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Health and Quality of Life Outcomes
Published in: Health and Quality of Life Outcomes 1/2021

Open Access 01-12-2021 | Research

Validity and responsiveness of EQ-5D-5L and SF-6D in patients with health complaints attributed to their amalgam fillings: a prospective cohort study of patients undergoing amalgam removal

Authors: Admassu N. Lamu, Lars Björkman, Harald J. Hamre, Terje Alræk, Frauke Musial, Bjarne Robberstad

Published in: Health and Quality of Life Outcomes | Issue 1/2021

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Abstract

Background

Evidence of health utility changes in patients who suffer from longstanding health complaints attributed to dental amalgam fillings are limited. The change in health utility outcomes enables calculating quality-adjusted life-year (QALY) and facilitates the comparison with other health conditions. The purpose of this study was to estimate the validity and responsiveness of the EQ-5D-5L and SF-6D utilities following removal of dental amalgam fillings in patients with health complaints attributed to their amalgam fillings, and examine the ability of these instruments to detect minimally important changes over time.

Methods

Patients with medically unexplained physical symptoms, which they attributed to dental amalgam restorations, were recruited to a prospective cohort study in Norway. Two health state utility instruments, EQ-5D-5L and SF-6D, as well as self-reported general health complaints (GHC-index) and visual analogue scale (EQ-VAS) were administered to all patients (n = 32) at baseline and at follow-up. The last two were used as criteria measures. Concurrent and predictive validities were examined using correlation coefficients. Responsiveness was assessed by the effect size (ES), standardized response mean (SRM), and relative efficiency. Minimally important change (MIC) was examined by distribution and anchor-based approaches.

Results

Concurrent validity of the EQ-5D-5L was similar to that of SF-6D utility. EQ-5D-5L was more responsive than SF-6D: the ES were 0.73 and 0.58 for EQ-5D-5L and SF-6D, respectively; SRM were 0.76 and 0.67, respectively. EQ-5D-5L was more efficient than SF-6D in detecting changes, but both were less efficient compared to criteria-based measures. The estimated MIC of EQ-5D-5L value set was 0.108 and 0.118 based on distribution and anchor-based approaches, respectively. The corresponding values for SF-6D were 0.048 and 0.064, respectively.

Conclusions

In patients with health complaints attributed to dental amalgam undergoing amalgam removal, both EQ-5D-5L and SF-6D showed reasonable concurrent and predictive validity and acceptable responsiveness. The EQ-5D-5L utility appears to be more responsive compared to SF-6D.
Trial registration The research was registered at ClinicalTrials.gov., NCT01682278. Registered 10 September 2012, https://​clinicaltrials.​gov/​ct2/​show/​NCT01682278.
Footnotes
1
EQ-5D-5L was available after registration at EuroQol Group http://​www.​euroqol.​org.
 
2
SF-6D was available after registering at University of Sheffield https://​licensing.​sheffield.​ac.​uk/​product/​SF-6D.
 
