Psychometric Validation of the Growth Hormone Deficiency-Child Impact Measure (GHD-CIM)

Meryl Brod, Michael Højby Rasmussen, Knud Vad, Suzanne Alolga, Donald M Bushnell, Jacques Bedoin, Aristides Maniatis, Meryl Brod, Michael Højby Rasmussen, Knud Vad, Suzanne Alolga, Donald M Bushnell, Jacques Bedoin, Aristides Maniatis

Abstract

Objective: The aim of this study was to perform psychometric testing of the Growth Hormone Deficiency-Child Impact Measure (GHD-CIM): a patient-reported outcome (PRO) for children with GHD aged 9 to < 13 years and an observer-reported outcome (ObsRO) for parents/guardians of children who are unable to answer for themselves.

Methods: A non-interventional, multicenter, clinic-based study was conducted in 30 private-practice and large institutional sites in the US and the UK. Psychometric analyses were conducted following an a priori validation statistical analysis plan.

Results: A preliminary examination of the data determined a PRO version for children aged 9 to < 13 years was not psychometrically sound and therefore the decision was made to have only an ObsRO measure of the GHD-CIM, which would be suitable for children aged 4 to < 13 years. The GHD-CIM ObsRO validity analyses included 98 parents/guardians. Factor analyses identified three domains: Physical Functioning (PHYS), Social Well-Being (SWB), and Emotional Well-Being (EWB). Internal consistency reliability was acceptable for all domains and for the overall score (Cronbach's alpha > 0.70), as was test-retest reliability for the SWB, EWB and overall (above 0.70). At least one convergent validity hypotheses for each domain and overall was proven (r > 0.40). Known-groups validity hypotheses for the EWB and SWB domains were significant (p < 0.05). Associated effect sizes ranged from - 0.40 to - 0.58, indicating that the GHD-CIM is sensitive to change. Anchor-based patient and clinician ratings of severity of disease suggest a preliminary minimally important difference of 5 points for the overall score, and 5 for PHYS, 7 for EWB, and 5 for SWB.

Conclusions: The GHD-CIM ObsRO was found to be a reliable and valid measure to assess disease-specific functioning, which will provide a more complete patient-centric picture to the growth hormone therapy experience in children.

Trial registration: ClinicalTrials.gov NCT02580032, first posted 20 October 2015.

Conflict of interest statement

Meryl Brod, Suzanne Alolga, and Donald M. Bushnell are paid consultants to the pharmaceutical industry, including Novo Nordisk. Michael Højby Rasmussen, Knud Vad, and Jacques Bedoin are employees of Novo Nordisk, A/S. Aristides Maniatis is a principal investigator for Novo Nordisk, Ascendis, Pfizer/OPKO, Genentech, and Sandoz.

© 2021. The Author(s).

Figures

Fig. 1
Fig. 1
Evidence for known-groups validity of the GHD-CIM based on the QoLISSY Coping domain. Significance for emotional well-being and social well-being was p < 0.05; physical functioning and overall were not significant. Assessed using the QoLISSY Coping domain. GHD-CIM Growth Hormone Deficiency-Child Impact Measure, QoLISSY Quality of Life in Short Stature Youth
Fig. 2
Fig. 2
Evidence for known-groups validity of the GHD-CIM based on the QoLISSY Emotional domain. Significance for all GHD-CIM domains was p < 0.01. Assessed using the QoLISSY Emotional domain. GHD-CIM Growth Hormone Deficiency-Child Impact Measure, QoLISSY Quality of Life in Short Stature Youth
Fig. 3
Fig. 3
GHD-CIM theoretical model. GHD-CIM Growth Hormone Deficiency-Child Impact Measure, GHD growth hormone deficiency
Fig. 4
Fig. 4
GHD-CIM conceptual framework. GHD-CIM Growth Hormone Deficiency-Child Impact Measure

