Your browser doesn't support javascript.
loading
A model-based approach to sample size estimation in recent onset type 1 diabetes.
Bundy, Brian N; Krischer, Jeffrey P.
Afiliação
  • Bundy BN; Health Informatics Institute, University of South Florida, Tampa, FL, USA.
  • Krischer JP; Health Informatics Institute, University of South Florida, Tampa, FL, USA. jpkrischer@epi.usf.edu.
Diabetes Metab Res Rev ; 32(8): 827-834, 2016 11.
Article em En | MEDLINE | ID: mdl-26991448
BACKGROUND: The area under the curve C-peptide following a 2-h mixed meal tolerance test from 498 individuals enrolled on five prior TrialNet studies of recent onset type 1 diabetes from baseline to 12 months after enrolment were modelled to produce estimates of its rate of loss and variance. RESULTS: Age at diagnosis and baseline C-peptide were found to be significant predictors, and adjusting for these in an ANCOVA resulted in estimates with lower variance. CONCLUSIONS: Using these results as planning parameters for new studies results in a nearly 50% reduction in the target sample size. The modelling also produces an expected C-peptide that can be used in observed versus expected calculations to estimate the presumption of benefit in ongoing trials. Copyright © 2016 John Wiley & Sons, Ltd.
Assuntos
Palavras-chave

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Biomarcadores / Modelos Estatísticos / Diabetes Mellitus Tipo 1 Tipo de estudo: Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Adolescent / Adult / Child / Child, preschool / Female / Humans / Male / Middle aged Idioma: En Ano de publicação: 2016 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Biomarcadores / Modelos Estatísticos / Diabetes Mellitus Tipo 1 Tipo de estudo: Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Adolescent / Adult / Child / Child, preschool / Female / Humans / Male / Middle aged Idioma: En Ano de publicação: 2016 Tipo de documento: Article