Statistical considerations when analyzing biomarker data.
Clin Immunol
; 161(1): 31-6, 2015 Nov.
Article
em En
| MEDLINE
| ID: mdl-26111480
ABSTRACT
Biomarkers have become, and will continue to become, increasingly important to clinical immunology research. Yet, biomarkers often present new problems and raise new statistical and study design issues to scientists working in clinical immunology. In this paper I discuss statistical considerations related to the important biomarker problems of 1) The design and analysis of clinical studies which seek to determine whether changes from baseline in a biomarker are associated with changes in a metabolic outcome; 2) The conditions that are required for a biomarker to be considered a "surrogate"; 3) Considerations that arise when analyzing whether or not a predictive biomarker could act as a surrogate endpoint; 4) Biomarker timing relative to the clinical endpoint; 5) The problem of analyzing studies that measure many biomarkers from few subjects; and, 6) The use of statistical models when analyzing biomarker data arising from count data.
Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Projetos de Pesquisa
/
Biomarcadores
/
Avaliação de Resultados em Cuidados de Saúde
/
Diabetes Mellitus Tipo 1
Tipo de estudo:
Diagnostic_studies
/
Prognostic_studies
/
Risk_factors_studies
Limite:
Humans
Idioma:
En
Ano de publicação:
2015
Tipo de documento:
Article