References

    1. Donaldson MDC, Gregory JW, Van Vliet G, Wolfsdorf JI, Deladoey J. Short stature. In: practical endocrinology and diabetes in children. 2019. 10.1002/9781119386230. Accessed 22 Jan 2020.
    1. Thomas M, Massa G, Craen M, de Zegher F, Bourguignon JP, Heinrichs C, et al. Prevalence and demographic features of childhood growth hormone deficiency in Belgium during the period 1986–2001. Eur J Endocrinol. 2004;151(1):67–72. doi: 10.1530/eje.0.1510067.
    1. Vimpani GV, Vimpani AF, Lidgard GP, Cameron EH, Farquhar JW. Prevalence of severe growth hormone deficiency. Br Med J. 1977;2(6084):427–430. doi: 10.1136/bmj.2.6084.427.
    1. Lindsay R, Feldkamp M, Harris D, Robertson J, Rallison M. Utah Growth Study: growth standards and the prevalence of growth hormone deficiency. J Pediatr. 1994;125(1):29–35. doi: 10.1016/s0022-3476(94)70117-2.
    1. Brod M, Alolga SL, Beck JF, Wilkinson L, Hojbjerre L, Rasmussen MH. Understanding burden of illness for child growth hormone deficiency. Qual Life Res. 2017;26(7):1673–1686. doi: 10.1007/s11136-017-1529-1.
    1. Grimberg A, DiVall SA, Polychronakos C, Allen DB, Cohen LE, Quintos JB, et al. Guidelines for growth hormone and insulin-like growth factor-I treatment in children and adolescents: growth hormone deficiency, idiopathic short stature, and primary insulin-like growth factor-I deficiency. Horm Res Paediatr. 2016;86(6):361–397. doi: 10.1159/000452150.
    1. Souza FM, Collett-Solberg PF. Adverse effects of growth hormone replacement therapy in children. Arq Bras Endocrinol Metabol. 2011;55(8):559–565. doi: 10.1590/s0004-27302011000800009.
    1. US FDA. Patient-reported outcome measures: use in medical product development to support labeling claims: guidance for industry. 2009. . Accessed 20 Feb 2019.
    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. 2005. . Accessed 20 Feb 2019.
    1. Matza LS, Patrick DL, Riley AW, Alexander JJ, Rajmil L, Pleil AM, et al. Pediatric patient-reported outcome instruments for research to support medical product labeling: report of the ISPOR PRO good research practices for the assessment of children and adolescents task force. Value Health. 2013;16(4):461–479. doi: 10.1016/j.jval.2013.04.004.
    1. World Medical Association (WMA). WMA Declaration of Helsinki—Ethical principles for medical research involving human subjects. 2013. . Accessed 10 May 2019.
    1. International Society for Pharmacoepidemiology Guidelines for good pharmacoepidemiology practices (GPP) Pharmacoepidemiol Drug Saf. 2008;17(2):200–208. doi: 10.1002/pds.1471.
    1. US Office of the Federal Register. Electronic Code of Federal Regulations. Titles 21§50 Protection of human subjects and §56 Institutional review boards. Washington, DC: Office of the Federal Register; 2018. . Accessed 10 May 2019.
    1. Prader A, Largo RH, Molinari L, Issler C. Physical growth of Swiss children from birth to 20 years of age. First Zurich longitudinal study of growth and development. Helv Paediatr Acta Suppl. 1989;52:1–125.
    1. Bullinger M, Quitmann J, Power M, Herdman M, Mimoun E, DeBusk K, et al. Assessing the quality of life of health-referred children and adolescents with short stature: development and psychometric testing of the QoLISSY instrument. Health Qual Life Outcomes. 2013;11:76. doi: 10.1186/1477-7525-11-76.
    1. Bullinger M, Schmidt S, Petersen C, Disabkids Group Assessing quality of life of children with chronic health conditions and disabilities: a European approach. Int J Rehabil Res. 2002;25(3):197–206. doi: 10.1097/00004356-200209000-00005.
    1. Whiteside SP. Adapting the Sheehan disability scale to assess child and parent impairment related to childhood anxiety disorders. J Clin Child Adolesc Psychol. 2009;38(5):721–730. doi: 10.1080/15374410903103551.
    1. Snoek FJ, Mollema ED, Heine RJ, Bouter LM, van der Ploeg HM. Development and validation of the Diabetes Fear of Injecting and Self-Testing Questionnaire (D-FISQ): first findings. Diabet Med. 1997;14(10):871–876. doi: 10.1002/(SICI)1096-9136(199710)14:10<871:AID-DIA457>;2-Y.
    1. SPSS Inc. PASW Statistics for Windows. 18.0 ed. Chicago, IL: SPSS Inc.; 2009.
    1. Carmines EC, Zeller RA. Reliability and validity assessment. Beverly Hills: Sage Publications; 1979.
    1. Gliem JA, Gliem RR. Calculating, interpreting, and reporting Cronbach’s alpha reliability coefficient for Likert-type scales. In: 2003 Midwest research to practice conference in adult, continuing, and community education; 2003. pp. 82–8
    1. Cronbach LJ. Coefficient alpha and the internal structure of tests. Psychometrika. 1951;16(2):297–334. doi: 10.1007/BF02310555.
    1. Cohen J. Statistical power analysis for the behavioral sciences. 2. Hillsdale: L. Erlbaum Associates; 1988.
    1. Guyatt GH, Osoba D, Wu AW, Wyrwich KW, Norman GR, Clinical Significance Consensus Meeting Group Methods to explain the clinical significance of health status measures. Mayo Clin Proc. 2002;77(4):371–383. doi: 10.4065/77.4.371.
    1. Wyrwich KW, Nienaber NA, Tierney WM, Wolinsky FD. Linking clinical relevance and statistical significance in evaluating intra-individual changes in health-related quality of life. Med Care. 1999;37(5):469–478. doi: 10.1097/00005650-199905000-00006.
    1. Byrne BM. Structural equation modeling with AMOS: basic concepts, applications, and programming. New York: Routledge; 2001.
    1. Arbuckle JL. AMOS 20.0 user’s guide. Crawfordville: Amos Development Corporation; 2011.
    1. Kline RB. Principles and practice of structural equation modeling. 3. New York: Guilford Publications; 2010.
    1. Hu L, Bentler PM. Cutoff criteria for fit indexes in covariance structure analysis: conventional criteria versus new alternatives. Struct Equ Model. 1999;6:1–55. doi: 10.1080/10705519909540118.
    1. Nunnally JC, Bernstein IH. Psychometric theory. 3. New York: McGraw-Hill; 1994.

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