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Interpreting small treatment differences from quality of life data in cancer trials: an alternative measure of treatment benefit and effect size for the EORTC-QLQ-C30

Overview of attention for article published in Health and Quality of Life Outcomes, November 2015
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1 Redditor

Citations

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36 Mendeley
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Title
Interpreting small treatment differences from quality of life data in cancer trials: an alternative measure of treatment benefit and effect size for the EORTC-QLQ-C30
Published in
Health and Quality of Life Outcomes, November 2015
DOI 10.1186/s12955-015-0374-6
Pubmed ID
Authors

Iftekhar Khan, Zahid Bashir, Martin Forster

Abstract

The EORTC-QLQ-C30 is a widely used health related quality of life (HRQoL) questionnaire in lung cancer patients. Small HRQoL treatment effects are often reported as mean differences (MDs) between treatments, which are rarely justified or understood by patients and clinicians. An alternative approach using odds ratios (OR) for reporting effects is proposed. This may offer advantages including facilitating alignment between patient and clinician understanding of HRQoL effects. Data from six CRUK sponsored randomized controlled lung cancer trials (2 small cell and 4 in non-small cell, in 2909 patients) were used to HRQoL effects. Results from Beta-Binomial (BB) standard mixed effects were compared. Preferences for ORs vs MDs were determined and Time to Deterioration (TD) was also compared. HRQoL effects using ORs offered coherent interpretations: MDs >0 resulted in ORs >1 and vice versa; effect sizes were classified as 'Trivial' if the OR was between 1 ± 0.05 (i.e. 0.95 to 1.05); 'Small': for 1 ± 0.1; 'Medium': 1 ± 0.2 and 'Large': OR <0.8 or >1.20. Small HRQoL effects on the MD scale may translate to important treatment differences on the OR scale: for example, a worsening in symptoms (MD) by 2.6 points (p = 0.1314) would be a 17 % deterioration (p < 0.0001) with an OR. Hence important differences may be missed with MD; conversely, small ORs are unlikely to yield large MDs because methods based on OR model skewed data well. Initial evidence also suggests oncologists prefer ORs over MDs since interpretation is similar to hazard ratios. Reporting HRQoL benefits as MDs can be misleading. Estimates of HRQoL treatment effects in terms of ORs are preferred over MDs. Future analysis of QLQ-C30 and other HRQoL measures should consider reporting HRQoL treatment effects as ORs.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 36 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 36 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 6 17%
Other 5 14%
Student > Doctoral Student 3 8%
Student > Ph. D. Student 3 8%
Student > Master 2 6%
Other 3 8%
Unknown 14 39%
Readers by discipline Count As %
Medicine and Dentistry 11 31%
Nursing and Health Professions 2 6%
Psychology 2 6%
Agricultural and Biological Sciences 2 6%
Pharmacology, Toxicology and Pharmaceutical Science 1 3%
Other 2 6%
Unknown 16 44%
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 22 November 2015.
All research outputs
#20,296,405
of 22,833,393 outputs
Outputs from Health and Quality of Life Outcomes
#1,972
of 2,158 outputs
Outputs of similar age
#235,706
of 281,504 outputs
Outputs of similar age from Health and Quality of Life Outcomes
#27
of 29 outputs
Altmetric has tracked 22,833,393 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,158 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one is in the 1st percentile – i.e., 1% 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 281,504 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 29 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.