Literature
1.
Bates MN. Mercury amalgam dental fillings: an epidemiologic assessment. Int J Hyg Environ Health. 2006;209(4):309–16.PubMedCrossRef
2.
Kristoffersen AE, Musial F, Hamre HJ, Björkman L, Stub T, Salamonsen A, Alræk T. Use of complementary and alternative medicine in patients with health complaints attributed to former dental amalgam fillings. BMC Complement Altern Med. 2016;16:22.PubMedPubMedCentralCrossRef
3.
Melchart D, Vogt S, Kohler W, Streng A, Weidenhammer W, Kremers L, Hickel R, Felgenhauer N, Zilker T, Wuhr E, Halbach S. Treatment of health complaints attributed to amalgam. J Dent Res. 2008;87(4):349–53.PubMedCrossRef
4.
Drummond MF, Sculpher MJ, Claxton K, Stoddart GL, Torrance GW. Methods for the economic evaluation of health care programmes. Oxford: Oxford University Press; 2015.
5.
Whitehead SJ, Ali S. Health outcomes in economic evaluation: the QALY and utilities. Br Med Bull. 2010;96(1):5–21.PubMedCrossRef
6.
7.
Brazier J, Roberts J, Deverill M. The estimation of a preference-based measure of health from the SF-36. J Health Econ. 2002;21(2):271–92.PubMedCrossRef
8.
Olsen JA, Lamu AN, Cairns J. In search of a common currency: a comparison of seven EQ-5D-5L value sets. Health Econ. 2018;27(1):39–49.PubMedCrossRef
9.
Herdman M, Gudex C, Lloyd A, Janssen M, Kind P, Parkin D, Bonsel G, Badia X. Development and preliminary testing of the new five-level version of EQ-5D (EQ-5D-5L). Qual Life Res. 2011;20(10):1727–36.PubMedPubMedCentralCrossRef
10.
11.
NICE. Methods for the development of NICE Public Health Guidance: NICE process and methods guides. 3rd ed. London: National Institute for Health and Care Excellence (NICE); 2012.
12.
NoMA. Guidelines for the submission of documentation for single technology assessment (STA) of pharmaceuticals. Oslo: The Norwegian Medicines Agency (NoMA). 2020. https://​legemiddelverket​.​no/​. Accessed 10 June 2020.
13.
van Hout B, Janssen MF, Feng Y-S, Kohlmann T, Busschbach J, Golicki D, Lloyd A, Scalone L, Kind P, Pickard AS. Interim scoring for the EQ-5D-5L: mapping the EQ-5D-5L to EQ-5D-3L value sets. Value Health. 2012;15(5):708–15.PubMedCrossRef
14.
Kennedy-Martin M, Slaap B, Herdman M, van Reenen M, Kennedy-Martin T, Greiner W, Busschbach J, Boye KS. Which multi-attribute utility instruments are recommended for use in cost-utility analysis? A review of national health technology assessment (HTA) guidelines. Eur J Health Econ. 2020;21(8):1245–57.PubMedPubMedCentralCrossRef
15.
Wisløff T, Hagen G, Hamidi V, Movik E, Klemp M, Olsen JA. Estimating QALY gains in applied studies: a review of cost-utility analyses published in 2010. Pharmacoeconomics. 2014;32(4):367–75.PubMedPubMedCentralCrossRef
16.
Feng Y-S, Kohlmann T, Janssen MF, Buchholz I. Psychometric properties of the EQ-5D-5L: a systematic review of the literature. Qual Life Res. 2020;30:647–73.PubMedPubMedCentralCrossRef
17.
Feng Y, Devlin N, Herdman M. Assessing the health of the general population in England: how do the three- and five-level versions of EQ-5D compare? Health Qual Life Outcomes. 2015;13:171.PubMedPubMedCentralCrossRef
18.
Hernandez G, Garin O, Pardo Y, Vilagut G, Pont À, Suárez M, Neira M, Rajmil L, Gorostiza I, Ramallo-Fariña Y, et al. Validity of the EQ-5D-5L and reference norms for the Spanish population. Qual Life Res. 2018;27(9):2337–48.PubMedCrossRef
19.
Hinz A, Kohlmann T, Stöbel-Richter Y, Zenger M, Brähler E. The quality of life questionnaire EQ-5D-5L: psychometric properties and normative values for the general German population. Qual Life Res. 2014;23(2):443–7.PubMedCrossRef
20.
21.
