Hostname: page-component-586b7cd67f-rcrh6 Total loading time: 0 Render date: 2024-11-28T04:24:22.306Z Has data issue: false hasContentIssue false

WHICH QUALITY OF LIFE MEASURES FIT YOUR RELATIVE EFFECTIVENESS ASSESSMENT?

Published online by Cambridge University Press:  11 June 2015

Irina Cleemput
Affiliation:
Belgian Health Care Knowledge Centre, AC Kruidtuin [email protected]
Mattias Neyt
Affiliation:
Belgian Health Care Knowledge Centre, AC Kruidtuin

Abstract

Background: Health-related quality of life (HRQoL) is an important endpoint of many healthcare interventions. This study develops guidance on how to select appropriate HRQoL measures for inclusion in a clinical trial, given the purposes of the HRQoL measurement.

Methods: The guidance is based on a systematic literature review, discussions with members of the European Network for Health Technology Assessment (EUnetHTA) and two rounds of public consultation.

Results: A set of twelve recommendations was developed, addressing the requirements for HRQoL data for relative effectiveness assessment, for cost-utility analyses and for informing clinical decision making. Recommendations relate to the choice of the type of measure as well as to aspects such as measurement frequency, target population and presentation.

Conclusions: The purpose and context of HRQoL measurement is crucial for the relevance of the data obtained with a specific HRQoL measure. It is recommended to always include a generic HRQoL instrument in clinical trials to cover a wide range of possible future uses of the HRQoL data.

Type
Methods
Copyright
Copyright © Cambridge University Press 2015 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

1. European Medicines Agency. Reflection paper on the regulatory guidance for the use of health-related quality of life (HRQL) measures in the evaluation of medicinal products. London: EMA; 2006:5.Google Scholar
2. Food and Drug Administration. Guidance for industry. Patient-reported outcome measures: Use in medical product development to support labeling claims. Washington, DC: U.S. Department of Health and Human Services; 2009.Google Scholar
3. Goodman, CS. Healthcare technology assessment: Methods, framework, and role in policy making. Am J Manag Care. 1998;4 Spec No:SP200-14.Google Scholar
4. Jackowski, D, Guyatt, G. A guide to health measurement. Clin Orthop Relat Res. 2003:8089.Google Scholar
5. Kleijnen, S, Goettsch, W, d'Andon, A, et al. EUnetHTA JA WP5: Relative Effectiveness Assessment (REA) of pharmaceuticals. Background review. July 2011 (version 5B). Copenhagen: EUnetHTA; 2011.Google Scholar
6. Fitzpatrick, R, Davey, C, Buxton, MJ, Jones, DR. Evaluating patient-based outcome measures for use in clinical trials. Health Technol Assess. 1998;2:i–iv, 174.Google Scholar
7. Guyatt, GH, Feeny, DH, Patrick, DL. Measuring health-related quality of life. Ann Intern Med. 1993;118:622629.Google Scholar
8. Neyt, M. Towards more consistent use of generic quality-of-life instruments. Pharmacoeconomics. 2010;28:345346.Google Scholar
9. Stull, DE, Leidy, NK, Parasuraman, B, Chassany, O. Optimal recall periods for patient-reported outcomes: Challenges and potential solutions. Curr Med Res Opin. 2009;25:929942.Google Scholar
10. Machin, D, Weeden, S. Suggestions for the presentation of quality of life data from clinical trials. Stat Med. 1998;17:711724.Google Scholar
11. Petrillo, J, Cairns, J. Converting condition-specific measures into preference-based outcomes for use in economic evaluation. Expert Rev Pharmacoecon Outcomes Res. 2008;8:453461.Google Scholar
12. Chuang, LH, Kind, P. Converting the SF-12 into the EQ-5D: An empirical comparison of methodologies. Pharmacoeconomics. 2009;27:491505.Google Scholar
13. Wild, D, Eremenco, S, Mear, I, et al. Multinational trials-recommendations on the translations required, approaches to using the same language in different countries, and the approaches to support pooling the data: The ISPOR Patient-Reported Outcomes Translation and Linguistic Validation Good Research Practices Task Force report. Value Health. 2009;12:430440.Google Scholar
14. Ware, JE Jr, Keller, SD, Gandek, B, Brazier, JE, Sullivan, M. Evaluating translations of health status questionnaires. Methods from the IQOLA project. International Quality of Life Assessment. Int J Technol Assess Healthcare. 1995;11:525551.Google Scholar
15. Gao, F, Ng, GY, Cheung, YB, et al. The Singaporean English and Chinese versions of the EQ-5D achieved measurement equivalence in cancer patients. J Clin Epidemiol. 2009;62:206213.Google Scholar
16. Hahn, EA, Bode, RK, Du, H, Cella, D. Evaluating linguistic equivalence of patient-reported outcomes in a cancer clinical trial. Clin Trials. 2006;3:280290.Google Scholar
17. Coons, SJ, Gwaltney, CJ, Hays, RD, et al. Recommendations on evidence needed to support measurement equivalence between electronic and paper-based patient-reported outcome (PRO) measures: ISPOR ePRO Good Research Practices Task Force report. Value Health. 2009;12:419429.Google Scholar
18. Hacker, ED. Technology and quality of life outcomes. Semin Oncol Nurs. 2010;26:4758.Google Scholar
19. Hoedemaekers, R, Dekkers, W. Key concepts in health care priority setting. Health Care Anal. 2003;11:309323.Google Scholar
20. Staquet, M, Berzon, R, Osoba, D, Machin, D. Guidelines for reporting results of quality of life assessments in clinical trials. Qual Life Res. 1996;5:496502.Google Scholar
21. Calvert, MJ, Freemantle, N. Use of health-related quality of life in prescribing research. Part 2: Methodological considerations for the assessment of health-related quality of life in clinical trials. J Clin Pharm Ther. 2004;29:8594.Google Scholar
22. Billingham, LJ, Abrams, KR, Jones, DR. Methods for the analysis of quality-of-life and survival data in health technology assessment. Health Technol Assess. 1999;3:1152.Google Scholar
23. Fayers, PM, Machin, D. Quality of life: Assessment, analysis, and interpretation. Chichester, New York: John Wiley; 2000.Google Scholar
24. Kristensen, F, Sigmund, H. Health technology assessment handbook. Copenhagen: Danish Centre for Health Technology Assessment, National Board of Health; 2007.Google Scholar