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26-05-2021

Development of a preference-based heart disease-specific health state classification system using MacNew heart disease-related quality of life instrument

Auteurs: Sanjeewa Kularatna, Donna Rowen, Clara Mukuria, Steven McPhail, Gang Chen, Brendan Mulhern, Jennifer A. Whitty, Joshua Byrnes, Paul Scuffham, John Atherton, Stefan Höfer, William Parsonage

Gepubliceerd in: Quality of Life Research | Uitgave 1/2022

Abstract

Purpose

The MacNew Heart Disease Health-Related Quality of Life Instrument (MacNew) is a validated, clinically sensitive, 27-item disease-specific questionnaire. This study aimed to develop a new heart disease-specific classification system for the MacNew amenable for use in health state valuation.

Methods

Patients with heart disease attending outpatient clinics and inpatient wards in Brisbane, Australia, completed MacNew. The development of the new disease-specific classification system included three stages. First, a principal component analysis (PCA) established dimensionality. Second, Rasch analysis was used to select items for each dimension. Third, Rasch analysis was used to explore response-level reduction. In addition, clinician and patient judgement informed item selection.

Results

Participants included 685 patients (acute coronary 6%, stable coronary 41%, chronic heart failure 20%). The PCA identified 4 dimensions (restriction, emotion, perception of others, and symptoms). The restriction dimension was divided into physical and social dimensions. One item was selected from each to be included in the classification system. Three items from the emotional dimension and two symptom items were also selected. The final classification system had seven dimensions with four severity levels in each: physical restriction; excluded from doing things with other people; worn out or low in energy; frustrated, impatient or angry; unsure and lacking in self-confidence; shortness of breath; and chest pain.

Conclusion

This study generated a brief heart disease-specific classification system, consisting of seven dimensions with four severity levels in each. The classification system is amenable to valuation to enable the generation of utility value sets to be developed for use in economic evaluation.

vorige artikel Correction to: Patients’ and parents’ perspective on the implementation of Patient Reported Outcome Measures in pediatric clinical practice using the KLIK PROM portal

volgende artikel Psychometric properties of the PROMIS-57 questionnaire, Norwegian version

Alleen toegankelijk voor geautoriseerde gebruikers

Cardiovascular disease: a costly burden for America: projections through 2035. Research Triangle Park, NC: Research Triangle Institute (2017)

Centres for Disease Control and Prevention (2019). Heart Disease Facts https://www.cdc.gov/heartdisease/facts.htm. Accessed 26 May 2020

Chan, Y.-K., Tuttle, C., Ball, J., Teng, T.-H.K., Ahamed, Y., Carrington, M. J., et al. (2016). Current and projected burden of heart failure in the Australian adult population: a substantive but still ill-defined major health issue. BMC Health Services Research, 16(1), 501. https://doi.org/10.1186/s12913-016-1748-0CrossRefPubMedPubMedCentral

Weisfeldt, M. L., & Zieman, S. J. (2007). Advances in the prevention and treatment of cardiovascular disease. Health Aff (Millwood), 26(1), 25–37. https://doi.org/10.1377/hlthaff.26.1.25CrossRef

Drummond, M. F., et al. (2015). Methods for the economic evaluation of health care programmes (4th ed.). . Oxford: Pxford University Press.

Kularatna, S., Whitty, J. A., Johnson, N. W., Jayasinghe, R., & Scuffham, P. A. (2015). Valuing EQ-5D health states for Sri Lanka. Quality of Life Research, 24(7), 1785–1793. https://doi.org/10.1007/s11136-014-0906-2CrossRefPubMed

Rowen, D., Rivero-Arias, O., Devlin, N., & Ratcliffe, J. (2020). Review of valuation methods of preference-based measures of health for economic evaluation in child and adolescent populations: Where are we now and where are we going. PharmacoEconomics. https://doi.org/10.1007/s40273-019-00873-7CrossRefPubMed

Devlin, N. J., & Brooks, R. (2017). EQ-5D and the EuroQol Group: Past, present and future. Applied health economics and health policy, 15(2), 127–137. https://doi.org/10.1007/s40258-017-0310-5CrossRefPubMedPubMedCentral

Lorgelly, P. K., Doble, B., Rowen, D., Brazier, J., Thomas, D. M., Fox, S. B., et al. (2017). Condition-specific or generic preference-based measures in oncology? A comparison of the EORTC-8D and the EQ-5D-3L. Quality of Life Research, 26(5), 1163–1176. https://doi.org/10.1007/s11136-016-1443-yCrossRefPubMed

10.

