SMART designs in cancer research: Past, present, and future

被引:42
作者
Kidwell, Kelley M. [1 ]
机构
[1] Univ Michigan, Dept Biostat, Ann Arbor, MI 48109 USA
关键词
2-STAGE RANDOMIZATION DESIGNS; DYNAMIC TREATMENT REGIMES; ADAPTIVE TREATMENT STRATEGIES; COLONY-STIMULATING FACTOR; HIGH-RISK NEUROBLASTOMA; ACUTE MYELOID-LEUKEMIA; SAMPLE-SIZE; TREATMENT POLICIES; SURVIVAL DISTRIBUTIONS; MAINTENANCE THERAPY;
D O I
10.1177/1740774514525691
中图分类号
R-3 [医学研究方法]; R3 [基础医学];
学科分类号
1001 ;
摘要
Background Cancer affects millions of people worldwide each year. Patients require sequences of treatment based on their response to previous treatments to combat cancer and fight metastases. Physicians provide treatment based on clinical characteristics, changing over time. Guidelines for these individualized sequences of treatments are known as dynamic treatment regimens (DTRs) where the initial treatment and subsequent modifications depend on the response to previous treatments, disease progression, and other patient characteristics or behaviors. To provide evidence-based DTRs, the Sequential Multiple Assignment Randomized Trial (SMART) has emerged over the past few decades. Purpose To examine and learn from past SMARTs investigating cancer treatment options, to discuss potential limitations preventing the widespread use of SMARTs in cancer research, and to describe courses of action to increase the implementation of SMARTs and collaboration between statisticians and clinicians. Conclusion There have been SMARTs investigating treatment questions in areas of cancer, but the novelty and perceived complexity has limited its use. By building bridges between statisticians and clinicians, clarifying research objectives, and furthering methods work, there should be an increase in SMARTs addressing relevant cancer treatment questions. Within any area of cancer, SMARTs develop DTRs that can guide treatment decisions over the disease history and improve patient outcomes.
引用
收藏
页码:445 / 456
页数:12
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