Response-adaptive randomization for multi-arm clinical trials using the forward looking Gittins index rule.
Biometrics
; 71(4): 969-78, 2015 Dec.
Article
em En
| MEDLINE
| ID: mdl-26098023
ABSTRACT
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.
Palavras-chave
Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Ensaios Clínicos Controlados Aleatórios como Assunto
Tipo de estudo:
Clinical_trials
/
Prognostic_studies
/
Risk_factors_studies
Limite:
Humans
Idioma:
En
Revista:
Biometrics
Ano de publicação:
2015
Tipo de documento:
Article
País de afiliação:
Reino Unido