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Estimating minimal important differences for several scales assessing function and quality of life in patients with attention-deficit/hyperactivity disorder

Published online by Cambridge University Press:  18 August 2016

Paul Hodgkins ,
Andrew Lloyd ,
M. Haim Erder ,
Juliana Setyawan ,
Margaret D. Weiss ,
Rahul Sasané  and
Beenish Nafees
Paul Hodgkins
Affiliation:
Health Economics Outcomes Research (HEOR), Shire, Wayne, Pennsylvania, USA
Andrew Lloyd
Affiliation:
Patient Reported Outcomes, ICON PRO, Oxford, UK
M. Haim Erder
Affiliation:
Health Economics Outcomes Research (HEOR), Shire, Wayne, Pennsylvania, USA
Juliana Setyawan*
Affiliation:
Health Economics Outcomes Research (HEOR), Shire, Wayne, Pennsylvania, USA
Margaret D. Weiss
Affiliation:
Department of Psychiatry, Children’s and Women’s Health Centre, Vancouver, British Columbia, Canada
Rahul Sasané
Affiliation:
Health Economics Outcomes Research (HEOR), Shire, Wayne, Pennsylvania, USA
Beenish Nafees
Affiliation:
Health and Outcomes Research, Nafees Consulting Limited, London, UK
*
*Address for correspondence: Juliana Setyawan, PharmD, MS, Shire, 725 Chesterbrook Boulevard, Wayne, PA 19087, USA. (Email: [email protected])
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Abstract

Objective

Defining minimal important difference (MID) is critical to interpreting patient-reported outcomes data and treatment efficacy in clinical trials. This study estimates the MID for the Weiss Functional Impairment Rating Scale–Parent Report (WFIRS-P) and the Child Health and Illness Profile–Parent Report (CHIP-CE-PRF76) among parents of young people with attention-deficit/hyperactivity disorder (ADHD) in the UK.

Methods

Parents of children (6–12 years; n=100) and adolescents (13–17 years; n=117) with ADHD completed a socio-demographic form, the CHIP-CE-PRF76, the WFIRS-P, and the Pediatric Quality of Life scale at baseline and 4 weeks later. At follow-up, a subset of parents completed anchor questions measuring change in the child/adolescent from baseline. MIDs were estimated using anchor-based and distribution-based methods, and separately for children and adolescents.

Results

The MID estimates for overall change in the WFIRS-P total score ranged from 11.31 (standard error of measurement) to 13.47 (anchor) for the total sample. The range of MID estimates for the CHIP-CE-PRF76 varied by domain: 6.80–7.41 (satisfaction), 6.18–7.34 (comfort), 5.60–6.72 (resilience), 6.06–7.57 (risk avoidance), and 4.00–5.63 (achievement) for the total sample. Overall, MID estimates for WFIRS-P MID and CHIP-CE-PRF76 were slightly higher for adolescents than for children.

Conclusion

This study estimated MIDs for these instruments using several methods. The observed convergence of the MID estimates increases confidence in their reliability and could assist clinicians and decision makers in deriving meaningful interpretations of observed changes in the WFIRS-P and CHIP-CE in clinical trials and practice.

Keywords

ADHDchildrenCHIP-CEminimal important differenceWFIRS
Type
Original Research
Information
CNS Spectrums , Volume 22 , Issue 1 , February 2017 , pp. 31 - 40
Copyright
© Cambridge University Press 2016 

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Footnotes

†

Affiliation at the time of the study.

This research was funded by Shire Development LLC. The authors would like to acknowledge input by Sarah Hearn (University of Oxford, Oxford, UK) for assistance with the statistical analysis of the study. Editorial assistance in formatting, proofreading, copyediting, and coordination and collation of comments for the manuscript was provided by Caudex (funded by Shire International GmbH, Switzerland). Although employees of Shire were involved in the design, collection, analysis, interpretation, and fact checking of information, the content of this manuscript, the ultimate interpretation, and the decision to submit it for publication in CNS Spectrums was made by the authors independently. The authors are entirely responsible for the scientific content of the paper.