Rankin, J., Rowen, D., Howe, A., Cleland, J. G. F., & Whitty, J. A. (2019). Valuing health-related quality of life in heart failure: A systematic review of methods to derive quality-adjusted life years (QALYs) in trial-based cost–utility analyses. Heart Failure Reviews, 24(4), 549–563. https://doi.org/10.1007/s10741-019-09780-7CrossRefPubMedPubMedCentral

11.

Kularatna, S., Byrnes, J., Chan, Y. K., Carrington, M. J., Stewart, S., & Scuffham, P. A. (2017). Comparison of contemporaneous responses for EQ-5D-3L and Minnesota living with heart failure; a case for disease specific multiattribute utility instrument in cardiovascular conditions. International Journal of Cardiology, 227, 172–176. https://doi.org/10.1016/j.ijcard.2016.11.030CrossRefPubMed

12.

Kularatna, S., Senanayake, S., Chen, G., & Parsonage, W. (2020). Mapping the Minnesota living with heart failure questionnaire (MLHFQ) to EQ-5D-5L in patients with heart failure. Health and Quality of Life Outcomes, 18(1), 115. https://doi.org/10.1186/s12955-020-01368-2CrossRefPubMedPubMedCentral

13.

Chen, G., McKie, J., Khan, M. A., & Richardson, J. R. (2015). Deriving health utilities from the MacNew Heart Disease Quality of Life Questionnaire. European Journal of Cardiovascular Nursing, 14(5), 405–415. https://doi.org/10.1177/1474515114536096CrossRefPubMed

14.

Eurich, D. T., Johnson, J. A., Reid, K. J., & Spertus, J. A. (2006). Assessing responsiveness of generic and specific health related quality of life measures in heart failure. Health and Quality of Life Outcomes, 4, 89. https://doi.org/10.1186/1477-7525-4-89CrossRefPubMedPubMedCentral

15.

Berry, C., & McMurray, J. (1999). A review of quality-of-life evaluations in patients with congestive heart failure. PharmacoEconomics, 16(3), 247–271. https://doi.org/10.2165/00019053-199916030-00003CrossRefPubMed

16.

Bilbao, A., Escobar, A., García-Perez, L., Navarro, G., & Quirós, R. (2016). The Minnesota living with heart failure questionnaire: Comparison of different factor structures. Health and Quality of Life Outcomes, 14, 23–23. https://doi.org/10.1186/s12955-016-0425-7CrossRefPubMedPubMedCentral

17.

Spertus, J. A., Winder, J. A., Dewhurst, T. A., Deyo, R. A., Prodzinski, J., McDonell, M., et al. (1995). Development and evaluation of the Seattle Angina Questionnaire: A new functional status measure for coronary artery disease. Journal of the American College of Cardiology, 25(2), 333–341. https://doi.org/10.1016/0735-1097(94)00397-9CrossRefPubMed

18.

Höfer, S., Lim, L., Guyatt, G., & Oldridge, N. (2004). The MacNew Heart Disease health-related quality of life instrument: A summary. Health and Quality of Life Outcomes, 2(1), 3. https://doi.org/10.1186/1477-7525-2-3CrossRefPubMedPubMedCentral

19.

Dempster, M., Donnelly, M., & O’Loughlin, C. (2004). The validity of the MacNew Quality of Life in heart disease questionnaire. Health and Quality of Life Outcomes, 2, 6–6. https://doi.org/10.1186/1477-7525-2-6CrossRefPubMedPubMedCentral

20.

Alphin, S., Höfer, S., Perk, J., Slørdahl, S., Zwisler, A.-D.O., & Oldridge, N. (2015). The MacNew Heart Disease Health-Related Quality of Life questionnaire: A scandinavian validation study. Social indicators research, 122(2), 519–537. https://doi.org/10.1007/s11205-014-0694-7CrossRefPubMed

21.

Rowen, D., Brazier, J., Ara, R., & Azzabi Zouraq, I. (2017). The role of condition-specific preference-based measures in health technology assessment. PharmacoEconomics, 35(1), 33–41. https://doi.org/10.1007/s40273-017-0546-9CrossRefPubMed

22.

Green, C. P., Porter, C. B., Bresnahan, D. R., & Spertus, J. A. (2000). Development and evaluation of the Kansas city cardiomyopathy questionnaire: a new health status measure for heart failure. Journal of the American College of Cardiology, 35(5), 1245–1255. https://doi.org/10.1016/s0735-1097(00)00531-3CrossRefPubMed

23.

