Challenges in longitudinal exposure-response modeling of data from complex study designs: a case study of modeling CDAI score for ustekinumab in patients with Crohn's disease.
J Pharmacokinet Pharmacodyn
; 44(5): 425-436, 2017 Oct.
Article
em En
| MEDLINE
| ID: mdl-28623612
ABSTRACT
Informative exposure-response modeling of clinical endpoints is important in drug development to identify optimum dose and dosing regimens. Despite much recent progress in mechanism-based longitudinal modeling of clinical data, challenges remain in clinical trials of diseases such as Crohn's disease, where a commonly used composite endpoint Crohn's Disease Activity Index (CDAI) has considerable variation in its administration and scoring between different assessors and complex study designs typically include maintenance phases with randomized withdrawal re-randomizations and other response driven dose adjustments. This manuscript illustrates the complexities of exposure-response modeling of such composite endpoint data through a latent-variable based Indirect Response model framework for CDAI scores using data from three phase III trials of ustekinumab in patients with moderate-to-severe Crohn's Disease. Visual predictive check was used to evaluate model performance. Potential impacts of the study design on model development and evaluation of the E-R relationship in the induction and maintenance phases of treatment are discussed. Certain biases appeared difficult to overcome, and an autocorrelated residual error model was found to provide improvement.
Palavras-chave
Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Projetos de Pesquisa
/
Doença de Crohn
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Relação Dose-Resposta a Droga
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Ustekinumab
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Modelos Biológicos
Tipo de estudo:
Clinical_trials
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Observational_studies
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Prognostic_studies
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Risk_factors_studies
Limite:
Humans
Idioma:
En
Revista:
J Pharmacokinet Pharmacodyn
Assunto da revista:
FARMACOLOGIA
Ano de publicação:
2017
Tipo de documento:
Article
País de afiliação:
Estados Unidos