A small n sequential multiple assignment randomized trial design for use in rare disease research

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• 作者：Roy N. Tamura^a ; ^{roy.tamura@epi.usf.edu" class="auth_mail" title="E-mail the corresponding author} ; Jeffrey P. Krischer^a ; ^{jeffrey.krischer@epi.usf.edu" class="auth_mail" title="E-mail the corresponding author} ; Christian Pagnoux^b ; ^{Cpagnoux@mtsinia.on.ca" class="auth_mail" title="E-mail the corresponding author} ; Robert Micheletti^c ; ^{Robert.Micheletti@uphs.upenn.edu" class="auth_mail" title="E-mail the corresponding author} ; Peter C. Grayson^d ; ^{peter.grayson@nih.gov" class="auth_mail" title="E-mail the corresponding author} ; Yeh-Fong Chen^e ; ^{YehFong.Chen@fda.hhs.gov" class="auth_mail" title="E-mail the corresponding author} ; Peter A. Merkel^f ; ^{Peter.Merkel@uphs.upenn.edu" class="auth_mail" title="E-mail the corresponding author}
• 关键词：Re-randomization ; Binary data ; Weighted Z statistic
• 刊名：Contemporary Clinical Trials
• 出版年：2016
• 出版时间：January 2016
• 年：2016
• 卷：46
• 期：Complete
• 页码：48-51
• 全文大小：241 K

文摘

Clinical trials in rare diseases are difficult to conduct due to the limited number of patients available with each disorder. We developed a Phase 2 trial which is a small n sequential multiple assignment randomized trial (snSMART) design to test several treatments for a rare disease for which no standard therapy exists.

Purpose

This paper illustrates the design, sample size estimation and operating characteristics of an snSMART.

Methods

We investigate the performance of a class of weighted Z statistics via computer simulations.

Results

We demonstrate the increase in power over traditional single stage designs, and indicate how the power changes as a function of the weight given to each stage.

Conclusion

The snSMART design is promising in a rare disease setting where several alternative treatments are under consideration and small sample sizes are necessary.