Generating Virtual Patients by Multivariate and Discrete Re-Sampling Techniques.
Pharm Res
; 32(10): 3228-37, 2015 Oct.
Article
en En
| MEDLINE
| ID: mdl-25994981
ABSTRACT
PURPOSE:
Clinical Trial Simulations (CTS) are a valuable tool for decision-making during drug development. However, to obtain realistic simulation scenarios, the patients included in the CTS must be representative of the target population. This is particularly important when covariate effects exist that may affect the outcome of a trial. The objective of our investigation was to evaluate and compare CTS results using re-sampling from a population pool and multivariate distributions to simulate patient covariates.METHODS:
COPD was selected as paradigm disease for the purposes of our analysis, FEV1 was used as response measure and the effects of a hypothetical intervention were evaluated in different populations in order to assess the predictive performance of the two methods.RESULTS:
Our results show that the multivariate distribution method produces realistic covariate correlations, comparable to the real population. Moreover, it allows simulation of patient characteristics beyond the limits of inclusion and exclusion criteria in historical protocols.CONCLUSION:
Both methods, discrete resampling and multivariate distribution generate realistic pools of virtual patients. However the use of a multivariate distribution enable more flexible simulation scenarios since it is not necessarily bound to the existing covariate combinations in the available clinical data sets.Palabras clave
Texto completo:
1
Bases de datos:
MEDLINE
Asunto principal:
Simulación por Computador
Tipo de estudio:
Guideline
/
Prognostic_studies
Límite:
Adult
/
Aged
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Aged80
/
Female
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Humans
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Male
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Middle aged
Idioma:
En
Revista:
Pharm Res
Año:
2015
Tipo del documento:
Article
País de afiliación:
Países Bajos