Craig BM, Pickard AS, Lubetkin EI. Health problems are more common, but less severe when measured using newer EQ-5D versions. J Clin Epidemiol. 2014;67(1):93–9.PubMedCrossRef
22.
Agborsangaya CB, Lahtinen M, Cooke T, Johnson JA. Comparing the EQ-5D 3L and 5L: measurement properties and association with chronic conditions and multimorbidity in the general population. Health Qual Life Outcomes. 2014;12(1):74.PubMedPubMedCentralCrossRef
23.
Campolina AG, López RVM, Nardi EP, Ferraz MB. Internal consistency of the SF-6D as a health status index in the Brazilian urban population. Value Health Reg Issues. 2018;17:74–80.PubMedCrossRef
24.
Luo N, Wang P, Fu AZ, Johnson JA, Coons SJ. Preference-based SF-6D scores derived from the SF-36 and SF-12 have different discriminative power in a population health survey. Med Care. 2012;50(7):627–32.PubMedCrossRef
25.
Baxter S, Sanderson K, Venn A, Otahal P, Palmer AJ. Construct validity of SF-6D health state utility values in an employed population. Qual Life Res. 2015;24(4):851–70.PubMedCrossRef
26.
Kangwanrattanakul K. A comparison of measurement properties between UK SF-6D and English EQ-5D-5L and Thai EQ-5D-5L value sets in general Thai population. Expert Rev Pharmacoecon Outcomes Res. 2020;1–10.
27.
Shiroiwa T, Fukuda T, Ikeda S, Igarashi A, Noto S, Saito S, Shimozuma K. Japanese population norms for preference-based measures: EQ-5D-3L, EQ-5D-5L, and SF-6D. Qual Life Res. 2016;25(3):707–19.PubMedCrossRef
28.
Zhao L, Liu X, Liu D, He Y, Liu Z, Li N. Comparison of the psychometric properties of the EQ-5D-3L and SF-6D in the general population of Chengdu city in China. Medicine. 2019;98(11):e14719.PubMedPubMedCentralCrossRef
29.
Brazier J, Connell J, Papaioannou D, Mukuria C, Mulhern B, Peasgood T, Jones ML, Paisley S, O’Cathain A, Barkham M, et al. A systematic review, psychometric analysis and qualitative assessment of generic preference-based measures of health in mental health populations and the estimation of mapping functions from widely used specific measures. Health Technol Assess. 2014;18(34):1–188.PubMedPubMedCentralCrossRef
30.
Brazier J, Roberts J, Tsuchiya A, Busschbach J. A comparison of the EQ-5D and SF-6D across seven patient groups. Health Econ. 2004;13(9):873–84.PubMedCrossRef
31.
Chen P, Lin KC, Liing RJ, Wu CY, Chen CL, Chang KC. Validity, responsiveness, and minimal clinically important difference of EQ-5D-5L in stroke patients undergoing rehabilitation. Qual Life Res. 2016;25(6):1585–96.PubMedCrossRef
32.
Engel L, Bryan S, Evers SMAA, Dirksen CD, Noonan VK, Whitehurst DGT. Exploring psychometric properties of the SF-6D, a preference-based health-related quality of life measure, in the context of spinal cord injury. Qual Life Res. 2014;23(8):2383–93.PubMedCrossRef
33.
Goodwin PC, Ratcliffe J, Morris J, Morrissey MC. Using the knee-specific Hughston Clinic Questionnaire, EQ-5D and SF-6D following arthroscopic partial meniscectomy surgery: a comparison of psychometric properties. Qual Life Res. 2011;20(9):1437–46.PubMedCrossRef
34.
Khanna D, Furst DE, Wong WK, Tsevat J, Clements PJ, Park GS, Postlethwaite AE, Ahmed M, Ginsburg S, Hays RD, Ron D. Hays for the Scleroderma Collagen Type 1 Study Group. Reliability, validity, and minimally important differences of the SF-6D in systemic sclerosis. Qual Life Res. 2007;16(6):1083–92.PubMedCrossRef
35.
Mulhern B, Meadows K. The construct validity and responsiveness of the EQ-5D, SF-6D and Diabetes Health Profile-18 in type 2 diabetes. Health Qual Life Outcomes. 2014;12:42.PubMedPubMedCentralCrossRef
36.
