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Journal of the National Cancer Institute Advance Access originally published online on October 30, 2007
JNCI Journal of the National Cancer Institute 2007 99(21):1577-1582; doi:10.1093/jnci/djm185
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© The Author 2007. Published by Oxford University Press.

COMMENTARY

Statistical Methods for Analyzing Sequentially Randomized Trials

Oliver Bembom, Mark J. van der Laan

Affiliation of authors: Division of Biostatistics, University of California at Berkeley, Berkeley, CA

Correspondence to: Mark J. van der Laan, PhD, Division of Biostatistics, School of Public Health, University of California at Berkeley, Earl Warren Hall #7360, Berkeley, CA 94720-7360 (e-mail: laan{at}stat.berkeley.edu).

In this issue of the Journal, Thall et al. present the results of a clinical trial that makes use of sequential randomization, a novel trial design that allows the investigator to study adaptive treatment strategies. Our aim is to complement this groundbreaking work by reviewing the current state of the art of statistical methods available for such analyses. Using the data collected by Thall et al. as an example, we focus on two different approaches for estimating the success rates of different adaptive treatment strategies of interest. By emphasizing the intuitive appeal and straightforward implementation of these methods and illustrating the striking findings to which these methods can lead, we hope to convince the reader that this novel trial design provides a rich source of information that is made readily accessible through current analytical approaches.

Manuscript received July 9, 2007; revised August 23, 2007; accepted September 10, 2007.


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