↓ Skip to main content

Estimation of Quality-adjusted Life Years alongside clinical trials: the impact of ‘time-effects’ on trial results

Overview of attention for article published in Journal of Pharmaceutical Health Services Research, February 2018
Altmetric Badge

About this Attention Score

  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
1 X user

Readers on

mendeley
33 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.
Article details
Title
Estimation of Quality-adjusted Life Years alongside clinical trials: the impact of ‘time-effects’ on trial results
Published in
Journal of Pharmaceutical Health Services Research, February 2018
DOI 10.1111/jphs.12218
Pubmed ID
Authors
Abstract

The objectives were to investigate the impact of 'time-effect' on the estimation of quality-adjusted life years (QALYs) along prospective clinical trials' outcomes using an assumed fixed time duration versus the actual time durations for each case. The 'time' duration is the length of time in a health state. Two methods were used in the estimation of QALYs based using EQ-5D 3L scores collected at specific time-point intervals. One method used the actual time durations for each case based on CRF records, and the other used an assumed time duration and globally applied it to all the cases. Using SPSS ® software program, we used paired-sample t-tests to assess whether the 'time-effect' can potentially affect trial results using CONSTRUCT trial data as reported in the trial results publications. The trial compared use of Infliximab with Cyclosporine for patients with Ulcerative Colitis and it involved some 270 participants. The results largely indicate statistically significant differences between the two methods of QALY estimations. QALYs at the respective time-points indicate no statistical difference between the two approaches. However, the difference in terms of total QALYs between the two QALY estimation approaches is statistically significant with considerable impact on costs/QALY. Considering the possible impact of the time-effect on QALY estimations, the result implies that it can have significant implications for resources allocations decisions. In this respect, researchers have to pay due considerations to the approach they use and where possible, actual time durations must be used in QALY estimations along prospective clinical trials.

Login to access the Attention Digest and the Sentiment Analysis related to this output.

Timeline Attention over time Attention Score history
Login to access the full charts related to this output.
Activity
Login to access the full charts related to this output.
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 demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 33 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Login to view Mendeley reader trends over time.

Geographical breakdown

Geographical breakdown
Country Count As %
Unknown 33 100%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Ph. D. Student 4 12%
Student > Master 4 12%
Researcher 4 12%
Student > Postgraduate 4 12%
Student > Doctoral Student 2 6%
Other 6 18%
Unknown 9 27%
Readers by discipline
Readers by discipline Count As %
Medicine and Dentistry 10 30%
Psychology 3 9%
Nursing and Health Professions 2 6%
Economics, Econometrics and Finance 2 6%
Environmental Science 1 3%
Other 6 18%
Unknown 9 27%
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 July 2019.
All research outputs
#22,537,614
of 27,578,965 outputs
Outputs from Journal of Pharmaceutical Health Services Research
#137
of 193 outputs
Outputs of similar age
#274,566
of 348,504 outputs
Outputs of similar age from Journal of Pharmaceutical Health Services Research
#3
of 5 outputs
Altmetric has tracked 27,578,965 research outputs across all sources so far. This one is in the 10th percentile – i.e., 10% of other outputs scored the same or lower than it.
So far Altmetric has tracked 193 research outputs from this source. They receive a mean Attention Score of 3.6. This one is in the 4th percentile – i.e., 4% 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 348,504 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 11th percentile – i.e., 11% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 5 others from the same source and published within six weeks on either side of this one. This one has scored higher than 2 of them.