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The Pursuit of Balance Using Stratified and Dynamic Randomization Techniques: An Overview

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Abstract

Many pharmaceutical industry trials seek to achieve a balanced allocation of treatments over prognostic factors, including center. Much of the literature has discussed the merits of this from the viewpoint of statistical efficiency. This motivation is discussed and evaluated for trials of varying sizes with particular reference to multicenter trials. It is concluded that statistical efficiency for the primary analysis variable will rarely be the main reason for seeking balance and other often more important reasons are outlined. Randomization and dynamic allocation techniques to achieve balance are described and evaluated; these are Zelen’s method, stratified permuted blocks randomization, minimization, urn designs, and optimal allocation techniques. Practical considerations arising from experience with using the techniques are described. Criteria which the practitioner can use to judge which is the most appropriate technique for his particular trial are given; these are balance, predictability, power, implications for analysis, and implications for medication supply. System requirements for the implementation of these techniques are described.

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References

  1. International Conference un Harmonisation. Guidance on Statistical Principles Tor Clinical Trials. Federal Register. International Confer-ence on Harmonisation; E-9 Document. 1998: Vol.63, 179:49583–49598.

    Google Scholar 

  2. Kernan WN, Viscoli CM, Makuch RW, Brass LM, Horwitz RI. Stratified randomization for clinical tri-als. J Clin Epidemiol. 1999:52(1): 19–26.

    Article  CAS  PubMed  Google Scholar 

  3. Schulz KF, Grimes DA. Allocation concealment in randomised trials: defending against deciphering. Lancet. 2002:359:614–618.

    Article  PubMed  Google Scholar 

  4. Grizzle JE. A note on stratifying versus complete random assignment in clinical trials. Control Clin Trials. 1982:3:365–368.

    Article  CAS  PubMed  Google Scholar 

  5. Palta M, Amini SB. Magnitude and likelihood of loss resulting from non-stratified randomization. Stat Med. 1982:1:267–275.

    Article  CAS  PubMed  Google Scholar 

  6. Palla M. Investigating maximum power losses in survival studies with nonstratified randomization. Biometrics. 1985:41:497–504.

    Article  Google Scholar 

  7. Peto R, Pike MG, Armitage P et al. Design and analysis of randomized clinical trials requiring prolonged observation of each subject. Br J Can-cer. 1976:34:585.

    Article  CAS  Google Scholar 

  8. Simon R. Restricted randomization designs in clinical trials. Biometrics. 1979;35:503–512.

    Article  CAS  PubMed  Google Scholar 

  9. Atkinson AC. Optimum biased-coin designs for sequential treatment allocation with covariate information. Stat Med. 1999:18:1741–1752.

    Article  CAS  PubMed  Google Scholar 

  10. McHugh R, Matts J, Post-stratification in the ran-domized clinical trial. Biometries. 1983:39:217–225.

    Article  CAS  Google Scholar 

  11. Green SB, Byar DP. The effect of stratified ran-domization on size and power of statistical tests in clinical trials. J Chron Dis. 1978:31:445–454.

    Article  CAS  PubMed  Google Scholar 

  12. Pocock SJ, Simon R, Sequential treatment assign-ment with balancing for prognostic factors in the controlled clinical trial. Biometrics. 1975:31:103–115.

    Article  CAS  PubMed  Google Scholar 

  13. Signorini DF, Leung O, Simes RJ, Beller E, Gebski VJ. Dynamic balanced randomization for clinical trials. Stat Med. 1993:12:2343–2350.

    Article  CAS  PubMed  Google Scholar 

  14. Wei LJ, Lachin JM. Properties of the urn random-ization in clinical trials. Control Clin Trials. 1988:9:345–364.

    Article  CAS  PubMed  Google Scholar 

  15. Tu D, Shalay K, Pater J, Adjustment of treatment effect for covartales in clinical trials: statistical and regulatory issues. Drug Inf J. 2000:34:511–523.

    Article  Google Scholar 

  16. Lachin JM, Matts JP, Wei LJ. Randomization in clinical trials: conclusions and recommendations. Control Clin Trials, 1988:9:365–374.

    Article  CAS  PubMed  Google Scholar 

  17. Schulz KF, Grimes DA. Generation of allocation sequences in randomised trials: chance, not choice. Lancet 2002:359:515–519.

