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Bioequivalence tests based on individual estimates using non-compartmental or model-based analyses: evaluation of estimates of sample means and type I error for different designs.

Abstract : PURPOSE: The main objective of this work is to compare the standard bioequivalence tests based on individual estimates of the area under the curve and the maximal concentration obtained by non-compartmental analysis (NCA) to those based on individual empirical Bayes estimates (EBE) obtained by nonlinear mixed effects models. METHODS: We evaluate by simulation the precision of sample means estimates and the type I error of bioequivalence tests for both approaches. Crossover trials are simulated under H ( 0 ) using different numbers of subjects (N) and of samples per subject (n). We simulate concentration-time profiles with different variability settings for the between-subject and within-subject variabilities and for the variance of the residual error. RESULTS: Bioequivalence tests based on NCA show satisfactory properties with low and high variabilities, except when the residual error is high, which leads to a very poor type I error, or when n is small, which leads to biased estimates. Tests based on EBE lead to an increase of the type I error, when the shrinkage is above 20%, which occurs notably when NCA fails. CONCLUSIONS: For small n or data with high residual error, tests based on a global data analysis should be considered instead of those based on individual estimates.
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https://www.hal.inserm.fr/inserm-00470343
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Submitted on : Tuesday, April 6, 2010 - 12:07:45 PM
Last modification on : Thursday, May 14, 2020 - 2:48:10 PM
Long-term archiving on: : Tuesday, September 14, 2010 - 5:19:59 PM

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Anne Dubois, Sandro Gsteiger, Etienne Pigeolet, France Mentré. Bioequivalence tests based on individual estimates using non-compartmental or model-based analyses: evaluation of estimates of sample means and type I error for different designs.. Pharmaceutical Research, American Association of Pharmaceutical Scientists, 2010, 27 (1), pp.92-104. ⟨10.1007/s11095-009-9980-5⟩. ⟨inserm-00470343⟩

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