An information-theoretic approach for the assessment of a continuous outcome as a surrogate for a binary true endpoint based on causal inference: Application to vaccine evaluation.
Stat Med
; 43(6): 1083-1102, 2024 Mar 15.
Article
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| MEDLINE
| ID: mdl-38164018
ABSTRACT
Within the causal association paradigm, a method is proposed to assess the validity of a continuous outcome as a surrogate for a binary true endpoint. The methodology is based on a previously introduced information-theoretic definition of surrogacy and has two main steps. In the first step, a new model is proposed to describe the joint distribution of the potential outcomes associated with the putative surrogate and the true endpoint of interest. The identifiability issues inherent to this type of models are handled via sensitivity analysis. In the second step, a metric of surrogacy new to this setting, the so-called individual causal association is presented. The methodology is studied in detail using theoretical considerations, some simulations, and data from a randomized clinical trial evaluating an inactivated quadrivalent influenza vaccine. A user-friendly R package Surrogate is provided to carry out the evaluation exercise.
Palabras clave
Texto completo:
1
Banco de datos:
MEDLINE
Asunto principal:
Vacunas
/
Investigación Biomédica
Tipo de estudio:
Clinical_trials
Límite:
Humans
Idioma:
En
Revista:
Stat Med
/
Stat. med
/
Statistics in medicine
Año:
2024
Tipo del documento:
Article
País de afiliación:
Bélgica