Premium
Designing a series of decision‐theoretic phase II trials in a small population
Author(s) -
Hee Siew Wan,
Stallard Nigel
Publication year - 2012
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.5573
Subject(s) - interim , phase (matter) , series (stratigraphy) , frequentist inference , interim analysis , computer science , population , clinical trial , econometrics , statistics , bayesian probability , medicine , mathematics , artificial intelligence , bayesian inference , paleontology , chemistry , environmental health , archaeology , organic chemistry , biology , history
This paper introduces a decision‐theoretic design for a series of phase II trials. Instead of designing phase II trials individually, we proposed a development plan that consists of a series of phase II trials and one phase III trial such that the long‐term expected utility on the whole is optimized. The phase II trials are conducted sequentially, and patients are recruited sequentially to each phase II trial. At each interim stage, a decision is made to continue recruiting patients to the current trial, to stop and recommend the treatment proceeds to a phase III trial, to stop and initiate a new phase II trial or to stop and cease the development plan. The methodology uses a hybrid approach in which it is assumed that the data from the final phase III trial will be analysed using a classical frequentist hypothesis test. The expected power of this test based on some specified prior distribution for the effect of the experimental treatment is then used in a utility function, which is used to obtain the optimal design for the whole series of trials. Copyright © 2012 John Wiley & Sons, Ltd.