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PATIENT-REPORTED OUTCOMES IN RARE LYSOSOMAL STORAGE DISEASES: KEY INFORMANT INTERVIEWS AND A SYSTEMATIC REVIEW PROTOCOL

Part of: Special Collection - Methods

Published online by Cambridge University Press:  28 December 2016

Patricia A. Miller Open the ORCID record for Patricia A. Miller [Opens in a new window] ,
Sohail M. Mulla ,
Thomasin Adams-Webber Open the ORCID record for Thomasin Adams-Webber [Opens in a new window] ,
Yasmin Sivji ,
Gordon H. Guyatt  and
Bradley C. Johnston
Patricia A. Miller
Affiliation:
School of Rehabilitation Science, McMaster [email protected]
Sohail M. Mulla
Affiliation:
Clinical Epidemiology and Biostatistics, McMaster University
Thomasin Adams-Webber
Affiliation:
The Hospital for Sick Children
Yasmin Sivji
Affiliation:
Department of Medicine, McMaster University
Gordon H. Guyatt
Affiliation:
Clinical Epidemiology and Biostatistics, McMaster University
Bradley C. Johnston
Affiliation:
The Hospital for Sick Children
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Abstract

Objectives: To investigate the use, challenges and opportunities associated with using patient-reported outcomes (PROs) in studies with patients with rare lysosomal storage diseases (LSDs), we conducted interviews with researchers and health technology assessment (HTA) experts, and developed the methods for a systematic review of the literature. The purpose of the review is to identify the psychometrically sound generic and disease-specific PROs used in studies with patients with five LSDs of interest: Fabry, Gaucher (Type I), Niemann-Pick (Type B) and Pompe diseases, and mucopolysaccharidosis (Types I and II).

Methods: Researchers and HTA experts who responded to an email invitation participated in a telephone interview. We used qualitative content analysis to analyze the anonymized transcripts. We conducted a comprehensive literature search for studies that used PROs to investigate burden of disease or to assess the impact of interventions across the five LSDs of interest.

Results: Interviews with seven researchers and six HTA experts representing eight countries revealed five themes. These were: (i) the importance of using psychometrically sound PROs in studies with rare diseases, (ii) the paucity of disease-specific PROs, (iii) the importance of having PRO data for economic analyses, (iv) practical and psychometric limitations of existing PROs, and (v) suggestions for new PROs. The systematic review has been completed.

Conclusions: The interviews highlight current challenges and opportunities experienced by researchers and HTA experts involved in work with rare LSDs. The ongoing systematic review will highlight the experience, opportunities, and limitations of PROs in LSDs and provide suggestions for future research.

Keywords

Patient-reported outcomesLysosomal storage diseasesSystematic reviewQualitative research
Type
Methods
Information
International Journal of Technology Assessment in Health Care , Volume 32 , Issue 6 , 2016 , pp. 393 - 399
Copyright
Copyright © Cambridge University Press 2016 

