Title |
Bayesian designs of phase II oncology trials to select maximum effective dose assuming monotonic dose-response relationship
|
---|---|
Published in |
BMC Medical Research Methodology, July 2014
|
DOI | 10.1186/1471-2288-14-95 |
Pubmed ID | |
Authors |
Beibei Guo, Yisheng Li |
Abstract |
For many molecularly targeted agents, the probability of response may be assumed to either increase or increase and then plateau in the tested dose range. Therefore, identifying the maximum effective dose, defined as the lowest dose that achieves a pre-specified target response and beyond which improvement in the response is unlikely, becomes increasingly important. Recently, a class of Bayesian designs for single-arm phase II clinical trials based on hypothesis tests and nonlocal alternative prior densities has been proposed and shown to outperform common Bayesian designs based on posterior credible intervals and common frequentist designs. We extend this and related approaches to the design of phase II oncology trials, with the goal of identifying the maximum effective dose among a small number of pre-specified doses. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
Venezuela, Bolivarian Republic of | 1 | 100% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Scientists | 1 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 1 | 8% |
Unknown | 12 | 92% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 5 | 38% |
Researcher | 4 | 31% |
Student > Master | 1 | 8% |
Unknown | 3 | 23% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 3 | 23% |
Medicine and Dentistry | 3 | 23% |
Social Sciences | 1 | 8% |
Unknown | 6 | 46% |