Comparison of Randomized Clinical Trial Designs for Targeted Agents

ISRN Oncology ◽  
2012 ◽  
Vol 2012 ◽  
pp. 1-6
Author(s):  
Laura Finn ◽  
Winston Tan

No single therapy benefits the majority of patients in the practice of oncology as responses differ even among patients with similar tumor types. The variety of response to therapy witnessed while treating our patients supports the concept of personalized medicine using patients' genomic and biologic information and their clinical characteristics to make informed decisions about their treatment. Personalized medicine relies on identification and confirmation of biologic targets and development of agents to target them. These targeted agents tend to focus on subsets of patients and provide improved clinical outcomes. The continued success of personalized medicine will depend on the expedited development of new agents from proof of concept to confirmation of clinical efficacy.


2002 ◽  
Vol 16 (5) ◽  
pp. 1287-1305 ◽  
Author(s):  
Brigette B.Y Ma ◽  
Carolyn D Britten ◽  
Lillian L Siu

2008 ◽  
Vol 14 (14) ◽  
pp. 4358-4367 ◽  
Author(s):  
Antje Hoering ◽  
Mike LeBlanc ◽  
John J. Crowley

2019 ◽  
pp. 1-9 ◽  
Author(s):  
Mei-Yin C. Polley ◽  
Edward L. Korn ◽  
Boris Freidlin

Recent advances in biotechnology and cancer genomics have afforded enormous opportunities for development of more effective anticancer therapies. A key thrust of this modern drug development paradigm is successful identification of predictive biomarkers that can distinguish patients who might be sensitive to new targeted therapies. To respond to this challenge, a number of phase III cancer trial designs integrating biomarker-based objectives have been proposed and implemented in oncology drug development. In this article, we provide an updated review of commonly used biomarker-based randomized clinical trial designs, with a particular focus on design efficiency. When the efficacy of a new therapy may be limited to a biomarker-defined subgroup, the choice of an appropriate randomized clinical trial design should be guided by the strength of the biomarker’s credentials. If compelling evidence indicates that a targeted therapy is beneficial only in a particular biomarker-defined subgroup, an enrichment design should be used. If there is strong evidence that the treatment is likely to be more beneficial in the biomarker-positive patients but a meaningful benefit is also possible in the biomarker-negative patients, then a properly powered biomarker-stratified design (eg, a subgroup-specific or Marker Sequential Test strategy) would provide the most rigorous determination of the sensitive populations. If the evidence supporting the predictive value of the biomarker is weak and the treatment is expected to work in the overall population, then a fallback design could be used. Careful selection of an appropriate phase III design strategy that integrates evaluation of a new anticancer therapy and its companion diagnostic is critical to the success of precision medicine in oncology.


2002 ◽  
Vol 89 (2) ◽  
pp. 154-157 ◽  
Author(s):  
F. F Palazzo ◽  
D. L Francis ◽  
M. A Clifton

2001 ◽  
Vol 120 (5) ◽  
pp. A453-A453 ◽  
Author(s):  
B SHEN ◽  
J ACHKAR ◽  
B LASHNER ◽  
A ORMSBY ◽  
F REMZI ◽  
...  

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