Communications for Statistical Applications and Methods

  • 제27권1호
  • /
  • Pages.1-14
  • /
  • 2020
  • /
  • 2287-7843(pISSN)
  • /
  • 2383-4757(eISSN)
한국통계학회 (The Korean Statistical Society)
권호 표지
DOI QR코드

DOI QR Code

Statistical tests for biosimilarity based on relative distance between follow-on biologics for ordinal endpoints

  • Yoo, Myung Soo (Department of Statistics, Sungkyunkwan University) ;
  • Kim, Donguk (Department of Statistics, Sungkyunkwan University)
  • 투고 : 2018.12.18
  • 심사 : 2019.07.20
  • 발행 : 2020.01.31
PDF 다운로드
⟨ 이전 논문 다음 논문 ⟩

초록

Investigations of biosimilarity between reference drugs and test drugs required statistical tests; in addition, statistical tests to evaluate biosimilarity have been recently proposed. Ordinal outcome data has been observed in research; however, appropriate statistical tests to deal with ordinal endpoints for biosimilar have not yet been proposed. This paper extends existing design for ordinal endpoints. Using measure of nominal-ordinal association and relative distances between drugs are defined so that testing procedures are developed. Through simulation studies, we investigate type I error rate and power to show the performance of our suggested method. Furthermore, a comparison between the statistical tests and other designs is proviede to show significance of ordinal endpoints.

키워드

참고문헌

  1. Agresti A (1981). Measures of nominal-ordinal association, Journal of the American Statistical Association, 76, 524-529. https://doi.org/10.1080/01621459.1981.10477679
  2. Chen C, Tsou H, Hsiao C, Lai Y, Chang W, and Liu J (2017). A tolerance interval approach to assessing the biosimilarity of follow-on biologics, Statistics in Biopharmaceutical Research, 9, 286-292. https://doi.org/10.1080/19466315.2017.1323669
  3. Doll R and Pygott F (1952). Factors influencing the rate of healing of gastric ulcers admission to hospital, phenobarbitone, and ascorbic acid, Lancet, 259, 171-175. https://doi.org/10.1016/S0140-6736(52)91405-0
  4. Kang SH and Chow SC (2013). Statistical assessment of biosimilarity based on relative distance between follow-on biologics, Statistics in Medicine, 32, 382-392. https://doi.org/10.1002/sim.5582
  5. Kang SH and Kim Y (2014). Sample size calculations for the development of biosimilar products, Journal of Biopharmaceutical Statistics, 24, 1215-1224. https://doi.org/10.1080/10543406.2014.941984
  6. Kang SH, Jung J, and Baik S (2015). Sample size calculations for the development of biosimilar products based on binary endpoints, Communications for Statistical Applications and Methods, 22, 389-399. https://doi.org/10.5351/CSAM.2015.22.4.389
  7. Kang SH and Shin W (2015). Statistical assesment of biosimilarity based on the relative distance between follow-on biologics in the (k + 1)-arm parallel design, Communications for Statistical Applications and Methods, 22, 605-613. https://doi.org/10.5351/CSAM.2015.22.6.605
  8. Lawless JF (1982). Statistical Models and Methods for Lifetime Data, Wiley, New York.
  9. Lu Y, Zhang Z, and Chow SC (2014). Frequency estimator for assessing of follow-on biologics, Journal of Biopharmaceutical Statistics, 24, 1280-1297. https://doi.org/10.1080/10543406.2014.941985
  10. Piccarreta R (2001). A new measure of nominal-ordinal association, Journal of Applied Statistics, 28, 107-120. https://doi.org/10.1080/02664760120011635
  11. Roozenbeek B, Lingsma H, Perel P, Edwards P, Roberts I, Murray G, Maas A, and Steyerberg E (2011). The added value of ordinal analysis in clinical trials: an example in traumatic brain injury, Critical Care, 15, R127. https://doi.org/10.1186/cc10240
  12. Shin W and Kang SH (2016). Statistical assessment of biosimilarity based on the relative distance between follow-on biologics for binary endpoints, Journal of Biopharmaceutical Statistics, 26, 227-239. https://doi.org/10.1080/10543406.2014.979195
  13. Sankey S andWeissfeld L (1998). A study of the effect of dichotomizing ordinal data upon modeling, Communications in Statistics-Simulation and Computation, 27, 871-887. https://doi.org/10.1080/03610919808813515
  14. US Food and Drug Administration (2015). Scientific consideration in demonstrating biosimilarity to a reference product: guidance for industry, Retrieved April, 2015, from: https://www.fda.gov/media/82647/download
  15. Vulto A and Jaquez O (2017). The process defines the product: what really matters in biosimilar design and production?, Rheumatology, 56, iv14-29. https://doi.org/10.1093/rheumatology/kex278
  16. Yang J, Zhang N, Chow SC, and Chi E (2012). An adapted F-test for homogeneity of variability in follow-on biological products, Statistics in Medicine, 32, 415-423. https://doi.org/10.1002/sim.5568
  17. Zhang N, Yang J, Chow SC, and Chi E (2014). Nonparametric tests for evaluation of biosimilarity in variability of follow-on biologics, Journal of Biopharmaceutical Statistics, 24, 1239-1253. https://doi.org/10.1080/10543406.2014.941991