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

Roy N Tamura; Jeffrey P Krischer; Christian Pagnoux; Robert Micheletti; Peter C Grayson; Yeh-Fong Chen; Peter A Merkel

doi:10.1016/j.cct.2015.11.010

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

Contemp Clin Trials. 2016 Jan:46:48-51. doi: 10.1016/j.cct.2015.11.010. Epub 2015 Nov 14.

Authors

Roy N Tamura¹, Jeffrey P Krischer², Christian Pagnoux³, Robert Micheletti⁴, Peter C Grayson⁵, Yeh-Fong Chen⁶, Peter A Merkel⁷

Affiliations

¹ Health Informatics Institute, University of South Florida, Tampa, FL, United States. Electronic address: roy.tamura@epi.usf.edu.
² Health Informatics Institute, University of South Florida, Tampa, FL, United States. Electronic address: jeffrey.krischer@epi.usf.edu.
³ Department of Rheumatology, University of Toronto, Canada. Electronic address: Cpagnoux@mtsinia.on.ca.
⁴ Departments of Dermatology and Medicine, University of Pennsylvania, Philadelphia, PA, United States. Electronic address: Robert.Micheletti@uphs.upenn.edu.
⁵ Systemic Autoimmunity Branch, National Institute of Arthritis and Musculoskeletal Diseases, Bethesda, MD, United States. Electronic address: peter.grayson@nih.gov.
⁶ Division of Biometrics 3, Office of Biostatistics, US Food and Drug Administration, Silver Spring, MD, United States. Electronic address: YehFong.Chen@fda.hhs.gov.
⁷ Division of Rheumatology, University of Pennsylvania, Philadelphia, PA, United States. Electronic address: Peter.Merkel@uphs.upenn.edu.

Abstract

Background: 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.

Keywords: Binary data; Re-randomization; Weighted Z statistic.

Publication types

Research Support, N.I.H., Extramural

MeSH terms

Clinical Trials, Phase II as Topic*
Computer Simulation*
Humans
Randomized Controlled Trials as Topic / methods*
Rare Diseases*
Sample Size*
Statistics as Topic / methods*

Abstract

Publication types

MeSH terms

Grants and funding