Obradovic M, Lal A, Liedgens H. Validity and responsiveness of EuroQol-5 dimension (EQ-5D) versus Short Form-6 dimension (SF-6D) questionnaire in chronic pain. Health Qual Life Outcomes. 2013;11:110.PubMedPubMedCentralCrossRef
37.
Glossary. Health outcomes methodology. Med Care. 2000;38(9):II7–13.
38.
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(6):1523–32.PubMedCrossRef
39.
Hagg O, Fritzell P, Nordwall A. The clinical importance of changes in outcome scores after treatment for chronic low back pain. Eur Spine J. 2003;12(1):12–20.PubMedCrossRef
40.
Juniper EF, Guyatt GH, Willan A, Griffith LE. Determining a minimal important change in a disease-specific Quality of Life Questionnaire. J Clin Epidemiol. 1994;47(1):81–7.PubMedCrossRef
41.
Jaeschke R, Singer J, Guyatt GH. Measurement of health status. Ascertaining the minimal clinically important difference. Control Clin Trials. 1989;10(4):407–15.PubMedCrossRef
42.
Bhadhuri A, Jowett S, Jolly K, Al-Janabi H. A comparison of the validity and responsiveness of the EQ-5D-5L and SF-6D for measuring health spillovers: a study of the family impact of meningitis. Med Decis Making. 2017;37(8):882–93.PubMedCrossRef
43.
Harrison MJ, Davies LM, Bansback NJ, McCoy MJ, Verstappen SMM, Watson K, Symmons DPM, The British Society for Rheumatology Biologics Register Control Centre Consortium, on behalf of the BSRBR. The comparative responsiveness of the EQ-5D and SF-6D to change in patients with inflammatory arthritis. Qual Life Res. 2009;18(9):1195–205.PubMedPubMedCentralCrossRef
44.
Nolan CM, Longworth L, Lord J, Canavan JL, Jones SE, Kon SS, Man WD. The EQ-5D-5L health status questionnaire in COPD: validity, responsiveness and minimum important difference. Thorax. 2016;71(6):493–500.PubMedCrossRef
45.
Björkman L, Musial F, Alraek T, Werner EL, Weidenhammer W, Hamre HJ. Removal of dental amalgam restorations in patients with health complaints attributed to amalgam: a prospective cohort study. J Oral Rehabil. 2020;47(11):1422–34.PubMedCrossRef
46.
Stavem K, Augestad LA, Kristiansen IS, Rand K. General population norms for the EQ-5D-3L in Norway: comparison of postal and web surveys. Health Qual Life Outcomes. 2018;16(1):204.PubMedPubMedCentralCrossRef
47.
48.
Devlin NJ, Shah KK, Feng Y, Mulhern B, van Hout B. Valuing health-related quality of life: an EQ-5D-5L value set for England. Health Econ. 2018;27(1):7–22.PubMedCrossRef
49.
Brazier JE, Roberts J. The estimation of a preference-based measure of health from the SF-12. Med Care. 2004;42(9):851–9.PubMedCrossRef
50.
Loge HJ, Kaasa S. Short Form 36 (SF-36) health survey: normative data from the general Norwegian population. Scand J Soc Med. 1998;26(4):250–8.PubMedCrossRef
51.
Jacobsen EL, Bye A, Aass N, Fosså SD, Grotmol KS, Kaasa S, Loge JH, Moum T, Hjermstad MJ. Norwegian reference values for the Short-Form Health Survey 36: development over time. Qual Life Res. 2018;27(5):1201–12.PubMedCrossRef
52.
Sjursen TT, Lygre GB, Dalen K, Helland V, LæGreid T, Svahn J, Lundekvam BF, Björkman L. Changes in health complaints after removal of amalgam fillings. J Oral Rehabil. 2011;38(11):835–48.PubMedPubMedCentralCrossRef
53.
Kaplan MS, Berthelot JM, Feeny D, McFarland BH, Khan S, Orpana H. The predictive validity of health-related quality of life measures: mortality in a longitudinal population-based study. Qual Life Res. 2007;16(9):1539–46.PubMedCrossRef
54.
Cronbach LJ, Meehl PE. Construct validity in psychological tests. Psychol Bull. 1955;52(4):281–302.PubMedCrossRef
55.
Kazis LE, Anderson JJ, Meenan RF. Effect sizes for interpreting changes in health status. Med Care. 1989;27(3 Suppl):S178-189.PubMedCrossRef
56.
Cohen J. Statistical power analysis for the behavioral sciences. Hillsdale, NJ: Lawrence Erlbaum Associates; 1988.
