Quality of life assessment in patients with heart failure: validity of the German version of the generic EQ-5D-5L™

Sigrid Boczor, Anne Daubmann, Marion Eisele, Eva Blozik, Martin Scherer, Sigrid Boczor, Anne Daubmann, Marion Eisele, Eva Blozik, Martin Scherer

Abstract

Background: Chronic heart failure patients typically suffer from tremendous strain and are managed mainly in primary care. New care concepts adapted to the severity of heart failure are a challenge and need to consider health-related quality of life aspects. This is the first psychometric validation of the German EQ-5D-5L™ as a generic instrument for assessing health-related quality of life (HRQOL) in a primary care heart failure patient sample.

Methods: Confirmatory factor analysis (CFA) was performed on the baseline EQ-5D-5L™ data from the RECODE-HF study (responses to all items from n = 3225 of 3778 patients). Basic CFA models for HRQOL were calculated based on the EQ-5D-5L™ items using the maximum likelihood (ML) and the asymptotic distribution-free method. In an extended CFA, physical activity and depression were added. The basic CFA ML model was verified for the reduced number of cases of the extended CFA model (n = 3064). In analyses of variance the association of the EQ-5D-5L™ visual analogue scale (VAS) and both the German and the British EQ-5D-5L™ crosswalk index with the SF-36 measure of general health were examined. The discriminant validity was analysed using Pearson's chi-squared tests applying the New York Heart Association classification, for the VAS and indices analyses of variance were calculated.

Results: In the basic CFA models the root mean square error of approximation was 0.095 with the ML method, and 0.081 with the asymptotic distribution-free method (Comparative Fit Index > 0.90 for both). Physical activity and depression were confirmed as influential factors in the extended model. The VAS and indices were strongly associated with the SF-36 measure of general health (partial eta-squared 0.525/0.454/0.481; all p < 0.001; n = 3155/3210/3210, respectively), also for physical activity and depression when included together (partial eta-squared 0.050, 0.200/0.047, 0.213/0.051 and 0.270; all p < 0.001; n = 3015/n = 3064/n = 3064, respectively). The discriminant validity analyses showed p-values < 0.001 and small to moderate effect sizes for all EQ-5D-5L™ items. Analyses of variance demonstrated moderate effect sizes for the VAS and indices (0.067/0.087/0.084; all p < 0.001; n = 3110/3171/3171).

Conclusion: The German EQ-5D-5L™ is a suitable method for assessing HRQOL in heart failure patients.

Keywords: Confirmatory factor analysis; Construct analysis; Discriminant validity; EQ-5D-5L; Heart failure; Quality of life.

Conflict of interest statement

SB received fees as a part-time lecturer/statistical consultant from Asklepios Medical School GmbH. All other authors declare that they have no financial conflicts of interest. Non-financial conflicts of interest: ME is a member of the German College of General Practitioners and Family Physicians. MS is Vice-President of the German College of General Practitioners and Family Physicians. EB is employed by a Swiss health insurance company. All other authors declare that they have no non-financial conflicts of interest.

Figures

Fig. 1
Fig. 1
Health-related quality of life (HRQOL) represented by the EQ-5D-5 L™ items. Basic measurement model of the latent construct of HRQOL with model fit and standardised parameter estimates calculated using the maximum likelihood and asymptotic distribution-free methods (in parentheses). E1 - e5 = residual variation
Fig. 2
Fig. 2
EQ-5D-5 L™ parameters and general health status. The association of the EQ-5D-5 L™ VAS (a), and the German and the British crosswalk index of the EQ-5D-5 L™ (b) with the SF-36 measure of general health
Fig. 3
Fig. 3
Essential influence factors on health-related quality of life (HRQOL) represented by the EQ-5D-5 L™ items. For the variables physical activity and psychosocial distress adjusted model of the latent construct of HRQOL with standardised parameter estimates calculated with the ML method. N = 3064; e1 - e6 = residual variation
Fig. 4
Fig. 4
Essential influence factors on health-related quality of life represented by the EQ-5D-5L™ VAS and indices. The association of the EQ-5D-5L™ VAS (a) (c), and the German and the British crosswalk index of the EQ-5D-5L™ (b) (d) with physical activity and psychosocial distress
Fig. 5
Fig. 5
Discriminative ability indicated by the severity of heart failure according to the NYHA classes. The discriminative ability of the five EQ-5D-5L™ questions (a) (b) (c) (d) (e), the EQ-5D-5L™ VAS (f), and the German and the British EQ-5D-5L™ crosswalk index (g), respectively

