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Approaches for estimating minimal clinically important differences in systemic lupus erythematosus

Overview of attention for article published in Arthritis Research & Therapy, June 2015
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  • Good Attention Score compared to outputs of the same age (71st percentile)
  • Above-average Attention Score compared to outputs of the same age and source (51st percentile)

Mentioned by

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2 X users
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1 patent
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1 Facebook page

Citations

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187 Dimensions

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232 Mendeley
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Title
Approaches for estimating minimal clinically important differences in systemic lupus erythematosus
Published in
Arthritis Research & Therapy, June 2015
DOI 10.1186/s13075-015-0658-6
Pubmed ID
Authors

Sharan K Rai, Jinoos Yazdany, Paul R Fortin, J Antonio Aviña-Zubieta

Abstract

A minimal clinically important difference (MCID) is an important concept used to determine whether a medical intervention improves perceived outcomes in patients. Prior to the introduction of the concept in 1989, studies focused primarily on statistical significance. As most recent clinical trials in systemic lupus erythematosus (SLE) have failed to show significant effects, determining a clinically relevant threshold for outcome scores (that is, the MCID) of existing instruments may be critical for conducting and interpreting meaningful clinical trials as well as for facilitating the establishment of treatment recommendations for patients. To that effect, methods to determine the MCID can be divided into two well-defined categories: distribution-based and anchor-based approaches. Distribution-based approaches are based on statistical characteristics of the obtained samples. There are various methods within the distribution-based approach, including the standard error of measurement, the standard deviation, the effect size, the minimal detectable change, the reliable change index, and the standardized response mean. Anchor-based approaches compare the change in a patient-reported outcome to a second, external measure of change (that is, one that is more clearly understood, such as a global assessment), which serves as the anchor. Finally, the Delphi technique can be applied as an adjunct to defining a clinically important difference. Despite an abundance of methods reported in the literature, little work in MCID estimation has been done in the context of SLE. As the MCID can help determine the effect of a given therapy on a patient and add meaning to statistical inferences made in clinical research, we believe there ought to be renewed focus on this area. Here, we provide an update on the use of MCIDs in clinical research, review some of the work done in this area in SLE, and propose an agenda for future research.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 232 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Spain 1 <1%
United States 1 <1%
Unknown 230 99%

Demographic breakdown

Readers by professional status Count As %
Researcher 44 19%
Student > Master 31 13%
Student > Ph. D. Student 27 12%
Student > Bachelor 17 7%
Other 16 7%
Other 51 22%
Unknown 46 20%
Readers by discipline Count As %
Medicine and Dentistry 83 36%
Nursing and Health Professions 25 11%
Psychology 14 6%
Neuroscience 10 4%
Engineering 8 3%
Other 29 13%
Unknown 63 27%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 5. 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 19 January 2022.
All research outputs
#7,205,554
of 25,374,917 outputs
Outputs from Arthritis Research & Therapy
#1,485
of 3,381 outputs
Outputs of similar age
#79,508
of 281,105 outputs
Outputs of similar age from Arthritis Research & Therapy
#29
of 60 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. This one has received more attention than most of these and is in the 71st percentile.
So far Altmetric has tracked 3,381 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.2. 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 281,105 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 71% of its contemporaries.
We're also able to compare this research output to 60 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 51% of its contemporaries.