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Review ArticleDOI Number : 10.36811/ojpsr.2019.110001Article Views : 1475Article Downloads : 47

A Critical Review on Adaptive Sample Size Re-estimation (SSR) Designs for Superiority Trials with Continuous Endpoints

Xiaoyu Cai, Yi Tsong* and Meiyu Shen

Division of Biometrics VI, Office of Biostatistics, Center for Drug Evaluation and Research, FDA,USA

*Corresponding author: Yi Tsong, Ph.D, Division of Biometrics VI, Office of Biostatistics, Center for Drug Evaluation and Research, FDA, USA, 10903 New Hampshire Ave, Silver Spring, MD 20903, Tel: 301-796-1013; Email: yi.tsong@fda.hhs.gov

Article Information

Aritcle Type: Review Article

Citation: Xiaoyu Cai, Yi Tsong, Meiyu Shen. 2019. A Critical Review on Adaptive Sample Size Re-estimation (SSR) Designs for Superiority Trials with Continuous Endpoints. Open J Pharm Sci Res. 1: 1-13.

Copyright:This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Copyright © 2019; Xiaoyu Cai

Publication history:

Received date: 08 March, 2019
Accepted date: 29 March, 2019
Published date: 01 April, 2019

Full text coming soon

References

  1. Friede T, Kieser M. 2006. Sample size recalculation in internal pilot study designs: a review. Biometrical Journal. 48: 537-555. [Ref.]
  2. Proschan MA. 2009. Sample size re-estimation in clinical trials. Biometrical Journal. 51: 348-357. [Ref.]
  3. Menon S, Massaro J, Pencina MJ, et al. 2013. Comparison of operating characteristics of commonly used sample size re-estimation procedures in a two-stage design. Communications in Statistics-Simulation and Computation. 42: 1140-1152. [Ref.]
  4. Pritchett YL, Menon S, Marchenko O, et al. 2015. Sample size re-estimation designs in confirmatory clinical trials-current state, statistical considerations, and practical guidance. Statistics in Biopharmaceutical Research. 7: 309-321. [Ref.]
  5. Guidance Draft. 2018. Adaptive Designs for Clinical Trials of Drugs and Biologics. Center for Biologics Evaluation and Research (CBER). [Ref.]
  6. Gould LA, Shih WJ. 1992. Sample size re-estimation without unblinding for normally distributed outcomes with unknown variance. Communications in Statistics-Theory and Methods. 21: 2833-2853. [Ref.]
  7. Gould LA. 1997. Issues in blinded sample size re-estimation. Communications in Statistics-Simulation and Computation. 26: 1229-1239. [Ref.]
  8. Friede T, Kieser M. 2002. On the inappropriateness of an EM algorithm based procedure for blinded sample size re-estimation. Statistics in Medicine. 21: 65-176. [Ref.]
  9. Zucker DM, Wittes JT, Schabenberger O, et al. 1999. Internal pilot studies II: comparison of various procedures. Statistics in Medicine. 18: 3493-3509. [Ref.]
  10. Kieser M, Friede T. 2003. Simple procedures for blinded sample size adjustment that do not affect the type I error rate. Statistics in Medicine. 22: 3571-3581. [Ref.]
  11. Stein C. 1945. A two-sample test for a linear hypothesis whose power is independent of the variance. The Annals of Mathematical Statistics. 16: 243-258. [Ref.]
  12. Wittes J, Brittain E. 1990. The role of internal pilot studies in increasing the efficiency of clinical trials. Statistics in Medicine. 9: 65-72. [Ref.]
  13. Kieser M, Friede T. 2000. Re-calculating the sample size in internal pilot study designs with control of the type I error rate. Statistics in Medicine. 19: 901-911. [Ref.]
  14. Friede T, Kieser M. 2001. Sample size adjustment in clinical trials for proving equivalence. Drug information journal. 35: 1401-1408. [Ref.]
  15. Bauer P, Kohne K. 1994. Evaluation of experiments with adaptive interim analyses. Biometrics. 1029-1041. [Ref.]
  16. Cui L, Hung HM, Wang SJ. 1999. Modification of sample size in group sequential clinical trials. Biometrics. 55: 853-857. [Ref.]
  17. Lehmacher W, Wassmer G. 1999. Adaptive sample size calculations in group sequential trials. Biometrics. 55: 1286-1290. [Ref.]
  18. Mehta C, Liu L. 2016. An objective re-evaluation of adaptive sample size re?estimation: commentary on ‘Twenty-five years of confirmatory adaptive designs’. Statistics in Medicine. 35: 350-358. [Ref.]
  19. Proschan MA, Hunsberge SA. 1995. Designed extension of studies based on conditional power. Biometrics. 1315-1324. [Ref.]
  20. Müller HH, Schäfer H. 2001. Adaptive group sequential designs for clinical trials: combining the advantages of adaptive and of classical group sequential approaches. Biometrics, 57: 886-891. [Ref.]
  21. Denne JS. 2001. Sample size recalculation using conditional power. Statistics in medicine. 20: 2645-2660. [Ref.]
  22. Gaffney M, Ware JH. 2017. An evaluation of increasing sample size based on conditional power. Journal of Biopharmaceutical Statistics. 1-11. [Ref.]
  23. Tsiatis AA, Mehta C. 2003. On the inefficiency of the adaptive design for monitoring clinical trials. Biometrika. 90: 367-378. [Ref.]
  24. Chen YH, DeMets DL, Gordon Lan KK. 2004. Increasing the sample size when the unblinded interim result is promising. Statistics in Medicine. 23: 1023-1038. [Ref.]
  25. Gao P, Ware JH, Mehta C. 2008. Sample size re-estimation for adaptive sequential design in clinical trials. Journal of Biopharmaceutical Statistics. 18: 1184-1196. [Ref.]
  26. Mehta CR, Pocock SJ. 2011. Adaptive increase in sample size when interim results are promising: a practical guide with examples. Statistics in Medicine. 30: 3267-3284. [Ref.]
  27. Jennison C, Turnbull BW. 2015. Adaptive sample size modification in clinical trials: start small then ask for more?. Statistics in medicine. 34: 3793-3810. [Ref.]
  28. Hsiao ST, Liu L, Mehta CR. 2018. Optimal promising zone designs. Biometrical Journal. [Ref.]
  29. Emerson SS, Levin GP, Emerson SC. 2011. Comments on ‘Adaptive increase in sample size when interim results are promising: A practical guide with examples’. Statistics in Medicine, 30: 3285-3301. [Ref.]
  30. Bauer P, Koenig F. 2006. The reassessment of trial perspectives from interim data—a critical view. Statistics in medicine. 25: 23-36. [Ref.]
  31. Shih WJ, Li G, Wang Y. 2016. Methods for flexible sample-size design in clinical trials: Likelihood, weighted, dual test, and promising zone approaches. Contemporary Clinical Trials. 47: 40-48. [Ref.]
  32. Levin GP, Emerson SC, Emerson SS. 2013. Adaptive clinical trial designs with pre-specified rules for modifying the sample size: understanding efficient types of adaptation. Statistics in Medicine, 32: 1259-1275. [Ref.]

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