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A Novel Framework for Bayesian Response-Adaptive Randomization

  • Jian ZhuEmail author
  • Ina Jazić
  • Yi Liu
Conference paper
Part of the Springer Proceedings in Mathematics & Statistics book series (PROMS, volume 218)

Abstract

The development of response-adaptive randomization (RAR) has taken many different paths over the past few decades. Some RAR schemes optimize certain criteria, but may be complicated and often rely on asymptotic arguments, which may not be suitable in trials with small sample sizes. Some Bayesian RAR schemes are very intuitive and easy to implement, but may not always be tailored toward the study goals. To bridge the gap between these methods, we proposed a framework in which easy-to-implement Bayesian RAR schemes can be derived to target the study goals. We showed that the popular Bayesian RAR scheme that assigns more patients to better performing arms fits in the new framework given a specific intention. We also illustrated the new framework in the setting where multiple treatment arms are compared to a concurrent control arm. Through simulation, we demonstrated that the RAR schemes developed under the new framework outperform a popular method in achieving the pre-specified study goals.

Keywords

Response-adaptive randomization Bayesian adaptive design Goal function Multi-arm comparative trials 

References

  1. 1.
    Barker, A.D., Sigman, C.C., Kelloff, G.J., Hylton, N.M., Berry, D.A., Esserman, L.J.: I-SPY 2: an adaptive breast cancer trial design in the setting of neoadjuvant chemotherapy. Clin. Pharmacolology Ther. 86(1), 97–100 (2009)CrossRefGoogle Scholar
  2. 2.
    Berry, D.A., Eick, S.G.: Adaptive assignment versus balanced randomization in clinical trials, a decision analysis. Stat. Med. 14, 231–246 (1995)CrossRefGoogle Scholar
  3. 3.
    Berry, D.A.: Adaptive clinical trials in oncology. Nat. Rev. Clin. Oncol. 9, 199–207 (2012)CrossRefGoogle Scholar
  4. 4.
    Bleck, T., Cock, H., Chamberlain, J., Cloyd, J., Connor, J., Elm, J., Fountain, N., Jones, E., Lowenstein, D., Shinnar, S., Silbergleit, R., Treiman, D., Trinka, E., Kapur, J.: The established status epilepticus trial 2013. Epilepsia 54, 89–92 (2013)CrossRefGoogle Scholar
  5. 5.
    Cheng, Y., Berry, D.A.: Optimal adaptive randomized designs for clinical trials. Biometrika 94, 673–689 (2007)MathSciNetCrossRefGoogle Scholar
  6. 6.
    Collins, S.P., Lindsell, C.J., Pang, P.S., Storrow, A.B., Peacock, W.F., Levy, P., Rahbar, M.H., Del Junco, D., Gheorghiade, M., Berry, D.A: Bayesian adaptive trial design in acute heart failure syndromes: moving beyond the mega trial. Am. Hear. J. 164, 138-145 (2012)CrossRefGoogle Scholar
  7. 7.
    Connor, J.T., Luce, B.R., Broglio, K.R., Ishak, K.J., Mullins, C.D., Vanness, D.J., Fleurence, R., Saunders, E., Davis, B.R.: Do Bayesian adaptive trials offer advantages for comparative effectiveness research? Protocol for the RE-ADAPT study. Clin. Trials 10, 807–827 (2013)CrossRefGoogle Scholar
  8. 8.
    Eisele, J.: The doubly adaptive biased coin design for sequential clinical trials. J. Stat. Plan. Inference 38, 249–261 (1994)MathSciNetCrossRefGoogle Scholar
  9. 9.
    Fiore, L.D., Brophy, M., Ferguson, R.E., D’Avolio, L., Hermos, J.A., Lewa, R.A., Doros, G., Conrada, C.H., O’Neil, J.A., Sabina, T.P., Kaufman, J., Swartz, S.L., Lawler, E., Lianga, M.H., Gaziano, M., Lavori, P.W.: A point-of-care clinical trial comparing insulin administered using a sliding scale versus a weight-based regimen. Clin. Trials 8, 183–195 (2011)CrossRefGoogle Scholar