References

    1. Sturm HB, van Gilst WH, Swedberg K, Hobbs FR, Haaijer-Ruskamp FM. Heart failure guidelines and prescribing in primary care across Europe. BMC Health Serv Res. 2005;5. 10.1186/1472-6963-5-57.
    1. Muntwyler J, Cohen-Solal A, Freemantle N, Eastaugh J, Cleland JG, Follath F. Relation of sex, age and concomitant diseases to drug prescription for heart failure in primary care in Europe. Eur J Heart Fail. 2004;6:663–668. doi: 10.1016/j.ejheart.2004.03.011.
    1. McDonald MA, Ashley EA, Fedak PWM, Hawkins N, Januzzi JL, McMurray JJV, et al. Mind the gap: current challenges and future state of heart failure care. Can J Cardiol. 2017;33:1434–1449. doi: 10.1016/j.cjca.2017.08.023.
    1. Ponikowski P, Voors AA, Anker SD, Bueno H, Cleland JGF, Coats AJS, et al. 2016 ESC guidelines for the diagnosis and treatment of acute and chronic heart failure:- web addenda. The task force for the diagnosis and treatment of acute and chronic heart failure of the European Society of Cardiology (ESC). Developed with the special contribution of the heart failure association (HFA) of the ESC. Eur J Heart Fail. 2016;18:891–975. doi: 10.1002/ejhf.592.
    1. Bundesärztekammer (BÄK), Kassenärztliche Bundesvereinigung (KBV), Arbeitsgemeinschaft der Wissenschaftlichen Medizinischen Fachgesellschaften (AWMF). Nationale VersorgungsLeitlinie Chronische Herzinsuffizienz. 2009. . Accessed 1 Nov 2017.
    1. Hunt SA, Baker DW, Chin MH, Cinquegrani MP, Feldman AM, Francis GS, et al. ACC/AHA guidelines for the evaluation and management of chronic heart failure in the adult: executive summary: A report of the american college of cardiology/american heart association task force on practice guidelines (committee to revise the 1995 guidelines for the evaluation and management of heart failure) developed in collaboration with the international society for heart and lung transplantation endorsed by the heart failure society of america. J Am Coll Cardiol. 2001;38:2101–2113. doi: 10.1016/S0735-1097(01)01683-7.
    1. Gasperoni F, Ieva F, Barbati G, Scagnetto A, Iorio A, Sinagra G, et al. Multi-state modelling of heart failure care path: a population-based investigation from Italy. PLoS One. 2017;12:e0179176. doi: 10.1371/journal.pone.0179176.
    1. Brunner-La Rocca H-P, Rickenbacher P, Muzzarelli S, Schindler R, Maeder MT, Jeker U, et al. End-of-life preferences of elderly patients with chronic heart failure. Eur Heart J. 2012;33:752–759. doi: 10.1093/eurheartj/ehr404.
    1. Tschöpe C, Birner C, Böhm M, Bruder O, Frantz S, Luchner A, et al. Heart failure with preserved ejection fraction: current management and future strategies. Clin Res Cardiol. 2018;107:1–19. doi: 10.1007/s00392-017-1170-6.
    1. Jaarsma T, Halfens R, Abu-Saad HH, Dracup K, Stappers J, Ree J. Quality of life in older patients with systolic and diastolic heart failure. Eur J Heart Fail. 1999;1:151–160. doi: 10.1016/S1388-9842(99)00007-0.
    1. Whellan DJ, O’Connor CM, Lee KL, Keteyian SJ, Cooper LS, Ellis SJ, et al. Heart failure and a controlled trial investigating outcomes of exercise TraiNing (HF-ACTION): design and rationale. Am Heart J. 2007;153:201–211. doi: 10.1016/j.ahj.2006.11.007.
    1. Stamp KD, Dunbar SB, Clark PC, Reilly CM, Gary RA, Higgins M, et al. Family context influences psychological outcomes of depressive symptoms and emotional quality of life in patients with heart failure. J Cardiovasc Nurs. 2014;29:517–527. doi: 10.1097/JCN.0000000000000097.
