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Quality of Life Research

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28-06-2021 | Review

Evidence on the relationship between PROMIS-29 and EQ-5D: a literature review

Auteurs: Tianxin Pan, Brendan Mulhern, Rosalie Viney, Richard Norman, An Tran-Duy, Janel Hanmer, Nancy Devlin

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

Abstract

Purpose

EQ-5D and PROMIS-29 are both concise, generic measures of patient-reported outcomes accompanied by preference weights that allow the estimation of quality-adjusted life years (QALYs). Both instruments are candidates for use in economic evaluation. However, they have different features in terms of the domains selected to measure respondents’ self-perceived health and the characteristics of (and methods used to obtain) the preference weights. It is important to understand the relationship between the instruments and the implications of choosing either for the evidence used in decision-making. This literature review aimed to synthesise existing evidence on the relationship between PROMIS-29 (and measures based on it, such as PROMIS-29+2) and EQ-5D (both EQ-5D-3L and EQ-5D-5L).

Methods

A literature review was conducted in PubMed and Web of Science to identify studies investigating the relationship between PROMIS-29 and EQ-5D-based instruments.

Results

The literature search identified 95 unique studies, of which nine studies met the inclusion criteria, i.e. compared both instruments. Six studies examined the relationship between PROMIS-29 and EQ-5D-5L. Three main types of relationship have been examined in the nine studies: (a) comparing PROMIS-29 and EQ-5D as descriptive systems; (b) mapping PROMIS-29 domains to EQ-5D utilities; and (c) comparing and transforming PROMIS-29 utilities to EQ-5D utilities.

Conclusion

This review has highlighted the lack of evidence regarding the relationship between PROMIS-29 and EQ-5D. The impact of choosing either instrument on the evidence used in cost-effectiveness analysis is currently unclear. Further research is needed to understand the relationship between the two instruments.

vorige artikel Non-parametric measurement for patient-reported outcomes

volgende artikel The influence of psychosocial factors on patient-reported outcome measures in rotator cuff tears pre- and post-surgery: a systematic review

For example, EQ-5D uses “dimension” to describe key components of self-perceived health, whereas the corresponding term in PROMIS measures is “domain”. For more detail on the differences in terms and descriptions, see Pan et al. [11‐13].

PROMIS-29-based instruments refer to PROMIS-29 and measures based on it, such as PROMIS-29 v1.0, PROMIS-29 v2.0, PROMIS-29+2 v2.1. PROMIS-29+2 v2.1 is the recommended instrument to calculate PROPr scores, which consist of the PROMIS-29 and two items from Cognitive Function-Abilities v2.0 [24]. EQ-5D instruments include EQ-5D-3L and EQ-5D-5L.

It is worth noting that there is one ongoing study uses item response theory to create a crosswalk to the EQ-5D-5L from PROMIS-29 domains [25]. After confirming with the authors, only abstract was available at this stage. Also, we identified two further studies which compared EQ-5D-5L utilities with PROPr utilities. However, the author did not use PROMIS-29 to calculate PROPr scores but administered 14 questions (2 for each PROPr domains) to respondents. Detailed information on the questions was not reported. Thus the two studies were not included in our literature review. For more information, please refer to [26, 27].

It is worth noting that the coefficient for Physical Function is positive, whereas the other coefficients are negative. This is because in PROMIS system, for positively worded concepts like Physical Function, higher domain raw scores and T-scores represent better health; negatively worded concepts like Anxiety and Pain, lower scores indicate better health.

Hartman et al. (2018) used a DCE value set for PROMIS-29 [9] and a TTO value set for EQ-5D-3L [29]; Hanmer et al. (2018) used PROPr and the EQ-5D crosswalk value set [32]. As we mentioned earlier, there are two studies that used 14 questions (i.e. not PROMIS-29) to calculate PROPr [26, 27], the authors compared PROPr with EQ-5D-5L utilities using the US value set for the latter [35].

In Hartman and Craig (2018), the authors tested four models: linear, non-linear power model, polynomial (quadratic and cubic), and two-part piecewise linear models and tested the goodness-to-fit for each model based on root mean square error (RMSE). Based on this criterion, the best fit was the non-linear power function as it had the smallest RMSE (0.0984).

The overlaps in the health domains in PROMIS-29 and EQ-5D are: Anxiety and Anxiety/Depression (the former being domains in PROMIS-29 and the latter being dimensions in EQ-5D); Depression and Anxiety/Depression; Pain Interference and Pain/Discomfort; Physical Function and Mobility; Social Roles and Usual Activities. There is no explicitly corresponding PROMIS-29 domains of Fatigue and Sleep Disturbance in EQ-5D, and no corresponding EQ-5D dimension of Self-care in PROMIS-29.

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.PubMedPubMedCentral

Feeny, D., Torrance, G., & Furlong, W. (1996). Health utilities index. Lippincott-Raven Press.

