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Exact test-based approach for equivalence test with parameter margin.

Xiaoyu Cassie Dong1, Yuanyuan Bian2, Yi Tsong3

  • 1a Global Biostatistical Science, Amgen Inc. , Washington , DC , USA.

Journal of Biopharmaceutical Statistics
|January 6, 2017
PubMed
Summary
This summary is machine-generated.

This study introduces an exact statistical test to accurately assess similarity between products, crucial for biosimilar development. It addresses inflated error rates in traditional methods, ensuring reliable equivalence testing.

Keywords:
Analytical similarityType I error rateequivalence marginequivalence testpower

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Area of Science:

  • Pharmaceutical Statistics
  • Biostatistics
  • Analytical Chemistry

Background:

  • Equivalence testing is vital in pharmaceutical statistics for assessing similarity between two groups, particularly for biosimilar products.
  • Current methods comparing mean values against an equivalence margin (±f × σR) can inflate Type I and Type II error rates when the margin is estimated from the sample (±f × SR).

Purpose of the Study:

  • To develop and evaluate an exact-based test method for equivalence testing of means.
  • To compare the performance of the new method against existing approaches like the Wald test, constrained Wald test, and Generalized Pivotal Quantity (GPQ).

Main Methods:

  • Development of an exact-based statistical test for equivalence.
  • Comparative analysis of Type I error rates and power across different testing methods.
  • Application of methods to real-world data analysis.

Main Results:

  • The proposed exact-based test method is shown to resolve inflated error rates associated with classic t-tests using estimated margins.
  • Performance comparison indicates the advantages of the new method over Wald, constrained Wald, and GPQ tests in specific scenarios.

Conclusions:

  • The developed exact-based test offers a more reliable approach for equivalence testing in pharmaceutical statistics.
  • This methodology is broadly applicable, extending beyond analytical similarity assessments for biosimilars.