Hostname: page-component-cd9895bd7-8ctnn Total loading time: 0 Render date: 2024-12-23T03:16:39.941Z Has data issue: false hasContentIssue false
  • English
  • Français

DIFFERENTIATION OF HEALTH-RELATED QUALITY OF LIFE OUTCOMES BETWEEN FIVE DISEASE AREAS: RESULTS FROM AN INTERNATIONAL SURVEY OF PATIENTS

Published online by Cambridge University Press:  25 September 2018

Olina Efthymiadou ,
Jean Mossman  and
Panos Kanavos
Olina Efthymiadou
Affiliation:
Medical Technology Research Group, LSE Health, London School of [email protected]
Jean Mossman
Affiliation:
Medical Technology Research Group, LSE Health, London School of Economics
Panos Kanavos
Affiliation:
Department of Social Policy, Medical Technology Research Group, LSE Health
Get access Rights & Permissions [Opens in a new window]

Abstract

Objectives:

Health-related quality of life (HRQoL) data generated by generic, preference-based instruments (i.e., EQ-5D) are highly demanded in health policy decision making, because they allow for direct comparisons of HRQoL outcomes between disease areas. We aimed to quantify HRQoL outcomes in breast cancer (BC), rheumatoid arthritis (RA), multiple sclerosis (MS), rare cancers (RC), and rare disease (RD) patients and understand the patterns that differentiate HRQoL outcomes between these disease areas, and more specifically between rare and more common disease population groups.

Methods:

An international, Web survey of patients measured HRQoL (EQ-5D-5L), self-perceived health (EQ-5D-5L Visual Analogue Scale), and additional QoL dimensions, such as patient disability level.

Results:

We received 675 completed responses. Average utility loss was 53.5 percent, 32.5 percent, and 33.3 percent for RD, RA, and MS patients, respectively, in contrast to 18.6 percent for BC and RC patients. Statistically significant differences (p < .05) were observed between disease groups in all EQ-5D-5L domain outcomes, apart from that of “Anxiety/Depression.” Severe and/or extreme problems were reported in performing usual activities for RD and RC (34 percent and 13 percent of overall problems reported respectively), mobility for MS (18 percent), pain/discomfort for RA (13 percent), and anxiety/depression for BC (7 percent) patients.

Conclusions:

We demonstrated significant differences in the dimensions that drive HRQoL outcomes between rare and more common diseases and showcased that the same EQ-5D utility may reflect very different severities depending on the patient population under investigation. Future research should examine whether outcomes in other, critical HRQoL domains not included in generic measures also highlight significant differences across disease areas.

Keywords

QoL utilitiesPatient preferencesHealth Technology AssessmentEQ-5D-5LRare diseases
Type
Assessment
Information
International Journal of Technology Assessment in Health Care , Volume 34 , Issue 5 , 2018 , pp. 498 - 506
Copyright
Copyright © Cambridge University Press 2018 

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.)

Footnotes

This study was supported by Advance-HTA, a research grant that has received funding from the European Commission, DG Research, 7th Framework Programme for Research (grant agreement No. 305983). The views expressed in this study are those of the authors and do not represent the views of the European Commission, DG Research. We are grateful for the invaluable support of all the European and international patient associations that were invited to participate in the study and voluntarily agreed to share the Web-survey links with their networks of patients. Finally, we are thankful to Hala Hourani, Ansgar Lange, Erica Visintin, and Olivier Wouters for their assistance in translating the survey questionnaires and for providing valuable support in the research process.

