment to phase III study.
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|Item Type:||Journal Article|
|Additional Information:||ISI Document Delivery No.: 409GW
Times Cited: 10
Cited Reference Count: 5
Leung, DHY Wang, YG
International biometric soc
|Keywords:||Bayesian, decision theory, gain function, Gittins Index, sample size, sequential design, clinical-trials|
|Divisions:||Current > QUT Faculties and Divisions > Science & Engineering Faculty|
|Copyright Owner:||Copyright Wiley-Blackwell|
|Deposited On:||20 Nov 2015 03:45|
|Last Modified:||20 Nov 2015 03:45|
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