    Article  PubMed  Google Scholar 

  18. Atkinson A. Beyond the platinum standard; ran-domisation and balancing covartales in sequential multi-center trials. Henry Stewart Conference on Statistics of Multi-center Trials. January 25, 2002. London.

    Google Scholar 

  19. Cox DR. Randomization and concomitant variables in the design of experinents. In: Kallianpur G, Krishnaiah PR, Ghosh JK eds. Statistics and Probability: Essaya in Honor of Rao CR. Amsterdam, Holland: North Holland Publishing Company: 1982:197–202.

    Google Scholar 

  20. Assman SF, Pocock SJ, Enos LE, Kasten LE. Sub-group analysis and other (mis)uses of baseline data in clinical trials. Lancet. 2000:355:1064–1069.

    Article  Google Scholar 

  21. Cui L, Hung MMJ, Wang SJ, Tsong Y, Issues relat-ing to subgroup analysis in clinical trials. J Biopbarm Stat. 2002:12:347–358

    Article  Google Scholar 

  22. Zelen M. The randomization and stratification of subjects to clinical trials. J Chronic Disease. 1974:27:365–375.

    Article  CAS  Google Scholar 

  23. Lachin J. Statistical properties of randomization in clinical trials. Control Clin Trials. 1988:9:289–311.

    Article  CAS  PubMed  Google Scholar 

  24. Simon R. Patient subsets and variation in thera-peutic efficacy. Br J Clin Pharmacol. 1982:14:473–482.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Hallstrom AI, Davis K, Imbalance in treatment as-signments in stratified blocked randomization. Control Clin Trials. 1988:9:375–382.

    Article  CAS  PubMed  Google Scholar 

  26. Schulz KE, Grimes DA. Unequal group sizes in randomised trials: guarding against guessing. Lancet. 2002:359:966–970.

    Article  PubMed  Google Scholar 

  27. Taves DR. Minimization: a new method of assign-ing subjects to treatment and control groups. Clin Pharmacol Therapeut. 1974:15:443–453.

    Article  CAS  Google Scholar 

  28. ISIS-3 Collaborative group. A randomised com-parison of streptokinase vs. tissue plasinogen ac-tivator vs. anistraplase and of aspirin plus heparin vs. aspirin alone among 41299 cases of suspected acute myocardial infarction. Lancet. 1992:339:753–770.

    Article  Google Scholar 

  29. ISIS-4 Collaborative Group. 1S1S-4: A randomized factorial trial assessing early oral captopril, oral mononitrate, and intravenous magnesium sulphate in 58050 subjects with suspected myocardial infarction. Lancet. 1995:349:1413–1421.

    Google Scholar 

  30. Scott NW, McPherson GC, Ramsay CR, Campbell MK. The method of minimization for allocation to clinical trials: a review. Control Clin Trials. 2002:23:662–674.

    Article  PubMed  Google Scholar 

  31. Freedman LS, While SJ. On the use of Pocock and Simon’s method for balancing treatment numbers over prognostic factors in the controlled clinical trial. Biometrics. 1976:32:691–694.

    Article  CAS  PubMed  Google Scholar 

  32. Zielhuis GA, Straatman H, van’t Hof-Grootenboer AE, [van Lier HJ, Rach GH, van den Broek P. The choice of a balanced allocation method for a clinical trial in otitis media with effusion. Stat Med. 1990:9:237–246.

    Article  CAS  PubMed  Google Scholar 

  33. Begg CB, Iglewicz B, A treatment allocation pro-cedure for sequential clinical trials. Biometrics. 1980:36:81–90.

    Article  CAS  PubMed  Google Scholar 

  34. Therneau TM. How many stratification factors are ‘too many’ to use in a randomization plan. Control Clin Trials. 1993:14:98–108.

    Article  CAS  PubMed  Google Scholar 

  35. Reed JV, Wickham EA. Practical experience of minimization in clinical trials. Pharmaceut Med. 1988:3:349–359.

    Google Scholar 

  36. Chen M-G. IVRS, In: Chow S-C, ed. Encyclopedia of Biopharmaceutical Statistics. New York, NY: Marcel Dekker; 2000:280–287

    Google Scholar 

  37. Frane JW. A method of biased coin randomizalion, its implementation, and its validation. Drug Inf J. 1998:32:423–432.