  10. 10.
    Gallo, P., Chuang-Stein, C., Dragalin, V., Gaydos, B., Krams, M., Pinheiro, J.: PhRMA Working Group: adaptive designs in clinical drug development–an executive summary of the PhRMA Working Group. J. Biopharm. Stat. 16, 275–283 (2006)CrossRefGoogle Scholar
  11. 11.
    Genovese, M.C., Lee, E., Satterwhite, J., Veenhuizen, M., Disch, D., Berclaz, P.Y., Myers, S., Sides, G., Benichou, O.: A phase 2 dose-ranging study of subcutaneous tabalumab for the treatment of patients with active rheumatoid arthritis and an inadequate response to methotrexate. Ann. Rheum. Dis. 72(9), 1453–60 (2013)CrossRefGoogle Scholar
  12. 12.
    Hu, F., Rosenberger, W.F.: Optimality, variability, power: evaluating response-adaptive randomization procedures for treatment comparisons. J. Am. Stat. Assoc. 98, 671–678 (2003)CrossRefGoogle Scholar
  13. 13.
    Hu, F., Zhang, L.X.: Asymptotic properties of doubly adaptive biased coin designs for multi-treatment clinical trials. Ann. Stat. 32, 268–301 (2004)zbMATHGoogle Scholar
  14. 14.
    Hu, F., Rosenberger, W.F.: The Theory of Response-adaptive Randomization in Clinical Trials. Wiley, Hoboken, NJ (2006)CrossRefGoogle Scholar
  15. 15.
    Kim, E.S., Herbst, R.S., Wistuba, I.I., Lee, J.J., Blumenschein Jr., G.R., Tsao, A., Stewart, D.J., Hicks, M.E., Erasmus Jr., J., Gupta, S., Alden, C.M., Liu, S., Tang, X., Khuri, F.R., Tran, H.T., Johnson, B.E., Heymach, J.V., Mao, L., Fossella, F., Kies, M.S., Papadimitrakopoulou, V., Davis, S.E., Lippman, S.M., Hong, W.K.: The BATTLE trial: personalizing therapy for lung cancer. Cancer Discov. 1, 44–53 (2011)CrossRefGoogle Scholar
  16. 16.
    Komaki, F., Biswas, A.: Bayesian optimal response-adaptive design for binary responses using stopping rule. Stat. Methods Med. Res. (2016).  https://doi.org/10.1177/0962280216647210CrossRefGoogle Scholar
  17. 17.
    Krams, M., Lees, K.R., Hacke, W., Grieve, A.P., Orgogozo, J.M., Ford, G.A.: Acute stroke therapy by inhibition of neutrophils (ASTIN): an adaptive dose-response study of UK-279,276 in acute ischemic stroke. Stroke 34, 2543–2548 (2003)CrossRefGoogle Scholar
  18. 18.
    Lenz, R.A., Pritchett, Y.L., Berry, S.M., Llano, D.A., Han, S., Berry, D.A., Sadowsky, C.H., Abi-Saab, W.M., Saltarelli, M.D.: Adaptive, dose-finding phase 2 trial evaluating the safety and efficacy of ABT-089 in mild to moderate Alzheimer disease. Alzheimer Dis. Assoc. Disord. 29, 192–199 (2015)CrossRefGoogle Scholar
  19. 19.
    Lewis, R.J., Viele, K., Broglio, K., Berry, S.M., Jones, A.E.: An adaptive, phase II, dose-finding clinical trial design to evaluate L-carnitine in the treatment of septic shock based on efficacy and predictive probability of subsequent phase III success. Crit. Care Med. 41(7), 1674–1678 (2013)CrossRefGoogle Scholar
  20. 20.
    Lin, J., Bunn, V.: Comparison of multi-arm multi-stage design and adaptive randomization in platform clinical trials. Contemp. Clin. Trials 54, 48–59 (2017)CrossRefGoogle Scholar
  21. 21.
    Luce, B.R., Connor, J.T., Broglio, K.R., Mullins, C.D., Ishak, K.J., Saunders, E., Davis, B.R.: Using Bayesian adaptive trial designs for comparative effectiveness research: a virtual trial execution. Ann. Med. 165(6), 431–438 (2016)Google Scholar
  22. 22.
    Parmar, S., Andersson, B.S., Couriel, D., Munsell, M.F., Fernandez-Vina, M., Jones, R.B., Shpall, E.J., Popat, U., Anderlini, P., Giralt, S., Alousi, A., Cano, P., Bosque, D., Hosing, C., Silva Lde, P., Westmoreland, M., Wathen, J.K., Berry, D., Champlin, R.E., de Lima, M.J.: Prophylaxis of graft-versus-host disease in unrelated donor transplantation with pentostatin, tacrolimus, and mini-methotrexate: a phase I/II controlled, adaptively randomized study. J. Clin. Oncol. 29(3), 294–302 (2011)CrossRefGoogle Scholar