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References

REFERENCES

1. Guyatt, G, Montori, V, Devereaux, PJ, Schunemann, H, Bhandari, M. Patients at the center: In our practice, and in our use of language. ACP J Club. 2004;140:A11–A12.Google Scholar
2. Johnston, BC, Donen, R, Pooni, A, et al. Conceptual framework for health-related quality of life assessment in acute gastroenteritis. J Pediatr Gastroenterol Nutr. 2013;56:280–289.Google Scholar
3. Fayers, P, Machin, D. Quality of life: The assessment, analysis and interpretation of patient-reported outcomes. New York: John Wiley & Sons; 2013.Google Scholar
4. US Food and Drug Administration. Guidance for industry: Patient-reported outcome measures. Use in medical product development to support labeling claims; 2009. http://www.fda.gov/downloads/drugs/guidances/ucm193282.pdf (accessed February 4, 2016).Google Scholar
5. Rahimi, K, Malhotra, A, Banning, AP, Jenkinson, C. Outcome selection and role of patient reported outcomes in contemporary cardiovascular trials: Systematic review. BMJ. 2010;341:c5707.Google Scholar
6. Kalyoncu, U, Dougados, M, Daures, JP, Gossec, L. Reporting of patient-reported outcomes in recent trials in rheumatoid arthritis: A systematic literature review. Ann Rheum Dis. 2009;68:183–190.Google Scholar
7. European Network for Health Technology Assessment. Endpoints used for relative effectiveness assessment of pharmaceuticals: Health-related quality of life and utility measures; 2013. http://www.eunethta.eu/sites/5026.fedimbo.belgium.be/files/Health-related%20quality%20of%20life.pdf (accessed February 4, 2016).Google Scholar
8. Reeve, BB, Wyrwich, KW, Wu, AW, et al. ISOQOL recommends minimum standards for patient-reported outcome measures used in patient-centered outcomes and comparative effectiveness research. Qual Life Res. 2013;22:1889–1905.Google Scholar
9. Magasi, S, Ryan, G, Revicki, D, et al. Content validity of patient-reported outcome measures: Perspectives from a PROMIS meeting. Qual Life Res. 2012;21:739–746.Google Scholar
10. Richardson, J, Chen, G, Khan, MA, Iezzi, A. Subjective wellbeing versus utility: Incommensurable or mismeasured construct. Working Paper 04-14; 2014. http://www.aqol.com.au/papers/workingpaper04-14.pdf (accessed February 4, 2016).Google Scholar
11. Hsieh, HF, Shannon, SE. Three approaches to qualitative content analysis. Qual Health Res. 2005;15:1277–1288.Google Scholar
12. Creswell, JW. Qualitative inquiry and research design: Choosing among the five traditions. Thousand Oaks: Sage Publications, Inc; 1998.Google Scholar
13. Wiebe, S, Guyatt, G, Weaver, B, Matijevic, S, Sidwell, C. Comparative responsiveness of generic and specific quality-of-life instruments. J Clin Epidemiol. 2003;56:52–60.Google Scholar
14. Schunemann, HJ, Guyatt, GH. Commentary–goodbye M(C)ID! Hello MID, where do you come from? Health Serv Res. 2005;40:593–597.CrossRefGoogle Scholar
15. Guyatt, GH, Osoba, D, Wu, AW, Wyrwich, KW, Norman, GR. Methods to explain the clinical significance of health status measures. Mayo Clin Proc. 2002;77:371–383.CrossRefGoogle ScholarPubMed
16. Guyatt, GH, Juniper, EF, Walter, SD, Griffith, LE, Goldstein, RS. Interpreting treatment effects in randomised trials. BMJ. 1998 Feb 28;316:690–693.Google Scholar
17. Norman, GR, Sloan, JA, Wyrwich, KW. Interpretation of changes in health-related quality of life: The remarkable universality of half a standard deviation. Med Care. 2003;41:582–592.Google Scholar
18. Ware, JE Jr. SF-36 health survey update. Spine. 2000;25:3130–3139.CrossRefGoogle ScholarPubMed
19. Sullivan, M, Karlsson, J, Ware, JE Jr. The Swedish SF-36 Health Survey–I. Evaluation of data quality, scaling assumptions, reliability and construct validity across general populations in Sweden. Soc Sci Med. 1995;41:1349–1358.Google Scholar
20. Schermuly, I, Muller, MJ, Muller, KM, et al. Neuropsychiatric symptoms and brain structural alterations in Fabry disease. Eur J Neurol. 2011;18:347–353.CrossRefGoogle ScholarPubMed
21. Kosinski, M, Zhao, SZ, Dedhiya, S, Osterhaus, JT, Jr, Ware JE. Determining minimally important changes in generic and disease-specific health-related quality of life questionnaires in clinical trials of rheumatoid arthritis. Arthritis Rheum. 2000;43:1478–1487.Google Scholar
22. Szende, A, Oppe, M, Devlin, NJ, editors. EQ-5D value sets: Inventory, comparative review and user guide. Dordrecht, The Netherlands: Springer; 2007.Google Scholar
23. Kind, P, Hardman, G, Macran, S. UK population norms for EQ-5D; 1999. http://www.york.ac.uk/media/che/documents/papers/discussionpapers/CHE%20Discussion%20Paper%20172.pdf (accessed February 4, 2016).Google Scholar
24. Walters, SJ, Brazier, JE. Comparison of the minimally important difference for two health state utility measures: EQ-5D and SF-6D. Qual Life Res. 2005;14:1523–1532.Google Scholar
25. Cleeland, CS, Ryan, KM. Pain assessment: Global use of the Brief Pain Inventory. Ann Acad Med Singapore. 1994;23:129–138.Google Scholar
26. Dworkin, RH, Turk, DC, Wyrwich, KW, et al. Interpreting the clinical importance of treatment outcomes in chronic pain clinical trials: IMMPACT recommendations. J Pain. 2008;9:105–121.CrossRefGoogle ScholarPubMed
27. Melzack, R. The short-form McGill Pain Questionnaire. Pain. 1987;30:191–197.Google Scholar
28. Ro, LS, Chen, CM, Chang, HS, et al. Contribution of clinical screening to carrier detection in a large Chinese family with Fabry disease due to a novel alpha-galactosidase A gene deletion. Eur J Neurol. 2007;14:493–497.CrossRefGoogle Scholar
29. Krupp, LB, LaRocca, NG, Muir-Nash, J, Steinberg, AD. The fatigue severity scale. Application to patients with multiple sclerosis and systemic lupus erythematosus. Arch Neurol. 1989;46:1121–1123.Google Scholar
30. Merkies, IS, Schmitz, PI, Samijn, JP, van der Meche, FG, van Doorn, PA. Fatigue in immune-mediated polyneuropathies. European Inflammatory Neuropathy Cause and Treatment (INCAT) Group. Neurology. 1999;53:1648–1654.CrossRefGoogle ScholarPubMed
31. Singh, G, Athreya, B, Fries, JF, Goldsmith, DP. Measurement of health status in children with juvenile rheumatoid arthritis. Arthritis Rheum. 1994;37:1761–1769.Google Scholar
32. Nugent, J, Ruperto, N, Grainger, J, et al. The British version of the Childhood Health Assessment Questionnaire (CHAQ) and the Child Health Questionnaire (CHQ). Clin Exp Rheumatol. 2001;19 (Suppl 23):S163–S167.Google Scholar
33. Dempster, H, Porepa, M, Young, N, Feldman, BM. The clinical meaning of functional outcome scores in children with juvenile arthritis. Arthritis Rheum. 2001;44:1768–1774.3.0.CO;2-Q>CrossRefGoogle ScholarPubMed
34. Merkies, IS, Schmitz, PI, Van Der Meche, FG, Samijn, JP, Van Doorn, PA. Psychometric evaluation of a new handicap scale in immune-mediated polyneuropathies. Muscle Nerve. 2002;25:370–377.CrossRefGoogle ScholarPubMed
35. Hagemans, ML, Laforet, P, Hop, WJ, et al. Impact of late-onset Pompe disease on participation in daily life activities: Evaluation of the Rotterdam Handicap Scale. Neuromuscul Disord. 2007; 17:537–543.Google Scholar
36. Johnston, BC, Miller, PA, Agarwal, A, et al. Limited responsiveness related to the minimal important difference of patient-reported outcomes in rare diseases. J Clin Epidemiol. 2016; Jul 2. pii: S0895-4356(16)30187-1. doi: 10.1016/j.jclinepi.2016.06.010. [Epub ahead of print]Google Scholar
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