References

1. Guy, W. ECDU Assessment Manual for Psychopharmacology. Rev. Bethesda, MD: U.S. Department of Health, Education and Welfare; 1976.Google Scholar
2. Rentz, AM, Matza, LM, Secnik, K, Swensen, A, Revicki, DA. Psychometric validation of the child health questionnaire (CHQ) in a sample of children and adolescents with attention-deficit/hyperactivity disorder. Qual Life Res. 2005; 14(3): 719–734.Google Scholar
3. European Medicines Agency (EMA). Guideline on the Clinical Investigation of Medicinal Products for the Treatment of Attention Deficit Hyperactivity Disorder (ADHD). London: EMA; 2010.Google Scholar
4. Hays, RD, Woolley, JM. The concept of clinically meaningful difference in health-related quality-of-life research. How meaningful is it? Pharmacoeconomics. 2000; 18(5): 419–423.Google Scholar
5. Guyatt, GH, Osoba, D, Wu, AW, Wyrwich, KW, Norman, GR, Clinical Significance Meeting Group. Methods to examine the clinical significance of health status measures. Mayo Clin Proc. 2002; 77(4): 371–383.Google Scholar
6. Revicki, DA, Erickson, PA, Sloan, JA, et al. Interpreting and reporting results based on patient-reported outcomes. Value Health. 2007; 10(Suppl 2): S116–S124.Google Scholar
7. Goodman, D, Faraone, SV, Adler, LA, Dirks, B, Hamdani, M, Weisler, R. Interpreting ADHD rating scale scores: linking ADHD rating scale scores and CGI levels in two randomized controlled trials of lisdexamfetamine dimesylate in ADHD. Primary Psychiatry. 2010; 17: 44–52.Google Scholar
8. Wyrwich, KW, Tierney, WM, Wolinsky, FD. Further evidence supporting an SEM-based criterion for identifying meaningful intra-individual changes in health-related quality of life. J Clin Epidemiol. 1999; 52(9): 861–873.Google Scholar
9. Cella, D, Hahn, EA, Dineen, K. Meaningful changes in cancer-specific quality of life scores: differences between improvement and worsening. Qual Life Res. 2002; 11(3): 207–221.CrossRefGoogle ScholarPubMed
10. Wyrwich, K, Tardino, V. Understanding global transition judgements. Qual Life Res. 2006; 15(6): 995–1004.Google Scholar
11. Farivar, SS, Liu, H, Hays, R. Half standard deviation estimate of the minimally important difference in HRQoL scores. Expert Rev Pharmacoecon Outcomes Res. 2004; 4(5): 515–523.Google Scholar
12. Revicki, D, Hays, RD, Cella, D, Sloan, J. Recommended methods for determining responsiveness and minimally important differences for patient-reported outcomes. J Clin Epidemiol. 2008; 61(2): 102–109.CrossRefGoogle ScholarPubMed
13. Riley, AW, Coghill, D, Forrest, CB, et al. Validity of the health-related quality of life assessment in the ADORE study: parent report form of the CHIP-Child edition. Eur Child Adolesc Psychiatry. 2006; 15(Suppl 1): I63–I71.Google Scholar
14. Varni, JW, Burwinkle, TM. The PedsQL™ as a patient-reported outcome in children and adolescents with attention-deficit/hyperactivity disorder: a population-based study. Health Qual Life Outcomes. 2006; 4: 26.CrossRefGoogle ScholarPubMed
15. Varni, JW, Seid, M, Kurtin, PS. PedsQL™ 4.0: reliability and validity of the Pediatric Quality of Life Inventory™ Version 4.0 Generic Core Scales in healthy and patient populations. Med Care. 2001; 39(8): 800–812.CrossRefGoogle ScholarPubMed
16. Varni, JW, Burwinkle, TM, Seid, M, Skarr, D. The PedsQLTM 4.0 as a pediatric population health measure: feasibility, reliability, and validity. Ambul Pediatr. 2003; 3(6): 329–341.Google Scholar
17. Riley, AW, Forrest, CB, Starfield, B, Rebok, GW, Robertson, JA, Green, BF. The parent report form of the CHIP-Child edition: reliability and validity. Med Care. 2004; 42(3): 210–220.Google Scholar
18. Preuss, U, Ralston, SJ, Baldursson, G, et al. Study design, baseline patient characteristics and intervention in a cross-cultural framework: results from the ADORE study. Eur Child Adolesc Psychiatry. 2006; 15(Suppl 1): I4–I14.Google Scholar
19. Harpin, VA. The effect of ADHD on the life of an individual, their family, and community from preschool to adult life. Arch Dis Child. 2005; 90(Suppl 1): I2–I7.Google Scholar
20. Hurtig, T, Ebeling, H, Taanila, A, et al. ADHD symptoms and subtypes: relationship between childhood and adolescent symptoms. J Am Acad Child Adolesc Psychiatry. 2007; 46(12): 1605–1613.Google Scholar
21. Gajria, K, Kosinski, M, Sikirica, V, et al. Psychometric validation of the Weiss Functional Impairment Rating Scale-Parent Report Form in children and adolescents with attention-deficit/hyperactivity disorder. Health Qual Life Outcomes. 2015; 13: 184.Google Scholar
22. Weiss, MD, Iverson, GL, Brooks, BL. Clinical normative data for the Weiss Functional Impairment Rating Scale in ADHD. Poster presented at the 2008 International Neuropsychological Society meeting, Hawaii, USA. J Int Neuropsychol Soc. 2008; 14(Suppl 1): 23.Google Scholar
23. Newcombe, PA, Sheffield, JK, Chang, AB. Minimally important change in a Parent-Proxy Quality of Life questionnaire for paediatric chronic cough (PC-QOL). Chest. 2011; 139(3): 576–580.Google Scholar
24. Dhanani, S, Quenneville, J, Perron, M, Abdolell, M, Feldman, BM. Minimal difference in pain associated with change in quality of life in children with rheumatic disease. Arthritis Rheum. 2002; 47(5): 501–505.Google Scholar
25. Juniper, EF, Guyatt, GH, Feeny, DH, Ferrie, PJ, Griffith, LE, Townsend, M. Measuring quality of life in the parents of children with asthma. Qual Life Res. 1996; 5(1): 27–34.Google Scholar