Quality of Life Research

, Volume 22, Issue 9, pp 2461–2475 | Cite as

Comparative responsiveness and minimal change of the Knee Quality of Life 26-item (KQoL-26) questionnaire

  • Ling-Hsiang Chuang
  • Andrew Garratt
  • Stephen Brealey
Article
First Online:
Accepted:

Abstract

Objectives

To assess the responsiveness of the KQoL-26 and demonstrate minimal change for this instrument in two different samples of patients with suspected internal derangement of the knee.

Methods

Data were collected from two surveys conducted alongside a clinical trial: the arthroscopy sample and the general practitioner (GP) sample. The effect size (ES) was used to assess responsiveness. Anchor-based minimal change included minimal clinical important difference (MCID) and receiver operator characteristic curves; standardized error of measurement and minimal detectable change (MDC) was employed for distribution-based approaches. The KQoL-26 results are compared with those for the Lysholm Knee Score, EQ-5D and SF-36.

Results

The arthroscopy sample consisted of 121 participants and the GP sample of 218 participants at baseline. The largest ES was found for the KQoL-26 emotional functioning scale in both samples. The results were in favour of the condition-specific instrument. The MCID for KQoL-26 physical functioning, activities limitations and emotional functioning scales were 3, 15 and 18, respectively, in the arthroscopy sample; they were 11, 16 and 24 in the GP sample. The MDC 95 % was estimated as 18, 28 and 34, and 15, 24 and 30 in each sample, respectively.

Conclusions

The KQoL-26 emotional functional scale was the most responsive of all scales. It is recommended that an instrument such as the KQoL-26 that includes emotional functioning should be included rather than the Lysholm in future clinical trials of patients with suspected internal derangement of the knee.

Keywords

Knee Quality of Life 26-item questionnaire KQoL-26 Responsiveness Minimal change Effect size Minimal clinical important difference Minimal detectable change Receiver operator characteristic curves Standardized error of measurement 
This is a preview of subscription content, log in to check access.

Notes

Acknowledgments

We thank the patients who took part in this study and the Medical Research Council for funding. We also thank members of the DAMASK Trial Team who collaborated with the authors in the design and conduct of the surveys.

Conflict of interest

The authors declare that they have no conflicts of interest.

