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Mapping CHU9D Utility Scores from the PedsQLTM 4.0 SF-15

Overview of attention for article published in PharmacoEconomics, December 2016
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Title
Mapping CHU9D Utility Scores from the PedsQLTM 4.0 SF-15
Published in
PharmacoEconomics, December 2016
DOI 10.1007/s40273-016-0476-y
Pubmed ID
Authors

Christine Mpundu-Kaambwa, Gang Chen, Remo Russo, Katherine Stevens, Karin Dam Petersen, Julie Ratcliffe

Abstract

The Pediatric Quality of Life Inventory™ 4.0 Short Form 15 Generic Core Scales (hereafter the PedsQL) and the Child Health Utility-9 Dimensions (CHU9D) are two generic instruments designed to measure health-related quality of life in children and adolescents in the general population and paediatric patient groups living with specific health conditions. Although the PedsQL is widely used among paediatric patient populations, presently it is not possible to directly use the scores from the instrument to calculate quality-adjusted life-years (QALYs) for application in economic evaluation because it produces summary scores which are not preference-based. This paper examines different econometric mapping techniques for estimating CHU9D utility scores from the PedsQL for the purpose of calculating QALYs for cost-utility analysis. The PedsQL and the CHU9D were completed by a community sample of 755 Australian adolescents aged 15-17 years. Seven regression models were estimated: ordinary least squares estimator, generalised linear model, robust MM estimator, multivariate factorial polynomial estimator, beta-binomial estimator, finite mixture model and multinomial logistic model. The mean absolute error (MAE) and the mean squared error (MSE) were used to assess predictive ability of the models. The MM estimator with stepwise-selected PedsQL dimension scores as explanatory variables had the best predictive accuracy using MAE and the equivalent beta-binomial model had the best predictive accuracy using MSE. Our mapping algorithm facilitates the estimation of health-state utilities for use within economic evaluations where only PedsQL data is available and is suitable for use in community-based adolescents aged 15-17 years. Applicability of the algorithm in younger populations should be assessed in further research.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 38 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 38 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 5 13%
Researcher 4 11%
Student > Bachelor 4 11%
Other 3 8%
Librarian 2 5%
Other 6 16%
Unknown 14 37%
Readers by discipline Count As %
Medicine and Dentistry 8 21%
Nursing and Health Professions 4 11%
Economics, Econometrics and Finance 4 11%
Business, Management and Accounting 2 5%
Engineering 2 5%
Other 6 16%
Unknown 12 32%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 16 September 2017.
All research outputs
#14,875,637
of 22,908,162 outputs
Outputs from PharmacoEconomics
#1,459
of 1,817 outputs
Outputs of similar age
#240,598
of 419,655 outputs
Outputs of similar age from PharmacoEconomics
#19
of 28 outputs
Altmetric has tracked 22,908,162 research outputs across all sources so far. This one is in the 33rd percentile – i.e., 33% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,817 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.7. This one is in the 18th percentile – i.e., 18% 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 419,655 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 39th percentile – i.e., 39% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 28 others from the same source and published within six weeks on either side of this one. This one is in the 32nd percentile – i.e., 32% of its contemporaries scored the same or lower than it.