Contemporary Clinical Trials 40 (2015) 240
Contents lists available at ScienceDirect
Contemporary Clinical Trials journal homepage: www.elsevier.com/locate/conclintrial
Letter to the Editor A note on response-adaptive randomization
Keywords: Big stick Maximal procedure Medical ethics Time horizons
for a vaccine that would offer the hope of herd immunity, so that the disease under study might actually be eradicated by the treatment (or vaccine) now under study. In this case, the argument for response-adaptive randomization might be compelling. The same cannot be said for the more typical case, in which it still seems best to use equal randomization, especially if we are diligent in which method of equal randomization we use. The most common method, the permuted blocks design, has been amply discredited [2,3], so better methods, such as the maximal procedure [4], should be used instead.
Editor: Du, Wang, and Lee [1] strike me as entirely correct in both their methods and their results, the most relevant being that equal randomization is preferred to response-adaptive randomization when the number of future patients swamps the number of current patients in the trial. But it seems to me that in all but a (very) few cases, this fact settles the matter. After all, how often would we know that this is not the case? And how would we ascertain this? It is true that even orphan diseases are studied in practice, but in this case the number of patients on the trial would likely be limited to the same degree as the number of future patients would be. The time horizon may be uncertain, as it may extend not indefinitely but, rather, only until a new and improved treatment comes along. But even here, how do we know how long it will be until a new treatment for the same disease not only gets on the market but also supersedes the one currently under study? The most compelling case might be for a treatment that is curative for a disease that is otherwise highly contagious, or
http://dx.doi.org/10.1016/j.cct.2014.12.013 1551-7144/Published by Elsevier Inc.
References [1] Du Y, Wang X, Lee JJ. Simulation study for evaluating the performance of response-adaptive randomization. Contemp Clin Trials 2014;40C:15–25. [2] Berger VW. Selection bias and covariate imbalances in randomized clinical trials. Chichester: John Wiley & Sons; 2005. [3] Berger VW. Do not use blocked randomization. Headache 2006;46(2):343. [4] Berger VW, Ivanova A, Deloria-Knoll M. Minimizing predictability while retaining balance through the use of less restrictive randomization procedures. Stat Med 2003;22(19):3017–28.
Vance W. Berger⁎ National Cancer Institute and University of Maryland Baltimore County, Biometry Research Group, National Cancer Institute, 9609 Medical Center Drive, Rockville, MD 20850, United States ⁎ Tel.: + 1 240 276 7142. E-mail address: [email protected]. 10 December 2014
Contents lists available at ScienceDirect
Contemporary Clinical Trials journal homepage: www.elsevier.com/locate/conclintrial
Letter to the Editor A note on response-adaptive randomization
Keywords: Big stick Maximal procedure Medical ethics Time horizons
for a vaccine that would offer the hope of herd immunity, so that the disease under study might actually be eradicated by the treatment (or vaccine) now under study. In this case, the argument for response-adaptive randomization might be compelling. The same cannot be said for the more typical case, in which it still seems best to use equal randomization, especially if we are diligent in which method of equal randomization we use. The most common method, the permuted blocks design, has been amply discredited [2,3], so better methods, such as the maximal procedure [4], should be used instead.
Editor: Du, Wang, and Lee [1] strike me as entirely correct in both their methods and their results, the most relevant being that equal randomization is preferred to response-adaptive randomization when the number of future patients swamps the number of current patients in the trial. But it seems to me that in all but a (very) few cases, this fact settles the matter. After all, how often would we know that this is not the case? And how would we ascertain this? It is true that even orphan diseases are studied in practice, but in this case the number of patients on the trial would likely be limited to the same degree as the number of future patients would be. The time horizon may be uncertain, as it may extend not indefinitely but, rather, only until a new and improved treatment comes along. But even here, how do we know how long it will be until a new treatment for the same disease not only gets on the market but also supersedes the one currently under study? The most compelling case might be for a treatment that is curative for a disease that is otherwise highly contagious, or
http://dx.doi.org/10.1016/j.cct.2014.12.013 1551-7144/Published by Elsevier Inc.
References [1] Du Y, Wang X, Lee JJ. Simulation study for evaluating the performance of response-adaptive randomization. Contemp Clin Trials 2014;40C:15–25. [2] Berger VW. Selection bias and covariate imbalances in randomized clinical trials. Chichester: John Wiley & Sons; 2005. [3] Berger VW. Do not use blocked randomization. Headache 2006;46(2):343. [4] Berger VW, Ivanova A, Deloria-Knoll M. Minimizing predictability while retaining balance through the use of less restrictive randomization procedures. Stat Med 2003;22(19):3017–28.
Vance W. Berger⁎ National Cancer Institute and University of Maryland Baltimore County, Biometry Research Group, National Cancer Institute, 9609 Medical Center Drive, Rockville, MD 20850, United States ⁎ Tel.: + 1 240 276 7142. E-mail address: [email protected]. 10 December 2014
