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.

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Abstract

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.

Impact and interest:

11 citations in Scopus
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10 citations in Web of Science®

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ID Code: 90605
Item Type: Journal Article
Refereed: Yes
Additional Information: ISI Document Delivery No.: 409GW
Times Cited: 10
Cited Reference Count: 5
Leung, DHY Wang, YG
International biometric soc
Washington
Keywords: Bayesian, decision theory, gain function, Gittins Index, sample size, sequential design, clinical-trials
DOI: 10.1111/j.0006-341X.2001.00309.x
ISSN: 0006-341X
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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