    1. Hoekstra T, Jaarsma T, Veldhuisen DJ, Hillege HL, Sanderman R, Lesman-Leegte I. Quality of life and survival in patients with heart failure. Eur J Heart Fail. 2013;15:94–102. doi: 10.1093/eurjhf/hfs148.
    1. Rector TS, Carson PE, Anand IS, McMurray JJ, Zile MR, McKelvie RS, et al. Assessment of long-term effects of Irbesartan on heart failure with preserved ejection fraction as measured by the Minnesota living with heart failure questionnaire in the Irbesartan in heart failure with preserved systolic function (I-PRESERVE) trial. Circ Heart Fail. 2012;5:217. doi: 10.1161/CIRCHEARTFAILURE.111.964221.
    1. The EuroQol Group. EQ-5D-5L | About. 2017. . Accessed 26 Oct 2017.
    1. Clouth J, Brähler E, Schmidt P, Kohlmann T. Testing construct validity of EQ-5D by Confirmatory Factor Analysis and Structural Equation Modeling (SEM). In: Baveno 2008 EuroQol Proceedings. 2008. . Accessed 24 Aug 2016.
    1. Robert Koch-Institut, editor. Gesundheit in Deutschland. Gesundheitsberichterstattung des Bundes. Gemeinsam getragen von RKI und Destatis. Berlin: Robert Koch-Institut; 2015.
    1. Herdman M, Gudex C, Lloyd A, Janssen MF, Kind P, Parkin D, et al. Development and preliminary testing of the new five-level version of EQ-5D (EQ-5D-5L) Qual Life Res. 2011;20:1727–1736. doi: 10.1007/s11136-011-9903-x.
    1. EuroQol Group. EQ-5D-5L. FAQs. . Accessed 16 Jan 2018.
    1. van Hout B, Janssen MF, Feng Y-S, Kohlmann T, Busschbach J, Golicki D, et al. Interim scoring for the EQ-5D-5L: mapping the EQ-5D-5L to EQ-5D-3L value sets. Value Health. 2012;15:708–715. doi: 10.1016/j.jval.2012.02.008.
    1. Charlson ME, Pompei P, Ales KL, MacKenzie CR. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis. 1987;40. 10.1016/0021-9681(87)90171-8.
    1. Schermelleh-Engel K, Moosbrugger H, Müller H. Evaluating the fit of structural equation models: test of significance and descriptive goodness-of-fit measures. Methods Psychol Res - Online. 2003;8(2):23–74.
    1. Olsson UH, Foss T, Troye SV, Howell RD. The performance of ML, GLS, and WLS estimation in structural equation modeling under conditions of misspecification and nonnormality. Struct Equ Model Multidiscip J. 2000;7:557–595. doi: 10.1207/S15328007SEM0704_3.
    1. Wirtz M. Einführung in die Analyse von Strukturgleichungsmodellen mit AMOS. 2016.
    1. Kline R. Principles and practice of structural equation modeling. 3. New York: Guilford Publications; 2011.
    1. Hooper D, Coughlan J, Mullen M. Structural equation Modelling: guidelines for determining model fit. Electron J Bus Res Methods. 2008;6(1):53–60.
    1. Sousa KH, Kwok O-M. Putting Wilson and Cleary to the test: analysis of a HRQOL conceptual model using structural equation modeling. Qual Life Res. 2006;15:725–737. doi: 10.1007/s11136-005-3975-4.
    1. Tran U. Effektstärken und deren Bedeutung für die klinische Forschung. 2011. . Accessed 29 Jul 2017.
    1. Richardson JTE. Eta squared and partial eta squared as measures of effect size in educational research. Educ Res Rev. 2011;6:135–147. doi: 10.1016/j.edurev.2010.12.001.
    1. Salazar A, Dueñas M, Fernandez-Palacin F, Failde I. Factors related to the evolution of health related quality of life in coronary patients. A longitudinal approach using weighted generalized estimating equations with missing data. Int J Cardiol. 2016;223:940–946. doi: 10.1016/j.ijcard.2016.08.300.
    1. Scherer M, Himmel W, Stanske B, Scherer F, Koschack J, Kochen MM, et al. Psychological distress in primary care patients with heart failure: a longitudinal study. Br J Gen Pract. 2007;57:801.
