Estimation in multi-arm two-stage trials with treatment selection and time-to-event endpoint.
Stat Med
; 36(20): 3137-3153, 2017 Sep 10.
Article
em En
| MEDLINE
| ID: mdl-28612371
ABSTRACT
We consider estimation of treatment effects in two-stage adaptive multi-arm trials with a common control. The best treatment is selected at interim, and the primary endpoint is modeled via a Cox proportional hazards model. The maximum partial-likelihood estimator of the log hazard ratio of the selected treatment will overestimate the true treatment effect in this case. Several methods for reducing the selection bias have been proposed for normal endpoints, including an iterative method based on the estimated conditional selection biases and a shrinkage approach based on empirical Bayes theory. We adapt these methods to time-to-event data and compare the bias and mean squared error of all methods in an extensive simulation study and apply the proposed methods to reconstructed data from the FOCUS trial. We find that all methods tend to overcorrect the bias, and only the shrinkage methods can reduce the mean squared error. © 2017 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.
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Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Ensaios Clínicos como Assunto
Tipo de estudo:
Clinical_trials
/
Prognostic_studies
Limite:
Humans
Idioma:
En
Revista:
Stat Med
Ano de publicação:
2017
Tipo de documento:
Article
País de afiliação:
Reino Unido