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Clin Cancer Res. 2018 Feb 15;24(4):730-736. doi: 10.1158/1078-0432.CCR-17-1355. Epub 2017 Aug 23.

Sequential, Multiple Assignment, Randomized Trial Designs in Immuno-oncology Research.

Author information

1
Department of Biostatistics, University of Michigan, School of Public Health, Ann Arbor, Michigan. kidwell@umich.edu.
2
Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, New York.
3
Weill Cornell Medical College, New York, New York.
4
Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, New York.

Abstract

Clinical trials investigating immune checkpoint inhibitors have led to the approval of anti-CTLA-4 (cytotoxic T-lymphocyte antigen-4), anti-PD-1 (programmed death-1), and anti-PD-L1 (PD-ligand 1) drugs by the FDA for numerous tumor types. In the treatment of metastatic melanoma, combinations of checkpoint inhibitors are more effective than single-agent inhibitors, but combination immunotherapy is associated with increased frequency and severity of toxicity. There are questions about the use of combination immunotherapy or single-agent anti-PD-1 as initial therapy and the number of doses of either approach required to sustain a response. In this article, we describe a novel use of sequential, multiple assignment, randomized trial (SMART) design to evaluate immune checkpoint inhibitors to find treatment regimens that adapt within an individual based on intermediate response and lead to the longest overall survival. We provide a hypothetical example SMART design for BRAF wild-type metastatic melanoma as a framework for investigating immunotherapy treatment regimens. We compare implementing a SMART design to implementing multiple traditional randomized clinical trials. We illustrate the benefits of a SMART over traditional trial designs and acknowledge the complexity of a SMART. SMART designs may be an optimal way to find treatment strategies that yield durable response, longer survival, and lower toxicity. Clin Cancer Res; 24(4); 730-6. ©2017 AACR.

PMID:
28835379
PMCID:
PMC5963278
[Available on 2019-02-15]
DOI:
10.1158/1078-0432.CCR-17-1355

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