TY - JOUR

T1 - Estimation in AB/BA cross-over trials with application to bioequivalence studies with incomplete and complete data designs

AU - Jaki, Thomas

AU - Pallmann, Philip

AU - Wolfsegger, Martin J.

PY - 2013/12/30

Y1 - 2013/12/30

N2 - Crossover studies are frequently used in clinical research as they allow within-subject comparisons instead of the between-subject evaluation of parallel group designs. Estimation of interesting parameters from such designs is, however, not trivial. We provide three methods for estimating treatment effects and associated standard errors from an AB/BA crossover trial. Assuming at least asymptotic normality, we can obtain the confidence intervals for single parameters as well as for differences or ratios of treatment effects. The latter is particularly useful in a pharmacokinetic context to establish bioequivalence using area under the concentration versus time curves (AUCs). In this work, we will illustrate how Fieller-type confidence intervals can be constructed for the ratio of AUCs estimated using a noncompartmental approach in a sparse sampling setting from a two-treatment, two-period, two-sequence crossover trial. In particular, we will discuss a flexible batch design, which includes traditional serial sampling and complete data designs as special cases. Via simulation, we show that the proposed intervals have nominal coverage and keep the type I error even for small sample sizes. Moreover, we illustrate the methodology in a real data example.

AB - Crossover studies are frequently used in clinical research as they allow within-subject comparisons instead of the between-subject evaluation of parallel group designs. Estimation of interesting parameters from such designs is, however, not trivial. We provide three methods for estimating treatment effects and associated standard errors from an AB/BA crossover trial. Assuming at least asymptotic normality, we can obtain the confidence intervals for single parameters as well as for differences or ratios of treatment effects. The latter is particularly useful in a pharmacokinetic context to establish bioequivalence using area under the concentration versus time curves (AUCs). In this work, we will illustrate how Fieller-type confidence intervals can be constructed for the ratio of AUCs estimated using a noncompartmental approach in a sparse sampling setting from a two-treatment, two-period, two-sequence crossover trial. In particular, we will discuss a flexible batch design, which includes traditional serial sampling and complete data designs as special cases. Via simulation, we show that the proposed intervals have nominal coverage and keep the type I error even for small sample sizes. Moreover, we illustrate the methodology in a real data example.

KW - 2 × 2 × 2 crossover

KW - bioequivalence

KW - area under the concentration versus time curve

KW - noncompartmental

KW - PK parameter

KW - Satterthwaite's approximation

U2 - 10.1002/sim.5886

DO - 10.1002/sim.5886

M3 - Journal article

VL - 32

SP - 5469

EP - 5483

JO - Statistics in Medicine

JF - Statistics in Medicine

SN - 0277-6715

IS - 30

ER -