    1. Eisele M, Rakebrandt A, Boczor S, Kazek A, Pohontsch N, Okolo-Kulak M, et al. Factors associated with general practitioners’ awareness of depression in primary care patients with heart failure: baseline-results from the observational RECODE-HF study. BMC Fam Pract. 2017;18. 10.1186/s12875-017-0641-1.
    1. Spitzer RL, Kroenke K, Williams JB. Validation and utility of a self-report version of PRIME-MD: the PHQ primary care study. Primary Care Evaluation of Mental Disorders. Patient health questionnaire. JAMA. 1999;282. 10.1001/jama.282.18.1737.
    1. Kroenke K, Spitzer RL, Williams JB. The PHQ-9: validity of a brief depression severity measure. J Gen Intern Med. 2001;16. 10.1046/j.1525-1497.2001.016009606.x.
    1. Löwe B, Gräfe K, Zipfel S, Witte S, Loerch B, Herzog W. Diagnosing ICD-10 depressive episodes: superior criterion validity of the patient health questionnaire. Psychother Psychosom. 2004;73. 10.1159/000080393.
    1. Bjelland I, Dahl AA, Haug TT, Neckelmann D. The validity of the hospital anxiety and depression scale: an updated literature review. J Psychosom Res. 2002;52:69–77. doi: 10.1016/S0022-3999(01)00296-3.
    1. Herrmann-Lingen C, Buss U, Snaith R. HADS-D - hospital anxiety and depression scale - deutsche version: deutsche adaptation der Hospital anxiety and depression scale (HADS) Bern: Huber; 2005.
    1. Pilkonis PA, Choi SW, Reise SP, Stover AM, Riley WT, Cella D. Item banks for measuring emotional distress from the patient-reported outcomes measurement information system (PROMIS®): depression, anxiety, and anger. Assessment. 2011;18. 10.1177/1073191111411667.
    1. Choi SW, Reise SP, Pilkonis PA, Hays RD, Cella D. Efficiency of static and computer adaptive short forms compared to full-length measures of depressive symptoms. Qual Life Res. 2010;19. 10.1007/s11136-009-9560-5.
    1. Frost MH, Reeve BB, Liepa AM, Stauffer JW, Hays RD. What is sufficient evidence for the reliability and validity of patient-reported outcome measures? Value Health. 2007;10:S94–105. doi: 10.1111/j.1524-4733.2007.00272.x.
    1. National Institute for Health and Care Excellence. Position statement on use of the EQ-5D-5L valuation set. . Accessed 23 Oct 2017.
    1. EuroQol Group. NICE position statement on the EQ-5D-5L. 2017. . Accessed 23 Oct 2017.
    1. Eisele M, Blozik E, Störk S, Träder J-M, Herrmann-Lingen C, Scherer M. Recognition of depression and anxiety and their association with quality of life, hospitalization and mortality in primary care patients with heart failure – study protocol of a longitudinal observation study. BMC Fam Pract. 2013;14:180. doi: 10.1186/1471-2296-14-180.
    1. Steinbüchel T. Psychometrische Prüfung der deutschen Version des Kansas City Cardiomyopathy Questionnaire (KCCQ) - Unter Berücksichtigung des Einflusses einer komobiden Depression auf die Validität. Albert-Ludwigs-Universität Freiburg, Wirtschafts- und Verhaltenswissenschaftliche Fakultät unter Beteiligung des Instituts für Psychologie; 2005. . Accessed 2 Feb 2017.
    1. Scherer M, Stanske B, Wetzel D, Koschack J, Kochen MM, Herrmann-Lingen C. Psychosocial co-symptoms in primary care patients with heart failure. Herz. 2006;31:347–354. doi: 10.1007/s00059-006-2742-9.
    1. Eisele M, Boczor S, Rakebrandt A, Blozik E, Träder J-M, Störk S, et al. General practitioners’ awareness of depressive symptomatology is not associated with quality of life in heart failure patients – cross-sectional results of the observational RECODE-HF study. BMC Fam Pract. 2017;18:100. doi: 10.1186/s12875-017-0670-9.

Source: PubMed

Sponsors and Collaborators

Medical Conditions

Drug Interventions

3
Subscribe