  23. 23.
    Popescu, I., Fleshner, P.R., Pezzullo, J.C., Charlton, P.A., Kosutic, G., Senagore, A.J.: The ghrelin agonist TZP-101 for management of postoperative ileus after partial colectomy: a randomized, dose-ranging, placebo-controlled clinical trial. Dis. Colon Rectum 53, 126–134 (2010)CrossRefGoogle Scholar
  24. 24.
    Rosenberger, W.F., Stallard, N., Ivanova, A., Harper, C.N., Ricks, M.L.: Optimal adaptive designs for binary response trials. Biometrics 57(3), 909–913 (2001)MathSciNetCrossRefGoogle Scholar
  25. 25.
    Rosenberger, W.F., Sverdlov, O., Hu, F.: Adaptive randomization for clinical trials. J. Biopharm. Stat. 22(4), 719–736 (2012)MathSciNetCrossRefGoogle Scholar
  26. 26.
    Skrivanek, Z., Gaydos, B.L., Chien, J.Y., Geiger, M.J., Heathman, M.A., Berry, S., Anderson, H., Forst, T., Milicevic, Z., Berry, D.: Dose-finding results in an adaptive, seamless, randomized trial of once-weekly dulaglutide combined with metformin in type 2 diabetes patients (AWARD-5). Diabetes Obes. Metab. 16, 748–756 (2014)CrossRefGoogle Scholar
  27. 27.
    Thall, P.F., Wathen, J.K.: Practical Bayesian adaptive randomization in clinical trials. Eur. J. Cancer 43, 859–866 (2007)CrossRefGoogle Scholar
  28. 28.
    Thall, P.F., Fox, P.S., Wathen, J.K.: Statistical controversies in clinical research: scientific and ethical problems with adaptive randomization in comparative clinical trials. Ann. Oncol. 26(8), 1621–1628 (2015)CrossRefGoogle Scholar
  29. 29.
    Thompson, W.R.: On the likelihood that one unknown probability exceeds another in view of the evidence of two samples. Biometrika 25, 275–294 (1933)CrossRefGoogle Scholar
  30. 30.
    Tymofyeyev, Y., Rosenberger, W.F., Hu, F.: Implementing optimal allocation in sequential binary response experiments. J. Am. Stat. Assoc. 102, 224–234 (2007)MathSciNetCrossRefGoogle Scholar
  31. 31.
    Villar, S.S., Wason, J., Bowden, J.: Response-adaptive randomization for multi-arm clinical trials using the forward looking Gittins index rule. Biometrics 71, 969–978 (2015)MathSciNetCrossRefGoogle Scholar
  32. 32.
    Wathen, J.K., Thall, P.F.: A simulation study of outcome adaptive randomization in multi-arm clinical trials. Clin. Trials 14(5), 432–440 (2017)CrossRefGoogle Scholar
  33. 33.
    Wei, L.J., Durham, S.: The randomized play-the-winner rule in medical trials. J. Am. Stat. Assoc. 73, 840–843 (1978)CrossRefGoogle Scholar
  34. 34.
    Yin, G., Chen, N., Lee, J.J.: Phase II trial design with Bayesian adaptive randomization and predictive probability. J. R. Stat. Soc. Ser. C 61(2), 219–235 (2012)MathSciNetCrossRefGoogle Scholar
  35. 35.
    Zang, Y., Lee, J.J.: Adaptive clinical trial designs in oncology. Chin. Clin. Oncol. 3(4), 49 (2014)Google Scholar
  36. 36.
    Zelen, M.: Play the winner rule and the controlled clinical trial. J. Am. Stat. Assoc. 64, 131–146 (1969)MathSciNetCrossRefGoogle Scholar
  37. 37.
    Zhu, H., Hu, F.: Sequential monitoring of response-adaptive randomized clinical trials. Ann. Stat. 38, 2218–2241 (2010)MathSciNetCrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Global StatisticsTakeda Pharmaceutical Company LimitedTokyoJapan
  2. 2.Department of Biostatistics, T.H. Chan School of Public HealthHarvard UniversityCambridgeUSA
  3. 3.Takeda PharmaceuticalCambridgeUSA

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