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Adaptive Clinical Trials: Overview of Phase III Designs and Challenges

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Abstract

Adaptive designs use accruing data to make changes in an ongoing trial according to a prespecified plan and potentially offer great efficiencies for clinical development. There are many types of adaptive designs and many trial aspects that could in theory be adapted. However, the scope of adaptive designs with relevance in confirmatory trials is narrower, and in addition, extensive pre-planning is needed and various types of challenges need to be addressed in order to use these designs in this stage of development. Nevertheless, with careful planning, there are opportunities for these designs to offer important benefits even in the confirmatory stage of development. We provide an overview of adaptive designs that have relevance for confirmatory trials and discuss considerations that may affect whether they should or should not be used in particular trials or programs as well as the challenges that need to be addressed.

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References

  1. Tessella and Berry Consultants. The Fixed and Adaptive Clinical Trial Simulator User Guide. Newton, MA: Tessella and Berry Consultants; 2012.

    Google Scholar 

  2. Aptiv Solutions. ADDPLAN 6.0 User Manual. Cologne, Germany: Aptiv Solutions; 2011.

    Google Scholar 

  3. Cytel. East 5.0 User Manual. Cambridge, MA: Cytel; 2011.

    Google Scholar 

  4. O’Brien PC, Fleming TR. A multiple testing procedure for clinical trials. Biometrics. 1979;35:549–556.

    Article  PubMed  Google Scholar 

  5. Pocock SJ. Group sequential methods in the design and analysis of clinical trials. Biometrika. 1977;64:191–199.

    Article  Google Scholar 

  6. Lan KKG, DeMets DL. Discrete sequential boundaries for clinical trials. Biometrika. 1983;70:659–663.

    Article  Google Scholar 

  7. Bauer P, Köhne K. Evaluation of experiments with adaptive interim analyses. Biometrics. 1994;50:1029–1041.

    Article  CAS  PubMed  Google Scholar 

  8. Lehmacher W, Wassmer G. Adaptive sample size calculations in group sequential trials. Biometrics. 1999;55:1286–1290.

    Article  CAS  PubMed  Google Scholar 

  9. Posch M, König F, Branson M, Brannath W, Dunger-Baldauf C, Bauer P. Testing and estimation in flexible group sequential designs with adaptive treatment selection. Stat Med. 2005;24:3697–3714.

    Article  PubMed  Google Scholar 

  10. Bretz F, Koenig F, Brannath W, Glimm E, Posch M. Adaptive designs for confirmatory clinical trials. Stat Med. 2009;28:1181–1217.

    Article  PubMed  Google Scholar 

  11. Bebu I, Luta G, Dragalin V. Likelihood inference for a two-stage design with treatment selection. Biom J. 2010;52:811–822.

    Article  PubMed  Google Scholar 

  12. Bowden J, Glimm E. Unbiased estimation of selected treatment means in two-stage trials. Biom J. 2008;50:515–527.

    Article  PubMed  Google Scholar 

  13. Carreras M, Brannath W. Shrinkage estimation in two-stage adaptive designs with mid-trial treatment selection. Stat Med. 2013;32:1677–1690.

    Article  PubMed  Google Scholar 

  14. Wu S, Wang W, Yang M. Interval estimation for drop-the-losers designs. Biometrika. 2010;97:406–418.

    Article  Google Scholar 

  15. Kieser M, Friede T. Simple procedures for blinded sample size adjustment that do not affect the type I error rate. Stat Med. 2003;22:3571–3581.

    Article  PubMed  Google Scholar 

  16. Cui L, Hung HMJ, Wang SJ. Modification of sample size in group sequential trials. Biometrics. 1999;55:853–857.

    Article  CAS  PubMed  Google Scholar 

  17. Proschan MA, Hunsberger SA. Designed extension of studies based on conditional power. Biometrics. 1995;51:1315–1324.

    Article  CAS  PubMed  Google Scholar 

  18. Chen YH, DeMets DL, Lan KK. Increasing the sample size when the unblinded interim result is promising. Stat Med. 2004;23:1023–1038.

    Article  PubMed  Google Scholar 

  19. Mehta CR, Pocock SJ. Adaptive increase in sample size when interim results are promising: a practical guide with examples. Stat Med. 2011;30:3267–3284.

    Article  PubMed  Google Scholar 

  20. Jennison C, Turnbull BW. Mid-course sample size modification in clinical trials based on the observed treatment effect. Stat Med. 2003;22:971–993.

    Article  PubMed  Google Scholar 

  21. Tsiatis AA, Mehta CR. On the inefficiency of the adaptive design for monitoring clinical trials. Biometrika. 2003;90:367–378.

    Article  Google Scholar 

  22. Maca J, Bhattacharya S, Dragalin V, et al. Adaptive seamless phase II/III designs—background, operational aspects, and examples. Drug Inf J. 2006;4:463–473.

    Article  Google Scholar 

  23. Bretz F, Schmidli H, König F, Racine A, Maurer W. Confirmatory seamless phase II/III clinical trials with hypotheses selection at interim: general concepts. Biom J. 2006;48(4):623–634.

    Article  PubMed  Google Scholar 

  24. Barnes P, Pocock S, Magnussen H, et al. Integrating indacaterol dose selection in a clinical study in COPD using an adaptive seamless design. Pulm Pharmacol Ther. 2010;23:165–171.

