Research output: Contribution to Journal/Magazine › Journal article › peer-review
Research output: Contribution to Journal/Magazine › Journal article › peer-review
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TY - JOUR
T1 - Considerations on covariates and endpoints in multi-arm multi-stage clinical trials selecting all promising treatments
AU - Jaki, Thomas
AU - Magirr, Dominic
PY - 2013/3/30
Y1 - 2013/3/30
N2 - In early stages of drug development, there is often uncertainty about the most promising among a set of different treatments. To ensure the best use of resources in such situations, it is important to decide which, if any, of the treatments should be taken forward for further testing. In later development, it has been shown that evaluating more than one dose increases the chance of success substantially. In this work, we discuss how multi-arm multi-stage trials can be designed such that all promising treatments are kept in the study at the interim analyses. We first investigate the impact of deviating from the planned design and show how confidence intervals can be constructed before we consider the impact of important covariates. We show that under orthogonality, the inclusion of covariates has no effect on familywise error rate control in the strong sense. We further show that the derived methodology can be used to investigate non-normal endpoints.
AB - In early stages of drug development, there is often uncertainty about the most promising among a set of different treatments. To ensure the best use of resources in such situations, it is important to decide which, if any, of the treatments should be taken forward for further testing. In later development, it has been shown that evaluating more than one dose increases the chance of success substantially. In this work, we discuss how multi-arm multi-stage trials can be designed such that all promising treatments are kept in the study at the interim analyses. We first investigate the impact of deviating from the planned design and show how confidence intervals can be constructed before we consider the impact of important covariates. We show that under orthogonality, the inclusion of covariates has no effect on familywise error rate control in the strong sense. We further show that the derived methodology can be used to investigate non-normal endpoints.
KW - confidence intervals
KW - Dunnett test
KW - multi-arm, multi-stage
KW - ordinal
KW - time-to-event
U2 - 10.1002/sim.5669
DO - 10.1002/sim.5669
M3 - Journal article
VL - 32
SP - 1150
EP - 1163
JO - Statistics in Medicine
JF - Statistics in Medicine
SN - 0277-6715
IS - 7
ER -