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Quality of Life Research
Published in: Quality of Life Research 1/2015

01-01-2015 | Quantitative Methods Special Section

Testing the measurement invariance of the EORTC QLQ-C30 across primary cancer sites using multi-group confirmatory factor analysis

Authors: D. S. J. Costa, N. K. Aaronson, P. M. Fayers, J. F. Pallant, G. Velikova, M. T. King

Published in: Quality of Life Research | Issue 1/2015

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Abstract

Purpose

The EORTC Quality of Life Questionnaire is a widely used cancer-specific quality of life instrument comprising a core set of 30 items (QLQ-C30) supplemented by cancer site-specific modules. The purpose of this paper was to examine the extent to which the conventional multi-item domain structure of the QLQ-C30 holds across patients with seven different primary cancer sites.

Methods

Multi-group confirmatory factor analysis was used to test whether a measurement model of the QLQ-C30 was invariant across cancer sites. Configural (same patterns of factor loadings), metric (equivalence of factor loadings) and scalar (equivalence of thresholds) invariance amongst the cancer site groups were assessed (N = 1,906) by comparing the fit of a model with these parameters freely estimated to a model where estimates were constrained to be equal for the corresponding items in each group.

Results

All groups exhibited good model fit except for the prostate group, which was excluded. Only 1 of 576 parameters was found to differ between primary sites: specifically, the first threshold of Item 1 in the breast cancer group exhibited non-invariance. In a post hoc analysis, several instances of non-invariance by treatment status (baseline, on-treatment, off-treatment) were observed.

Conclusions

Given only one instance of non-invariance between cancer sites, there is a reason to be confident in the validity of conclusions drawn when comparing QLQ-C30 domain scores between different sites and when interpreting the scores of heterogeneous samples, although future research should assess the potential impact of confounding variables such as treatment and gender.
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next article Cancer patients’ function, symptoms and supportive care needs: a latent class analysis across cultures

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Literature
1.
Sprangers, M. A. G., et al. (1993). The European Organization for Research and Treatment of Cancer approach to quality of life assessment: guidelines for developing questionnaire modules. Quality of Life Research, 2(4), 287–295.PubMedCrossRef
2.
3.
Bjordal, K., et al. (2000). A 12 country field study of the EORTC QLQ-C30 (version 3.0) and the head and neck cancer specific module (EORTC QLQ-H&N35) in head and neck patients. European Journal of Cancer, 36, 1796–1807.PubMedCrossRef
4.
Aaronson, N. K., et al. (1993). The European Organisation for Research and Treatment of Cancer QLQ-C30: A quality-of-life instrument for use in international clinical trials in oncology. Journal of the National Cancer Institute, 85(5), 365–376.PubMedCrossRef
5.
Scott, N. W., et al. (2006). Comparing translations of the EORTC QLQ-C30 using differential item functioning analyses. Quality of Life Research, 15(6), 1103–1115.PubMedCrossRef
6.
Scott, N. W., et al. (2007). The use of differential item functioning analyses to identify cultural differences in responses to the EORTC QLQ-C30. Quality of Life Research, 16, 115–129.PubMedCrossRef
7.
King-Kallimanis, B. L., et al. (2012). Assessing measurement invariance of a health-related quality-of-life questionnaire in radiotherapy patients. Quality of Life Research, 21(10), 1745–1753.PubMedCentralPubMedCrossRef
8.
Meredith, W. (1993). Measurement invariance, factor analysis and factorial invariance. Psychometrika, 58(4), 525–543.CrossRef
9.
Yoon, M., & Millsap, R. E. (2007). Detecting violations of factorial invariance using data-based specification searches: A Monte Carlo study. Structural Equation Modeling, 14(3), 435–463.CrossRef
10.
Byrne, B. M., Shavelson, R. J., & Muthen, B. (1989). Testing for the equivalence of factor covariance and mean structures: The issue of partial measurement invariance. Psychological Bulletin, 105, 456–466.
11.
Meredith, W., & Teresi, J. A. (2006). An essay on measurement and factorial invariance. Medical Care, 44(11), S69–S77.PubMedCrossRef
12.
Reise, S. P., Widaman, K. F., & Pugh, R. H. (1993). Confirmatory factor analysis and item response theory: Two approaches for exploring measurement invariance. Psychological Bulletin, 114(3), 552–566.PubMedCrossRef
13.
Finney, S. J., & DiStefano, C. (2006). Non-normal and categorical data in structural equation modeling. In G. R. Hancock & R. O. Mueller(Eds.), Structural equation modeling: A second course. Greenwich: Information Age Publishing.
14.
Kline, R. B. (2005). Principles and practice of structural equation modeling, 2nd edn. New York: Guilford Press.
15.
Muthén, L. K., & Muthén, B. O. (2011). MPlus user’s guide, 6th edn. Los Angeles, CA: Muthén & Muthén.
16.
17.
Fayers, P. M., & Hand, D. J. (1997). Factor analysis, causal indicators and quality of life. Quality of Life Research, 6, 139–150.PubMed
18.
Yu, C.-Y. (2002). Evaluating cutoff criteria of model fit indices for latent variable models with binary and continuous outcomes. University of California.
Metadata
Title
Testing the measurement invariance of the EORTC QLQ-C30 across primary cancer sites using multi-group confirmatory factor analysis
Authors
D. S. J. Costa
N. K. Aaronson
P. M. Fayers
J. F. Pallant
G. Velikova
M. T. King
Publication date
01-01-2015
Publisher
Springer International Publishing
Published in
Quality of Life Research / Issue 1/2015
Print ISSN: 0962-9343
Electronic ISSN: 1573-2649
DOI
https://doi.org/10.1007/s11136-014-0799-0

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