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Data in longitudinal randomised controlled trials in cancer pain: is there any loss of the information available in the data? Results of a systematic literature review and guideline for reporting

Overview of attention for article published in BMC Cancer, October 2016
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Title
Data in longitudinal randomised controlled trials in cancer pain: is there any loss of the information available in the data? Results of a systematic literature review and guideline for reporting
Published in
BMC Cancer, October 2016
DOI 10.1186/s12885-016-2818-8
Pubmed ID
Authors

Odile Sauzet, Maren Kleine, John E. Williams

Abstract

Given the prevalence of untreated pain among cancer patients, there have been calls for more and better research in the domain. Increasingly, calls for less waste and more optimal use of trial data collected are being made. Waste of data includes non-optimal statistical analysis and non-presentation of interpretable effect size as a measure of effectiveness of an intervention which also enable comparisons across studies. We reviewed the recent literature on randomised trials on longitudinal cancer pain to identify sources of loss of data information by collecting material on the nature of outcomes collected, analysed, the method of analysis and what was presented as a result of the trial. Illustrated with real data, we propose some guidelines on how to adequately analyse longitudinal data and report the results using mixed models. We identified some major source of data information loss, one of which is the transformation of a continuous pain outcome. Not adjusting for the collected outcome baseline value is moreover a source of bias. Multiple testing by analysing the data cross-sectionnally at each time-point leads to loss of information and power. Finally, effect sizes reflecting the effectiveness of the intervention were never reported. We identified several sources of information loss in the way longitudinal trials on pain were analysed and reported. However these problems could be easily solved by using regression methods like mixed models and presenting regression parameters to provide a concrete quantitative effect of the intervention.

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The data shown below were collected from the profiles of 2 X users 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 24 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 24 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 5 21%
Researcher 3 13%
Student > Ph. D. Student 3 13%
Professor 2 8%
Lecturer > Senior Lecturer 1 4%
Other 0 0%
Unknown 10 42%
Readers by discipline Count As %
Medicine and Dentistry 6 25%
Nursing and Health Professions 2 8%
Psychology 2 8%
Veterinary Science and Veterinary Medicine 1 4%
Business, Management and Accounting 1 4%
Other 2 8%
Unknown 10 42%
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 30 September 2017.
All research outputs
#17,818,042
of 22,890,496 outputs
Outputs from BMC Cancer
#4,983
of 8,328 outputs
Outputs of similar age
#228,469
of 319,894 outputs
Outputs of similar age from BMC Cancer
#77
of 152 outputs
Altmetric has tracked 22,890,496 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 8,328 research outputs from this source. They receive a mean Attention Score of 4.3. This one is in the 34th percentile – i.e., 34% of its peers scored the same or lower than it.
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