Science Journal of Clinical Medicine

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Determination of Sample Size for Two Stage Sequential Designs in Bioequivalence Studies under 2x2 Crossover Design

Received: 23 May 2014    Accepted: 26 August 2014    Published: 30 September 2014
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Abstract

Sequential design is an adaptive design that allows for pre-mature termination of a trial due to efficacy or futility based on the interim analyses. The concept of sequential statistical methods was originally motivated by the need to obtain clinical benefits under certain economic constraints. That is for a trial for a positive results, early stopping ensures that a new drug product can exploited sooner, while negative results indicated, early stopping avoids wastage of resources. In short, the right drug at the right time for the right patient. Furthermore, the possible implication of two stage sequential design/ sample size re-estimation is to adjust the sample size based on the observed variance estimated from the first stage. The purpose of this work was to determine the minimum number of sample size required to proceed the second stage of sequential design, and the simulation is done through R ve. 3.0.3 Statistical software package. In general, from our simulation study, we can understand that, for highly variable drugs (CV ≥30), the appropriate GMR value is between (0.95, 1.05), which is also appropriate for low variable drugs to achieve the minimum sample size required to conduct any clinical trials.

DOI 10.11648/j.sjcm.20140305.12
Published in Science Journal of Clinical Medicine (Volume 3, Issue 5, September 2014)
Page(s) 82-90
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Two Stage Sequential Design, Geometric Mean Ratio, Bioequivalence Study, Power and Sample Size

References
[1] Phillips, K.F. power of the two-one sided tests procedure in bioequivalence study. J.pharmacokin.biopharm;1990. 18(7), 137-144.
[2] Jones, B. Bioequivalence and statistics in clinical pharmacology.1st ed. Chapman & Hall/crc: Boca raton; 2006.
[3] Potvin, et. equential design approach for bioequivalence studies with crossover designs. Pharmaceutical statistics;2008. 7(17), 245-262.
[4] Deletti, E., Hauschke, D., & Steinjans, V.W.. Sample size determination for bioequivalence assessment by means of confidence intervals. Int. J.clin. Pharm. Ther. Toxicol; 1991.29(7), 1-8.
[5] Grizzle, J.E. the two-period cross-over design and its use in clinical trials: biometrics;1965. 21(13), 467-480.
[6] Hauck, W.W., Preston, P.E., & Bois, F.Y. a group sequential approach to crossover trials for average bioequivalence. Journal of biopharmaceutical statistics;1997.7(9), 87-96.
[7] Pocock S. Group sequential methods in the design and analysis of clinical trials. Biometrika;1977. 64 (8),191–199.
[8] Bonate, P.L. & Howard, D, R. Pharmacokinetics in drug development.3rd ed. Springer, heidelberg dordrecht london 2011.
[9] Liu, J. P. & Weng, C.Sevaluation of parametric and nonparametric two one-sided tests procedures for assessing bioequivalence of average bioavailability. Journal of biopharmaceutical statistics.1993.3(17), 85-102.
[10] Schuirmann, D.. comparison of the two one-sided tests procedure and the power approach for assessing the equivalence of average bioavailability. Journal of pharmacokinetics and bio-pharmaceutics; 1987.15(13), 657–680.
[11] Altman, D. G. Statistics in medical journals. Statistics in medicine; 1982. 1:59-71.
[12] Chow, S.C., & Liu, J.P.. Design and analysis of bioavailability and bioequivalence studies.3rd edn. Chapman & Hall/crc: Boca raton; 2009.
[13] O’brien, P.C., & Fleming, T.R. a multiple testing procedure for clinical trials. Biometrika; 1979. 35(7), 549-556
[14] Patterson, S., &Jones, B. Bioequivalence and statistics in clinical pharmacology. Chapman & hall/crc: boca raton; 2006.
[15] Westlake, W.J. the use of confidence intervals in comparative bioavailability trials. Journal of pharmaceutical sciences; 1972. 61(1), 1340 –1341.
[16] Chow, S.C. adaptive design methods in clinical trials. Chapman & Hall/crc: Boca raton; 2007.
[17] Julious, s. A. Sample sizes for clinical trials. Chapman & Hall/crc, Boca raton; 2010.
[18] Senn, S. Crossover trials in clinical research. 2nd ed. Charater: john wiley & sons; 2002.
Author Information
  • Department of Statistics, College of Science, P.O. Box 79, Bahir Dar University, Bahir Dar, Ethiopia

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    Haile Mekonnen Fenta. (2014). Determination of Sample Size for Two Stage Sequential Designs in Bioequivalence Studies under 2x2 Crossover Design. Science Journal of Clinical Medicine, 3(5), 82-90. https://doi.org/10.11648/j.sjcm.20140305.12

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    Haile Mekonnen Fenta. Determination of Sample Size for Two Stage Sequential Designs in Bioequivalence Studies under 2x2 Crossover Design. Sci. J. Clin. Med. 2014, 3(5), 82-90. doi: 10.11648/j.sjcm.20140305.12

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    AMA Style

    Haile Mekonnen Fenta. Determination of Sample Size for Two Stage Sequential Designs in Bioequivalence Studies under 2x2 Crossover Design. Sci J Clin Med. 2014;3(5):82-90. doi: 10.11648/j.sjcm.20140305.12

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  • @article{10.11648/j.sjcm.20140305.12,
      author = {Haile Mekonnen Fenta},
      title = {Determination of Sample Size for Two Stage Sequential Designs in Bioequivalence Studies under 2x2 Crossover Design},
      journal = {Science Journal of Clinical Medicine},
      volume = {3},
      number = {5},
      pages = {82-90},
      doi = {10.11648/j.sjcm.20140305.12},
      url = {https://doi.org/10.11648/j.sjcm.20140305.12},
      eprint = {https://download.sciencepg.com/pdf/10.11648.j.sjcm.20140305.12},
      abstract = {Sequential design is an adaptive design that allows for pre-mature termination of a trial due to efficacy or futility based on the interim analyses. The concept of sequential statistical methods was originally motivated by the need to obtain clinical benefits under certain economic constraints. That is for a trial for a positive results, early stopping ensures that a new drug product can exploited sooner, while negative results indicated, early stopping avoids wastage of resources. In short, the right drug at the right time for the right patient. Furthermore, the possible implication of two stage sequential design/ sample size re-estimation is to adjust the sample size based on the observed variance estimated from the first stage. The purpose of this work was to determine the minimum number of sample size required to proceed the second stage of sequential design, and the simulation is done through R ve. 3.0.3 Statistical software package. In general, from our simulation study, we can understand that, for highly variable drugs (CV ≥30), the appropriate GMR value is between (0.95, 1.05), which is also appropriate for low variable drugs to achieve the minimum sample size required to conduct any clinical trials.},
     year = {2014}
    }
    

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