↓ Skip to main content

How do researchers determine the difference to be detected in superiority trials? Results of a survey from a panel of researchers

Overview of attention for article published in BMC Medical Research Methodology, July 2016
Altmetric Badge

About this Attention Score

  • Good Attention Score compared to outputs of the same age (70th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (57th percentile)

Mentioned by

twitter
7 tweeters

Citations

dimensions_citation
1 Dimensions

Readers on

mendeley
8 Mendeley
citeulike
1 CiteULike
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
How do researchers determine the difference to be detected in superiority trials? Results of a survey from a panel of researchers
Published in
BMC Medical Research Methodology, July 2016
DOI 10.1186/s12874-016-0195-2
Pubmed ID
Authors

Angèle Gayet-Ageron, Anne-Sophie Jannot, Thomas Agoritsas, Sandrine Rudaz, Christophe Combescure, Thomas Perneger

Abstract

There is currently no guidance for selecting a specific difference to be detected in a superiority trial. We explored 3 factors that in our opinion should influence the difference to be detected (type of outcome, patient age group, and presence of treatment side-effects), and 3 that should not (baseline level of risk, logistical difficulties, and cost of treatment). We conducted an experimental survey using a factorial design among 380 corresponding authors of randomized controlled trials indexed in Medline. Two hypothetical vignettes were submitted to participants: one described a trial of a new analgesic in mild trauma injuries, the other described a trial of a new chemotherapy among cancer patients. The first vignette tested the baseline level of risk, patient age-group, patient recruitment difficulties, and treatment side-effects. The second tested the baseline level of risk, patient age-group, type of outcome, and cost of treatment. The respondents were asked to select the smallest gain of effectiveness that should be detected by the trial. In vignette 1, respondents selected a median difference to be detected corresponding to an improvement of 7.0 % in pain control with the new treatment. In vignette 2, they selected a median difference to be detected corresponding to a reduction of 5.0 % in mortality or cancer recurrence with the new chemotherapy. In both vignettes, the difference to be detected decreased significantly with the baseline risk. The other factor influencing difference to be detected was the age group, but the impact of this factor was smaller. Cost, side-effects, outcome severity, or mention of logistical difficulties did not significantly impact the difference to be detected selected by participants. Three of the anticipated effects conformed to our expectations (the effect of patient age, and absence of effect of the cost of treatment and of patient recruitment difficulties) and the other three did not. These findings can guide future research in determining differences to be detected in trials that can translate to meaningful clinical decision-making.

Twitter Demographics

The data shown below were collected from the profiles of 7 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 8 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 13%
Unknown 7 88%

Demographic breakdown

Readers by professional status Count As %
Researcher 3 38%
Student > Master 2 25%
Professor 1 13%
Student > Ph. D. Student 1 13%
Professor > Associate Professor 1 13%
Other 0 0%
Readers by discipline Count As %
Medicine and Dentistry 4 50%
Psychology 1 13%
Pharmacology, Toxicology and Pharmaceutical Science 1 13%
Decision Sciences 1 13%
Philosophy 1 13%
Other 0 0%

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 11 September 2016.
All research outputs
#3,726,191
of 13,755,459 outputs
Outputs from BMC Medical Research Methodology
#562
of 1,268 outputs
Outputs of similar age
#77,177
of 263,056 outputs
Outputs of similar age from BMC Medical Research Methodology
#3
of 7 outputs
Altmetric has tracked 13,755,459 research outputs across all sources so far. This one has received more attention than most of these and is in the 72nd percentile.
So far Altmetric has tracked 1,268 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.1. This one has gotten more attention than average, scoring higher than 55% of its peers.
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 263,056 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 70% of its contemporaries.
We're also able to compare this research output to 7 others from the same source and published within six weeks on either side of this one. This one has scored higher than 4 of them.