    Article  Google Scholar 

  38. Akazawa K, Odaka T, Sakamoto M, Ohtsuki S, Shimada M, Kamakura T, Nose Y, A random allocation system with the minimization method for multi-institutional clinical trials. J Med Systems. 1991:15(4):311–319.

    Article  CAS  Google Scholar 

  39. Altman DG, Schulz KF, Moher D et al. The revised CONSORT statement for reporting randomized trials: explanation and elaboration. Ann int Med. 2001:134:663–694

    Article  CAS  PubMed  Google Scholar 

  40. Weir CJ, Lees KR. Comparison of stratification and adaptive methods for treatment allocation in an acute stroke clinical trial. Stat Med. 2003:22:705–726.

    Article  PubMed  Google Scholar 

  41. Wei LJ. An application ofan urn model to the design of sequential controlled clinical trials. J Am Stat Assoc. 1978:73:559–563.

    Article  Google Scholar 

  42. Schouten HJ. Adaptive biased urn randomization in small strata when blinding is impossible. Bio-metrics. 1995:51:1529–1535.

    CAS  Google Scholar 

  43. Atkinson AC. Optimum biased coin design for se-quential clinical trial with prognostic factors. Biometrika. 1982:69:61–67.

    Article  Google Scholar 

  44. Cook RD, Weisberg S. Residuals and Influence in Regression. New York, NY: Chapman and Hall; 1982:210.

    Google Scholar 

  45. Dror S, Faraggi D, Reiser B, Dynamic treatment allocation adjusting for prognostic factors for more than two treatments. Biometrics. 1995:51:1338–1343.

    Article  CAS  PubMed  Google Scholar 

  46. Rovers MM, Straatman H, Zeilhaus GA, Ingels K, van der Wilt G-J. Using a balancing procedure in multicenter clinical trials: simulation of patient allocation based on a trial of ventilation tubes for otitis media with effusion in patients. Int J Tech-nol Assess Health Care. 2000:16:276–280.

    Article  CAS  Google Scholar 

  47. Efron B, Forcing a sequential experiment to be balanced. Biomctrika. 1971:58:403–417.

    Article  Google Scholar 

  48. Quinaux E, Buyse M, Choosing an optimal treatment allocation method in randomised clinical trials (poster). Presented at the Drug Information Association Annual Meeting. Chicago, IL, 2001.

    Google Scholar 

  49. Ebbutt A, Kay R, McNamara J, Engler J, The analy-sis of trials using a minimization algorithm. In: 20th Anniversary Conference Report. Macclesfield, England: PSI; 1998:12–14.

    Google Scholar 

  50. Ohashi Y. Randomization in cancer clinical trials: permutation test and development of a computer program. Environmental Health Perspectives. 1990:87:13–17.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Kalish LA, Begg CB. The impact of treatment allo-cation procedures on nominal significance levels and bias. Conlrol Clin Trials. 1987:8:121–135.

    Article  CAS  Google Scholar 

  52. Dowlman N. Intelligent medication manage-ment—using IVR to optimise the drug supply process, Pharma Manufactur Pack Sourcer. 2001:Summer;24–28.

    Google Scholar 

  53. Dowlman N. The cost benefits of using 1VR sys-tems in the supply chain. Pharma Manufactur Pack Sourcer. 2001;Autumn:74–79.

    Google Scholar 

  54. Byrom B. Using IVRS in clinical trial management. Appl Clin Trials. 2002:10:36–42.

    Google Scholar 

  55. Food and Drug Adminstration. 21 CFR Part 11. Electronic Records; Electronic Signatures. Federal Register. 1997; Vol. 62. 54:13430–13466.

    Google Scholar 

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  1. Statistics Group, ClinPhone Lt., Lady Bay House, Meadow Grove, Nottingham, NG2 3HF, UK

    Damian J. McEntegart MSc

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  1. Damian J. McEntegart MSc
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Correspondence to Damian J. McEntegart MSc.

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McEntegart, D.J. The Pursuit of Balance Using Stratified and Dynamic Randomization Techniques: An Overview. Ther Innov Regul Sci 37, 293–308 (2003). https://doi.org/10.1177/009286150303700305

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