References

  1. 1.
    Garratt, A. M., Schmidt, L., Mackintosh, A., & Fitzpatrick, R. (2002). Quality of life measurement: Bibliographic study of patient assessed health outcome measures. British Medical Journal, 324, 1417–1419.PubMedCrossRefGoogle Scholar
  2. 2.
    U.S. Department of Health and Human Services Food and Drug Administration (2009). Guidance for industry patient-reported outcome measures: Use in medical product development to support labeling claims.Google Scholar
  3. 3.
    National Institute for Health and Clinical Excellence. (2008). Guide to the methods of technology appraisal. London, UK: National Institute for Health and Clinical Excellence.Google Scholar
  4. 4.
    Garratt, A. M., Brealey, S., & Gillespie, W. (2004). Patient-assessed health instruments for the knee: A structured review. Rheumatology (Oxford), 43, 1414–1423.CrossRefGoogle Scholar
  5. 5.
    Irrgang, J. J., Anderson, A. F., Boland, A. L., et al. (2001). Development and validation of the international keen documentation committee subjective knee form. American Journal of Sport Medicine, 29, 600–613.Google Scholar
  6. 6.
    Roos, E. M., Roos, H. P., Lohmander, L. S., Ekdahl, C., & Beynnon, B. D. (1998). Knee injuries and osteoarthritis outcome score (KOOS)—development of a self-administered outcome measure. Journal of Orthopedic and Sports Physical Therapy, 78, 88–96.CrossRefGoogle Scholar
  7. 7.
    Fitzpatrick, R., Davey, C., Buxton, M. J., & Jones, D. R. (1998). Evaluation patient-based outcome measures for use in clinical trials. Health Technology Assessment, 2(14), 1–14.PubMedGoogle Scholar
  8. 8.
    Garratt, A. M., Brealey, S., Robling, M., et al. (2008). Development of the knee quality of life (KQoL-26) 26-item questionnaire: Data quality, reliability, validity and responsiveness. Health and Quality of Life Outcomes, 6, 48–59.PubMedCrossRefGoogle Scholar
  9. 9.
    Hay, R., & Hadorn, D. (1992). Responsiveness to change: An aspect of validity, not a separate dimension. Quality of Life Research, 1, 73–75.CrossRefGoogle Scholar
  10. 10.
    Fayers, P. M., & Machin, D. (2000). Quality of life: Assessment, analysis and interpretation. Chichester: Wiley.Google Scholar
  11. 11.
    Guyatt, G. H., Osoba, D., et al. (2002). Methods to explain the clinical significance of health status measures. Mayo Clinic Proceedings, 77(4), 371–383.PubMedCrossRefGoogle Scholar
  12. 12.
    Revicki, D., Hays, R. D., Cella, D., & Sloan, J. (2007). Recommended methods for determining responsiveness and minimally important differences for patient-reported outcome. Journal of Clinical Epidemiology, 61, 102–109.PubMedCrossRefGoogle Scholar
  13. 13.
    Lysholm, J., & Gillquist, J. (1982). Evaluation of knee ligament surgery results with special emphasis on use of a scoring scale. American Journal of Sports Medicine, 10, 150–154.PubMedCrossRefGoogle Scholar
  14. 14.
    Brook, R. (1996). EuroQol: The current state of play. Health Policy, 37, 53–72.CrossRefGoogle Scholar
  15. 15.
    Ware, J. E., & Sherbourne, C. D. (1992). The SF-36 short-form health status survey 1, conceptual framework and item selection. Medical Care, 30, 473–483.PubMedCrossRefGoogle Scholar
  16. 16.
    Brealey, S. D., Atwell, C., Bryan, S., et al. (2006). The DAMASK trial protocol: A pragmatic randomised trial to evaluate whether GPs should have direct access to MRI for patients with suspected internal derangement of the knee. BMC Health Services Research, 6, 133.PubMedCrossRefGoogle Scholar
  17. 17.
    Briggs, K., Lysholm, J., Tegner, Y., Rodkey, W. G., Kocher, M. S., & Steadman, J. R. (2009). The reliability, validity, and responsiveness of the Lysholm Score and Tegner activity scale for anterior cruciate ligament injuries of the KNEE: 25 year later. American Journal of Sports Medicine, 37, 890–897.PubMedCrossRefGoogle Scholar
  18. 18.
    Dolan, P. (1997). Modeling valuations for EuroQol health states. Medical Care, 35(11), 1095–1108.PubMedCrossRefGoogle Scholar
  19. 19.
    Ware, J., Kosinski, M., & Keller, S. D. (1994). SF-36 Physical and mental health survey scale: A user’s manual. Boston, MA: The Health Institute, New England Medical Center.Google Scholar
  20. 20.
    Juniper, E. F., Guyatt, G. H., Willan, A., & Griffith, L. E. (1994). Determining a minimal important change in a disease-specific quality of life questionnaire. Journal of Clinical Epidemiology, 47, 81–87.PubMedCrossRefGoogle Scholar
  21. 21.
    StataCorp. (2008). Stata statistical software: Release 10.1. College Station (TX): Stata Corporation.Google Scholar
  22. 22.
    SPSS Inc. (2010). SPSS statistical software 17.0. Chicago (IL): SPSS Inc.Google Scholar
  23. 23.
    Cohen, J. (1997). Statistical power analysis for the behavioural sciences. New York: Academic Press.Google Scholar
  24. 24.
    Deyo, R. A., & Centor, R. M. (1986). Assessing the responsiveness of functional scales to clinical change: An analogy to diagnostic test performance. Journal of Chronic Diseases, 39, 897–906.PubMedCrossRefGoogle Scholar
  25. 25.
    Wyrwich, K., Nienaber, N., Tierney, W., & Wolinsky, F. (1999). Linking clinical relevant and statistical significant in evaluating intra-individual changes in health-related quality of life. Medical Care, 37, 469–478.PubMedCrossRefGoogle Scholar
  26. 26.
    Dawson, J., Doll, H., Boller, I., Fitzpatrick, R., Little, C., Rees, J., et al. (2008). Comparative responsiveness and minimal change for the Oxford Elbow Score following surgery. Quality of Life Research, 17(10), 1257–1267.PubMedCrossRefGoogle Scholar
  27. 27.
    Middel, B., Goudriaan, H., de Greef, M., et al. (2006). Recall bias did not affect perceived magnitude of changes in health-related functional status. Journal of Clinical Epidemiology, 59, 503–511.PubMedCrossRefGoogle Scholar
  28. 28.
    Terwee, C. B., Roorda, L. D., Dekker, J., et al. (2010). Mind the MIC: Large variation among populations and methods. Journal of Clinical Epidemiology, 63(5), 524–534.PubMedCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  • Ling-Hsiang Chuang
    • 1
  • Andrew Garratt
    • 2
  • Stephen Brealey
    • 1
  1. 1.York Trials Unit, Department of Health SciencesYorkUK
  2. 2.Norwegian Knowledge Centre for the Health ServicesOsloNorway

Personalised recommendations