Algorithms for evaluating reference scaled average bioequivalence: power, bias, and consumer risk

L. Tóthfalusi, Laszlo Endrenyi

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

The determination of the bioequivalence between highly variable drug products involves the evaluation of reference scaled average bioequivalence. The European and US regulatory authorities suggest different algorithms for the implementation of this approach. Both algorithms are based on approximations reflected in lower than the achievable power or higher than the nominal consumer risk of 5%. To overcome these deficiencies, a new class of algorithms, the so-called Exact methods, was earlier introduced. However, their applicability was limited. We propose 2 modifications which make their computation simpler and also applicable with any study design. Four algorithms were evaluated in simulated 3-period and 4-period bioequivalence studies: Hyslop's approach recommended by the US FDA, the method of average bioequivalence with expanding limits requested by the European EMA, and 2 versions of the new Exact methods. At small sample sizes, the Exact methods had substantially higher statistical power than Hyslop's algorithm and had lower consumer risk than the method of average bioequivalence with expanding limits. Similarly to the Hyslop's algorithm, higher than 5% consumer risk was observed only with either unbalanced study design or with additional regulatory requirements. The improved Exact algorithms compare favorably with the alternative procedures. They are based on the bias correction method of Hedges. The recognition that the scaled difference statistics is measured with bias has important practical implications when results of pilot bioequivalence studies are evaluated and, at the same time, calls for the revision of the statistical theory of RSABE and its related methods.

Original languageEnglish
Pages (from-to)4378-4390
Number of pages13
JournalStatistics in Medicine
Volume36
Issue number27
DOIs
Publication statusPublished - Nov 30 2017

Fingerprint

Consumer Risk
Bioequivalence
Therapeutic Equivalency
Exact Method
Unbalanced Designs
Bias Correction
Statistical Power
Small Sample Size
Exact Algorithms
Categorical or nominal
Drugs
Sample Size
Statistics
Alternatives
Requirements
Evaluation
Approximation

Keywords

  • bioequivalence
  • effect size
  • equivalence test
  • highly variable drugs
  • scaled bioequivalence

ASJC Scopus subject areas

  • Epidemiology
  • Statistics and Probability

Cite this

Algorithms for evaluating reference scaled average bioequivalence : power, bias, and consumer risk. / Tóthfalusi, L.; Endrenyi, Laszlo.

In: Statistics in Medicine, Vol. 36, No. 27, 30.11.2017, p. 4378-4390.

Research output: Contribution to journalArticle

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