↓ Skip to main content

Bayesian designs of phase II oncology trials to select maximum effective dose assuming monotonic dose-response relationship

Overview of attention for article published in BMC Medical Research Methodology, July 2014
Altmetric Badge

Mentioned by

twitter
1 X user

Citations

dimensions_citation
4 Dimensions

Readers on

mendeley
13 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
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

X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 13 Mendeley readers of this research output. Click here to see the associated Mendeley record.

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%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 07 August 2014.
All research outputs
#18,375,478
of 22,759,618 outputs
Outputs from BMC Medical Research Methodology
#1,733
of 2,009 outputs
Outputs of similar age
#163,347
of 228,918 outputs
Outputs of similar age from BMC Medical Research Methodology
#21
of 23 outputs
Altmetric has tracked 22,759,618 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,009 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.2. This one is in the 6th percentile – i.e., 6% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 228,918 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 15th percentile – i.e., 15% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 23 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.