Hillers, T. K., Guyatt, G. H., Oldridge, N., Crowe, J., Willan, A., Griffith, L., et al. (1994). Quality of life after myocardial infarction. Journal of Clinical Epidemiology, 47(11), 1287–1296. https://doi.org/10.1016/0895-4356(94)90134-1CrossRefPubMed

24.

Brazier, J., Roberts, J., & Deverill, M. (2002). The estimation of a preference-based measure of health from the SF-36. Journal of Health Economics, 21(2), 271–292. https://doi.org/10.1016/s0167-6296(01)00130-8CrossRefPubMed

25.

Nguyen, K. H., Mulhern, B., Kularatna, S., Byrnes, J., Moyle, W., & Comans, T. (2017). Developing a dementia-specific health state classification system for a new preference-based instrument AD-5D. Health and Quality of Life Outcomes, 15(1), 21. https://doi.org/10.1186/s12955-017-0585-0CrossRefPubMedPubMedCentral

26.

Mukuria, C., Rowen, D., Brazier, J. E., Young, T. A., & Nafees, B. (2015). Deriving a preference-based measure for myelofibrosis from the EORTC QLQ-C30 and the MF-SAF. Value in Health, 18(6), 846–855. https://doi.org/10.1016/j.jval.2015.07.004CrossRefPubMed

27.

Rowen, D., Brazier, J., Young, T., Gaugris, S., Craig, B. M., King, M. T., et al. (2011). Deriving a preference-based measure for cancer using the EORTC QLQ-C30. Value Health, 14(5), 721–731. https://doi.org/10.1016/j.jval.2011.01.004CrossRefPubMed

28.

Brazier, J., Rowen, D., Mavranezouli, I., Tsuchiya, A., & Young, T. (2012). Developing and testing methods for deriving preference-based measures of health from condition-specific measures and other patient-based measures of outcome. Health Technology Assessment, 16(32), 1–114.CrossRef

29.

Gable, R. K., McCoach, D. B., & Madura, J. P. (1993). Instrument development in the affective domain. New York: Springer.CrossRef

30.

Tabachnick, B. G., & Fidell, L. S. (2007). Using multivariate statistics (5th ed.). . Boston, MA: Allyn and Bacon/Pearson Education.

31.

Tennant, A., & Conaghan, P. G. (2007). The Rasch measurement model in rheumatology: What is it and why use it? When should it be applied, and what should one look for in a Rasch paper? Arthritis and Rheumatism, 57(8), 1358–1362. https://doi.org/10.1002/art.23108CrossRefPubMed

32.

Young, T. A., Yang, Y., Brazier, J. E., & Tsuchiya, A. (2011). The use of rasch analysis in reducing a large condition-specific instrument for preference valuation: The case of moving from AQLQ to AQL-5D. Medical Decision Making, 31(1), 195–210. https://doi.org/10.1177/0272989x10364846CrossRefPubMed

33.

Young, T., Yang, Y., Brazier, J. E., Tsuchiya, A., & Coyne, K. J. (2008). The first stage of developing preference-based measures: Constructing a health-state classification using Rasch analysis. Quality of Life Research, 18(2), 253. https://doi.org/10.1007/s11136-008-9428-0CrossRefPubMed

34.

Tennant, A., McKenna, S. P., & Hagell, P. (2004). Application of Rasch analysis in the development and application of quality of life instruments. Value Health, 7(Suppl 1), S22-26. https://doi.org/10.1111/j.1524-4733.2004.7s106.xCrossRefPubMed

35.

Comrey, A. L. (1973). A first course in factor analysis. New York: Academic Press.

36.

Young, T. A., Rowen, D., Norquist, J., & Brazier, J. E. (2010). Developing preference-based health measures: Using Rasch analysis to generate health state values. Quality of Life Research, 19(6), 907–917. https://doi.org/10.1007/s11136-010-9646-0CrossRefPubMed

Titel: Development of a preference-based heart disease-specific health state classification system using MacNew heart disease-related quality of life instrument
Auteurs: Sanjeewa Kularatna
Donna Rowen
Clara Mukuria
Steven McPhail
Gang Chen
Brendan Mulhern
Jennifer A. Whitty
Joshua Byrnes
Paul Scuffham
John Atherton
Stefan Höfer
William Parsonage
Publicatiedatum: 26-05-2021
Uitgeverij: Springer International Publishing
Gepubliceerd in: Quality of Life Research / Uitgave 1/2022
Print ISSN: 0962-9343
Elektronisch ISSN: 1573-2649
DOI: https://doi.org/10.1007/s11136-021-02884-4

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Abstract

Purpose

Methods

Results

Conclusion

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