References

REFERENCES

1.Schlenk, EA, Erlen, JA, Dunbar-Jacob, J, et al. Health-related quality of life in chronic disorders: A comparison across studies using the MOS SF-36. Qual Life Res. 1998;7:57–65.Google Scholar
2.Global Burden of Disease Cancer Collaboration. The global burden of cancer 2013. JAMA Oncol. 2015;1:505–527.Google Scholar
3.Global Alliance for Musculoskeletal Health. 2010. Influential global alliance calls on governments and the World Health Organisation to prioritise musculoskeletal health following findings of Global Burden of Disease Study. http://bjdonline.org/musculoskeletal-conditions-the-second-greatest-cause-of-disability-2/ (Accessed April 10, 2018).Google Scholar
4.Pfizer, Value of Medicines. Value of medicines for rare diseases. Issued by Global Policy and International Public Affairs. http://www.pfizer.com/files/health/Value_of_Medicine_Rare_Diseases.pdf (Accessed April 22, 2018).Google Scholar
5.Brazier, J, Rowen, D. (2011). NICEDSU technical support document 11: Alternatives to EQ-5D for generating health state utility values. Report By The Decision Support Unit. March 2011. http://www.nicedsu.org.uk/TSD11%20Alternatives%20to%20EQ-5D_final.pdf (Accessed April 6, 2016).Google Scholar
6.EURORDIS (2010). Why Research on Rare Diseases? http://www.eurordis.org/sites/default/files/publications/why_rare_disease_research.pdf (Accessed March 28, 2016).Google Scholar
7.Schuller, Y, Hollak, CEM, Biegstraaten, M. The quality of economic evaluations of ultra-orphan drugs in Europe – a systematic review. Orphanet J Rare Dis. 2015;10:92.Google Scholar
8.Marra, CA, Woolcott, JC, Kopec, JA, et al. A comparison of generic, indirect utility measures (the HUI2, HUI3, SF-6D, and the EQ-5D) and disease-specific instruments (the RAQoL and the HAQ) in rheumatoid arthritis. Soc Sci Med. 2005;60:1571–1582.Google Scholar
9.Sprangers, MA, de Regt, EB, Andries, F, et al. Which chronic conditions are associated with better or poorer quality of life? J Clin Epidemiol. 2000;53:895–907.Google Scholar
10.EuroQol. Who is using EQ-5D?. http://www.euroqol.org/about-eq-5d/how-to-use-eq-5d/who-is-using-eq-5d.html (Accessed March 9, 2015).Google Scholar
11.EuroQoL. EQ-5D-5L, Valuation. https://euroqol.org/eq-5d-instruments/eq-5d-5l-about/valuation/ (Accessed March 11, 2015).Google Scholar
12.EuroQoL. EQ-5D-5L, population norms. https://euroqol.org/eq-5d-instruments/eq-5d-3l-about/population-norms/ (Accessed March 11, 2015).Google Scholar
13.Brooks, R. EuroQoL: The current state of play. Health Policy. 1996;37:53–72.Google Scholar
14.Angelis, A, Kanavos, P, López-Bastida, J, et al. Social and economic costs and health-related quality of life in non-institutionalised patients with cystic fibrosis in the United Kingdom. BMC Health Serv Res. 2015;15:428.Google Scholar
15.De Wit, GA, Busschbach, JJ, De Charro, FT. Sensitivity and perspective in the valuation of health status: Whose values count? Health Econ. 2000;9:109–126.Google Scholar
16.Krabbe, PF, Tromp, N, Ruers, TJ, van Riel, PL. Are patients' judgments of health status really different from the general population? Health Qual Life Outcomes. 2011;9:31.Google Scholar
17.Versteegh, MM, Leunis, A, Uyl-de Groot, CA, Stolk, EA. Condition-specific preference-based measures: Benefit or burden? Value Health. 2012;15:504–513.Google Scholar
18.López-Bastida, J, Linertová, R, Oliva-Moreno, J, et al. Social/economic costs and health-related quality of life in patients with Prader-Willi syndrome in Europe. Eur J Health Econ. 2016;17(Suppl 1):99–108.Google Scholar
19.Chevreul, K, Gandré, C, Brigham, KB, et al. Social/economic costs and health-related quality of life in patients with fragile X syndrome in Europe. Eur J Health Econ. 2016;17(Suppl 1):43–52.Google Scholar
20.Cavazza, M, Kodra, Y, Armeni, P, et al. Social/economic costs and health-related quality of life in patients with Duchenne muscular dystrophy in Europe. Eur J Health Econ. 2016;17(Suppl 1):19–29.Google Scholar
21.Winter, Y, Schepelmann, K, Spottke, AE, et al. Health-related quality of life in ALS, myasthenia gravis and facioscapulohumeral muscular dystrophy. J Neurol. 2010;257:1473–1481.Google Scholar
22.Calvert, M, Pall, H, Hoppitt, T, et al. Health-related quality of life and supportive care in patients with rare long-term neurological conditions. Qual Life Res. 2013;22:1231–1238.Google Scholar
23.Kanavos, P, Nicod, E. What is wrong with orphan drug policies? Suggestions for ways forward. Value Health. 2012;15:1182–1184.Google Scholar
24.Drummond, M, Towse, A. Orphan drugs policies: A suitable case for treatment. Eur J Health Econ. 2014;15:335–340.Google Scholar
25.Mpofu, S, Moots, R. A case of multiple sclerosis associated with rheumatoid arthritis and positive anticardiolipin antibodies. Ann Rheum Dis. 2003;62:376.Google Scholar
26.Dua, T, Garrido Cumbrera, M, Mathers, C, Saxena, S. WHO 2006. Neurological disorders: Public health challenges. Chapter 2: Global burden of neurological disorders estimates and projections. © World Health Organization 2006. http://www.who.int/mental_health/neurology/chapter_2_neuro_disorders_public_h_challenges.pdf (Accessed July 10, 2016).Google Scholar
27.Dickens, C, Creed, F. The burden of depression in patients with rheumatoid arthritis. Rheumatology (Oxford). 2001;40:1327–1330.Google Scholar
28.Hunter, DJ, Riordan, EA. The impact of arthritis on pain and quality of life: An Australian survey. Int J Rheum Dis. 2014;17:149–155.Google Scholar
29.Sidovar, MF, Limone, BL, Coleman, CI. Mapping of Multiple Sclerosis Walking Scale (MSWS-12) to five-dimension EuroQol (EQ-5D) health outcomes: An independent validation in a randomized control cohort. Patient Relat Outcome Meas. 2016;7:13–18.Google Scholar
30.Kemanetzoglou, E, Andreadou, E. CNS Demyelination with TNF-α blockers. Curr Neurol Neurosci Rep. 2017;17:36.Google Scholar
31.Heins, MJ, Korevaar, JC, Hopman, PE, et al. Health-related quality of life and health care use in cancer survivors compared with patients with chronic diseases. Cancer. 2016;122:962–970.Google Scholar
32.Tordrup, D, Mossman, J, Kanavos, P. Responsiveness of the EQ-5D to clinical change: Is the patient experience adequately represented? Int J Technol Assess Health Care. 2014;30:10–19.Google Scholar
Supplementary material: File

Efthymiadou et al. supplementary material

Efthymiadou et al. supplementary material 1

Download Efthymiadou et al. supplementary material(File)
File 67.9 KB