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2015 ; 71
(4
): 969-78
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Response-adaptive randomization for multi-arm clinical trials using the forward
looking Gittins index rule
#MMPMID26098023
Villar SS
; Wason J
; Bowden J
Biometrics
2015[Dec]; 71
(4
): 969-78
PMID26098023
show ga
The Gittins index provides a well established, computationally attractive,
optimal solution to a class of resource allocation problems known collectively as
the multi-arm bandit problem. Its development was originally motivated by the
problem of optimal patient allocation in multi-arm clinical trials. However, it
has never been used in practice, possibly for the following reasons: (1) it is
fully sequential, i.e., the endpoint must be observable soon after treating a
patient, reducing the medical settings to which it is applicable; (2) it is
completely deterministic and thus removes randomization from the trial, which
would naturally protect against various sources of bias. We propose a novel
implementation of the Gittins index rule that overcomes these difficulties,
trading off a small deviation from optimality for a fully randomized, adaptive
group allocation procedure which offers substantial improvements in terms of
patient benefit, especially relevant for small populations. We report the
operating characteristics of our approach compared to existing methods of
adaptive randomization using a recently published trial as motivation.