Inference of bioequivalence for log-normal distributed data with unspecified variances.
Stat Med
; 33(17): 2924-38, 2014 Jul 30.
Article
en En
| MEDLINE
| ID: mdl-24403216
ABSTRACT
Two drugs are bioequivalent if the ratio of a pharmacokinetic (PK) parameter of two products falls within equivalence margins. The distribution of PK parameters is often assumed to be log-normal, therefore bioequivalence (BE) is usually assessed on the difference of logarithmically transformed PK parameters (δ). In the presence of unspecified variances, test procedures such as two one-sided tests (TOST) use sample estimates for those variances; Bayesian models integrate them out in the posterior distribution. These methods limit our knowledge on the extent that inference about BE is affected by the variability of PK parameters. In this paper, we propose a likelihood approach that retains the unspecified variances in the model and partitions the entire likelihood function into two components F-statistic function for variances and t-statistic function for δ. Demonstrated with published real-life data, the proposed method not only produces results that are same as TOST and comparable with Bayesian method but also helps identify ranges of variances, which could make the determination of BE more achievable. Our findings manifest the advantages of the proposed method in making inference about the extent that BE is affected by the unspecified variances, which cannot be accomplished either by TOST or Bayesian method.
Palabras clave
Texto completo:
1
Base de datos:
MEDLINE
Asunto principal:
Farmacocinética
/
Equivalencia Terapéutica
/
Funciones de Verosimilitud
/
Modelos Estadísticos
Tipo de estudio:
Prognostic_studies
/
Risk_factors_studies
Límite:
Humans
Idioma:
En
Revista:
Stat Med
Año:
2014
Tipo del documento:
Article
País de afiliación:
Estados Unidos