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The use of Bayesian hierarchical models for adaptive randomization in biomarker-driven phase II studies.

Publication ,  Journal Article
Barry, WT; Perou, CM; Marcom, PK; Carey, LA; Ibrahim, JG
Published in: J Biopharm Stat
2015

The role of biomarkers has increased in cancer clinical trials such that novel designs are needed to efficiently answer questions of both drug effects and biomarker performance. We advocate Bayesian hierarchical models for response-adaptive randomized phase II studies integrating single or multiple biomarkers. Prior selection allows one to control a gradual and seamless transition from randomized-blocks to marker-enrichment during the trial. Adaptive randomization is an efficient design for evaluating treatment efficacy within biomarker subgroups, with less variable final sample sizes when compared to nested staged designs. Inference based on the Bayesian hierarchical model also has improved performance in identifying the sub-population where therapeutics are effective over independent analyses done within each biomarker subgroup.

Duke Scholars

Published In

J Biopharm Stat

DOI

EISSN

1520-5711

Publication Date

2015

Volume

25

Issue

1

Start / End Page

66 / 88

Location

England

Related Subject Headings

  • Treatment Outcome
  • Statistics & Probability
  • Sample Size
  • Randomized Controlled Trials as Topic
  • Random Allocation
  • Predictive Value of Tests
  • Neoplasms
  • Models, Statistical
  • Humans
  • Computer Simulation
 

Citation

APA
Chicago
ICMJE
MLA
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Barry, W. T., Perou, C. M., Marcom, P. K., Carey, L. A., & Ibrahim, J. G. (2015). The use of Bayesian hierarchical models for adaptive randomization in biomarker-driven phase II studies. J Biopharm Stat, 25(1), 66–88. https://doi.org/10.1080/10543406.2014.919933
Barry, William T., Charles M. Perou, P Kelly Marcom, Lisa A. Carey, and Joseph G. Ibrahim. “The use of Bayesian hierarchical models for adaptive randomization in biomarker-driven phase II studies.J Biopharm Stat 25, no. 1 (2015): 66–88. https://doi.org/10.1080/10543406.2014.919933.
Barry WT, Perou CM, Marcom PK, Carey LA, Ibrahim JG. The use of Bayesian hierarchical models for adaptive randomization in biomarker-driven phase II studies. J Biopharm Stat. 2015;25(1):66–88.
Barry, William T., et al. “The use of Bayesian hierarchical models for adaptive randomization in biomarker-driven phase II studies.J Biopharm Stat, vol. 25, no. 1, 2015, pp. 66–88. Pubmed, doi:10.1080/10543406.2014.919933.
Barry WT, Perou CM, Marcom PK, Carey LA, Ibrahim JG. The use of Bayesian hierarchical models for adaptive randomization in biomarker-driven phase II studies. J Biopharm Stat. 2015;25(1):66–88.

Published In

J Biopharm Stat

DOI

EISSN

1520-5711

Publication Date

2015

Volume

25

Issue

1

Start / End Page

66 / 88

Location

England

Related Subject Headings

  • Treatment Outcome
  • Statistics & Probability
  • Sample Size
  • Randomized Controlled Trials as Topic
  • Random Allocation
  • Predictive Value of Tests
  • Neoplasms
  • Models, Statistical
  • Humans
  • Computer Simulation