Comparison of parametric and bootstrap method in bioequivalence test.

The Korean Journal of Physiology & Pharmacology : Official Journal of the Korean Physiological Society and the Korean Society of Pharmacology
Byung-Jin Ahn, Dong-Seok Yim

Abstract

The estimation of 90% parametric confidence intervals (CIs) of mean AUC and Cmax ratios in bioequivalence (BE) tests are based upon the assumption that formulation effects in log-transformed data are normally distributed. To compare the parametric CIs with those obtained from nonparametric methods we performed repeated estimation of bootstrap-resampled datasets. The AUC and Cmax values from 3 archived datasets were used. BE tests on 1,000 resampled datasets from each archived dataset were performed using SAS (Enterprise Guide Ver.3). Bootstrap nonparametric 90% CIs of formulation effects were then compared with the parametric 90% CIs of the original datasets. The 90% CIs of formulation effects estimated from the 3 archived datasets were slightly different from nonparametric 90% CIs obtained from BE tests on resampled datasets. Histograms and density curves of formulation effects obtained from resampled datasets were similar to those of normal distribution. However, in 2 of 3 resampled log (AUC) datasets, the estimates of formulation effects did not follow the Gaussian distribution. Bias-corrected and accelerated (BCa) CIs, one of the nonparametric CIs of formulation effects, shifted outside the parametric 90% CIs of the archive...Continue Reading

References

Jan 1, 1990·European Journal of Clinical Pharmacology·G Pabst, H Jaeger
Feb 1, 1993·Journal of Pharmaceutical Sciences·K K MidhaI J McGilveray
Mar 1, 1997·Journal of Biopharmaceutical Statistics·L F LaceyA Bye
Jun 7, 2005·Clinica Chimica Acta; International Journal of Clinical Chemistry·A Ralph Henderson

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Citations

Nov 1, 2015·NeuroImage·Andrea ChincariniUNKNOWN Alzheimer's Disease Neuroimaging Initiative
Oct 26, 2011·Journal of Biopharmaceutical Statistics·Iris PigeotJun Shao

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