Skip to main content
Top
Gepubliceerd in:

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

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

Gepubliceerd in: Quality of Life Research | Uitgave 1/2015

Log in om toegang te krijgen
share
DELEN

Deel dit onderdeel of sectie (kopieer de link)

  • Optie A:
    Klik op de rechtermuisknop op de link en selecteer de optie “linkadres kopiëren”
  • Optie B:
    Deel de link per e-mail

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.
Literatuur
1.
go back to reference 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 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
3.
go back to reference 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 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.
go back to reference 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 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.
go back to reference 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 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.
go back to reference 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 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.
go back to reference 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 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.
go back to reference Meredith, W. (1993). Measurement invariance, factor analysis and factorial invariance. Psychometrika, 58(4), 525–543.CrossRef Meredith, W. (1993). Measurement invariance, factor analysis and factorial invariance. Psychometrika, 58(4), 525–543.CrossRef
9.
go back to reference 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 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.
go back to reference 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. 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.
go back to reference Meredith, W., & Teresi, J. A. (2006). An essay on measurement and factorial invariance. Medical Care, 44(11), S69–S77.PubMedCrossRef Meredith, W., & Teresi, J. A. (2006). An essay on measurement and factorial invariance. Medical Care, 44(11), S69–S77.PubMedCrossRef
12.
go back to reference 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 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.
go back to reference 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. 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.
go back to reference Kline, R. B. (2005). Principles and practice of structural equation modeling, 2nd edn. New York: Guilford Press. Kline, R. B. (2005). Principles and practice of structural equation modeling, 2nd edn. New York: Guilford Press.
15.
go back to reference Muthén, L. K., & Muthén, B. O. (2011). MPlus user’s guide, 6th edn. Los Angeles, CA: Muthén & Muthén. Muthén, L. K., & Muthén, B. O. (2011). MPlus user’s guide, 6th edn. Los Angeles, CA: Muthén & Muthén.
17.
go back to reference Fayers, P. M., & Hand, D. J. (1997). Factor analysis, causal indicators and quality of life. Quality of Life Research, 6, 139–150.PubMed Fayers, P. M., & Hand, D. J. (1997). Factor analysis, causal indicators and quality of life. Quality of Life Research, 6, 139–150.PubMed
18.
go back to reference Yu, C.-Y. (2002). Evaluating cutoff criteria of model fit indices for latent variable models with binary and continuous outcomes. University of California. Yu, C.-Y. (2002). Evaluating cutoff criteria of model fit indices for latent variable models with binary and continuous outcomes. University of California.
Metagegevens
Titel
Testing the measurement invariance of the EORTC QLQ-C30 across primary cancer sites using multi-group confirmatory factor analysis
Auteurs
D. S. J. Costa
N. K. Aaronson
P. M. Fayers
J. F. Pallant
G. Velikova
M. T. King
Publicatiedatum
01-01-2015
Uitgeverij
Springer International Publishing
Gepubliceerd in
Quality of Life Research / Uitgave 1/2015
Print ISSN: 0962-9343
Elektronisch ISSN: 1573-2649
DOI
https://doi.org/10.1007/s11136-014-0799-0

Andere artikelen Uitgave 1/2015

Quality of Life Research 1/2015 Naar de uitgave