    Article  CAS  PubMed  Google Scholar 

  25. Brannath W, Zuber E, Branson M, et al. Confirmatory adaptive designs with Bayesian decision tools for a targeted therapy in oncology. Stat Med. 2009;28:1445–1463.

    Article  PubMed  Google Scholar 

  26. Temple R. Enrichment designs: efficiency in development of cancer treatments. J Clin Oncol. 2005;23:4838–4839.

    Article  PubMed  Google Scholar 

  27. Simon R. An agenda for clinical trials in the genomic era. Clin Trials. 2004;1:468–470.

    Article  PubMed  Google Scholar 

  28. Maitournam A, Simon R. On the efficiency of targeted clinical trials. Stat Med. 2005;24:329–339.

    Article  CAS  PubMed  Google Scholar 

  29. Friedlin B, Simon R. An evaluation of randomized discontinuation design. J Clin Oncol. 2005;23:5094–5098.

    Article  Google Scholar 

  30. Bauer P, Kieser M. Combining different phases in the development of medical treatments within a single trial. Stat Med. 1999;18:1833–1848.

    Article  CAS  PubMed  Google Scholar 

  31. Wang SJ, O’Neill R, Hung J. Approaches to evaluation of treatment effect in randomized clinical trials with genomic subset. Pharm Statist. 2007;6:227–244.

    Article  Google Scholar 

  32. Wang SJ, Hung HMJ, O’Neill RT. Adaptive patient enrichment designs in therapeutic trials. Biom J. 2009;51:358–374.

    Article  PubMed  Google Scholar 

  33. Wassmer G. On sample size determination in multi-armed confirmatory adaptive designs. J Biopharm Stat. 2011;21:802–817.

    Article  PubMed  Google Scholar 

  34. Jenkins M, Stone A, Jennison C. An adaptive seamless phase II/III design for oncology trials with subpopulation selection using correlated survival endpoints. Pharm Statist. 2011;10:347–356.

    Article  Google Scholar 

  35. Friede T, Parsons N, Stallard N. A conditional error function approach for subgroup selection in adaptive clinical trials. Stat Med. 2012;31:4309–4320.

    Article  CAS  PubMed  Google Scholar 

  36. Wassmer G, Dragalin V. Designing issues in confirmatory adaptive population enrichment trials. Stat Med. 2013; to be published.

  37. Mehta C, Gao P, Bhatt DL, Harrington RA, Skerjanec S, Ware JH. Optimizing trial design: sequential, adaptive, and enrichment strategies. Circulation. 2009;119:597–605.

    Article  PubMed  Google Scholar 

  38. Mehta C, Gao P. Population enrichment designs: case study of a large multinational trial. J Biopharm Stat. 2011;21:831–845.

    Article  PubMed  Google Scholar 

  39. Tournoux-Facon C, De Ryckee Y, Tubert-Bitter P. How a new stratified adaptive phase II design could improve targeting population. Stat Med. 2011;30:1555–1562.

    Article  PubMed  Google Scholar 

  40. Tournoux-Facon C, De Ryckee Y, Tubert-Bitter P. Targeting population entering phase III trials: a new stratified adaptive phase II design. Stat Med. 2011;30:801–811.

    Article  PubMed  Google Scholar 

  41. Food and Drug Administration. Enrichment Strategies for Clinical Trials to Support Approval of Human Drugs and Biological Products. Rockville, MD: Food and Drug Administration; 2012.

    Google Scholar 

  42. Gaydos B, Anderson K, Berry D, et al. Good practices for adaptive clinical trials in pharmaceutical product development. Drug Inf J. 2009;43:539–556.

    Article  Google Scholar 

  43. Committee for Medicinal Products for Human Use. Reflection Paper on Methodological Issues in Confirmatory Clinical Trials Planned with an Adaptive Design. London, UK: European Medicines Agency; 2007.

    Google Scholar 

  44. Food and Drug Administration. Guidance for Industry for Adaptive Clinical Trials for Drugs and Biologics. Rockville, MD: Food and Drug Administration; 2010.

    Google Scholar 

  45. Food and Drug Administration. Establishment and Operation of Clinical Trial Data Monitoring Committees. Rockville, MD: Food and Drug Administration; 2006.

    Google Scholar 

  46. Gallo P. Confidentiality and trial integrity issues for adaptive designs. Drug Inf J. 2006;40:445–450.

    Article  Google Scholar 

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Author information

Authors and Affiliations

  1. Center for Statistics in Drug Development, Quintiles Inc, 5927 South Miami Boulevard, Morrisville, NC, 27560, USA

    Jeff Maca PhD

  2. Aptiv Solutions, Durham, NC, USA

    Vladimir Dragalin PhD

  3. Statistical Methodology, Novartis Pharmaceuticals, East Hanover, NJ, USA

    Paul Gallo PhD

Authors
  1. Jeff Maca PhD
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  2. Vladimir Dragalin PhD
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  3. Paul Gallo PhD
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Correspondence to Jeff Maca PhD.

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Maca, J., Dragalin, V. & Gallo, P. Adaptive Clinical Trials: Overview of Phase III Designs and Challenges. Ther Innov Regul Sci 48, 31–40 (2014). https://doi.org/10.1177/2168479013507436

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  • DOI: https://doi.org/10.1177/2168479013507436

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