57.
Beaton DE, Hogg-Johnson S, Bombardier C. Evaluating changes in health status: reliability and responsiveness of five generic health status measures in workers with musculoskeletal disorders. J Clin Epidemiol. 1997;50(1):79–93.PubMedCrossRef
58.
Crosby RD, Kolotkin RL, Williams GR. Defining clinically meaningful change in health-related quality of life. J Clin Epidemiol. 2003;56(5):395–407.PubMedCrossRef
59.
de Vet HC, Terwee CB. The minimal detectable change should not replace the minimal important difference. J Clin Epidemiol. 2010;63(7):804–5.PubMedCrossRef
60.
de Vet HC, Terwee CB, Ostelo RW, Beckerman H, Knol DL, Bouter LM. Minimal changes in health status questionnaires: distinction between minimally detectable change and minimally important change. Health Qual Life Outcomes. 2006;4:54–54.PubMedPubMedCentralCrossRef
61.
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(5):582–92.PubMedCrossRef
62.
Le QA, Doctor JN, Zoellner LA, Feeny NC. Minimal clinically important differences for the EQ-5D and QWB-SA in Post-traumatic Stress Disorder (PTSD): results from a Doubly Randomized Preference Trial (DRPT). Health Qual Life Outcomes. 2013;11:59.PubMedPubMedCentralCrossRef
63.
Terluin B, Eekhout I, Terwee CB, de Vet HCW. Minimal important change (MIC) based on a predictive modeling approach was more precise than MIC based on ROC analysis. J Clin Epidemiol. 2015;68(12):1388–96.PubMedCrossRef
64.
Mehta CR, Patel NR. Exact logistic regression: theory and examples. Stat Med. 1995;14(19):2143–60.PubMedCrossRef
65.
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):102–9.PubMedCrossRef
66.
Golicki D, Niewada M, Karlinska A, Buczek J, Kobayashi A, Janssen MF, Pickard AS. Comparing responsiveness of the EQ-5D-5L, EQ-5D-3L and EQ VAS in stroke patients. Qual Life Res. 2015;24(6):1555–63.PubMedCrossRef
67.
Barnett AG, van der Pols JC, Dobson AJ. Regression to the mean: what it is and how to deal with it. Int J Epidemiol. 2005;34(1):215–20.PubMedCrossRef
68.
69.
Lamu AN, Gamst-Klaussen T, Olsen JA. Preference weighting of health state values: what difference does it make, and why? Value in Health. 2017;20(3):451–7.PubMedCrossRef
70.
Grieve R, Grishchenko M, Cairns J. SF-6D versus EQ-5D: reasons for differences in utility scores and impact on reported cost-utility. Eur J Health Econ. 2009;10(1):15–23.PubMedCrossRef
71.
Pickard AS, Wang Z, Walton SM, Lee TA. Are decisions using cost-utility analyses robust to choice of SF-36/SF-12 preference-based algorithm? Health Qual Life Outcomes. 2005;3:11.PubMedPubMedCentralCrossRef
72.
73.
Cunillera O, Tresserras R, Rajmil L, Vilagut G, Brugulat P, Herdman M, Mompart A, Medina A, Pardo Y, Alonso J, et al. Discriminative capacity of the EQ-5D, SF-6D, and SF-12 as measures of health status in population health survey. Qual Life Res. 2010;19(6):853–64.PubMedCrossRef
74.
Copay AG, Subach BR, Glassman SD, Polly DW Jr, Schuler TC. Understanding the minimum clinically important difference: a review of concepts and methods. Spine J. 2007;7(5):541–6.PubMedCrossRef
Metadata
Title
Validity and responsiveness of EQ-5D-5L and SF-6D in patients with health complaints attributed to their amalgam fillings: a prospective cohort study of patients undergoing amalgam removal
Authors
Admassu N. Lamu
Lars Björkman
Harald J. Hamre
Terje Alræk
Frauke Musial
Bjarne Robberstad
Publication date
01-12-2021
Publisher
BioMed Central
Published in
Health and Quality of Life Outcomes / Issue 1/2021
Electronic ISSN: 1477-7525
DOI
https://doi.org/10.1186/s12955-021-01762-4

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