Horsman, J., Furlong, W., Feeny, D., & Torrance, G. (2003). The health utilities index (HUI): Concepts, measurement properties and applications. Health and Quality of Life Outcomes, 1, 54.PubMedPubMedCentral

Ware, J. E., Jr., & Sherbourne, C. D. (1992). The MOS 36-item short-form health survey (SF-36). I. Conceptual framework and item selection. Medical Care, 30(6), 473–483.PubMed

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.PubMed

Cella, D., Riley, W., Stone, A., Rothrock, N., Reeve, B., Yount, S., Amtmann, D., Bode, R., Buysse, D., Choi, S., Cook, K., Devellis, R., DeWalt, D., Fries, J. F., Gershon, R., Hahn, E. A., Lai, J. S., Pilkonis, P., Revicki, D., … Group P. C. (2010). The patient-reported outcomes measurement information system (PROMIS) developed and tested its first wave of adult self-reported health outcome item banks: 2005–2008. Journal of Clinical Epidemiology, 63(11), 1179–1194.PubMedPubMedCentral

Health Measures. (2020). List of Adult Measures. Retrieved 27 April, 2020, from http://www.healthmeasures.net/explore-measurement-systems/promis/intro-to-promis/list-of-adult-measures

Dewitt, B., Feeny, D., Fischhoff, B., Cella, D., Hays, R. D., Hess, R., Pilkonis, P. A., Revicki, D. A., Roberts, M. S., Tsevat, J., Yu, L., & Hanmer, J. (2018). Estimation of a preference-based summary score for the patient-reported outcomes measurement information system: The PROMIS((R))-Preference (PROPr) scoring system. Medical Decision Making, 38(6), 683–698.PubMedPubMedCentral

Craig, B. M., Reeve, B. B., Brown, P. M., Cella, D., Hays, R. D., Lipscomb, J., Simon Pickard, A., & Revicki, D. A. (2014). US valuation of health outcomes measured using the PROMIS-29. Value Health, 17(8), 846–853.PubMedPubMedCentral

10.

Kennedy-Martin, M., Slaap, B., Herdman, M., van Reenen, M., Kennedy-Martin, T., Greiner, W., Busschbach, J., & Boye, K. S. (2020). Which multi-attribute utility instruments are recommended for use in cost-utility analysis? A review of national health technology assessment (HTA) guidelines. The European Journal of Health Economics, 21(8), 1245–1257.PubMedPubMedCentral

11.

Pan, T., Mulhern, B., Viney, R., Norman, R., Hanmer, J., & Devlin, N. (2020). How do the utilities for PROMIS-29 and EQ-5D-5L compare? A comparison of PROPr and EQ-5D-5L value sets, and implications for users. In: 37th EuroQol scientific plenary meeting.

12.

EQ-5D. (2020). Terminology—EQ-5D. Retrieved 19 May, 2020, from https://euroqol.org/support/terminology/

13.

Health Measures. (2020). Glossary. Retrieved 19 May, 2002, from http://www.healthmeasures.net/resource-center/measurement-science/glossary

14.

Cella, D., Choi, S. W., Condon, D. M., Schalet, B., Hays, R. D., Rothrock, N. E., Yount, S., Cook, K. F., Gershon, R. C., Amtmann, D., DeWalt, D. A., Pilkonis, P. A., Stone, A. A., Weinfurt, K., & Reeve, B. B. (2019). PROMIS((R)) adult health profiles: efficient short-form measures of seven health domains. Value Health, 22(5), 537–544.PubMedPubMedCentral

15.

Tsuchiya, A., Brazier, J., & Roberts, J. (2006). Comparison of valuation methods used to generate the EQ-5D and the SF-6D value sets. Journal of Health Economics, 25, 334–346.PubMed

16.

Herdman, M., Gudex, C., Lloyd, A., Janssen, M., Kind, P., Parkin, D., Bonsel, G., & Badia, X. (2011). Development and preliminary testing of the new five-level version of EQ-5D (EQ-5D-5L). Quality of Life Research, 20(10), 1727–1736.PubMedPubMedCentral

17.

Devlin, N., Parkin, D., & Janssen, B. (2020). Methods for analysing and reporting EQ-5D data. Springer.

18.

Szende, A., Oppe, M., & Devlin, N. (2007). EQ-5D value sets: Inventory, comparative review and user guide. Springer.

19.

Oppe, M., Devlin, N. J., Hout, B., Krabbe, P. F. M., & Charro, F. (2014). A program of methodological research to arrive at the new international EQ-5D-5L valuation protocol. Value in Health, 17(4), 445–453.PubMed

20.

Norman, R., Cronin, P., & Viney, R. (2013). A pilot discrete choice experiment to explore preferences for EQ-5D-5L health states. Applied Health Economics and Health Policy, 11(3), 287–298.PubMed

21.

Dewitt, B., Jalal, H., & Hanmer, J. (2020). Computing PROPr utility scores for PROMIS® profile instruments. Value in Health, 23(3), 370–378.PubMed

22.

Brazier, J., Connell, J., Papaioannou, D., Mukuria, C., Mulhern, B., Peasgood, T., Jones, M. L., Paisley, S., O’Cathain, A., Barkham, M., Knapp, M., Byford, S., Gilbody, S., & Parry, G. (2014). 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 Technology Assessment, 18(34), vii–viii, xiii-xxv 1–188.

23.

Longworth, L., Yang, Y., Young, T., Mulhern, B., Hernandez-Alava, M., Mukuria, C., Rowen, D., Tosh, J., Tsuchiya, A., & Evans, P. (2014). Use of generic and condition specific measures of health related quality of life in NICE decision making: Systematic review, statistical modelling and survey. Health Technology Assessment, 18, 9.

24.

Health Measures. (2019). Preference-based Scores. Retrieved 10 March, 2020, from www.healthmeasures.net/score-and-interpret/calculate-scores/preference-based-scores

25.

Dewitt, B., Yu, L., & Hanmer, J. (2020). Using item response theory to estimate EQ-5D-5L utilities from PROMIS, Society for Medical Decision Making 42nd Annual Meeting. https://smdm.confex.com/smdm/2020/meetingapp.cgi/Paper/13540

26.

Hanmer, J., DeWalt, D. A., & Berkowitz, S. A. (2021). Association between food insecurity and health-related quality of life: A nationally representative survey. Journal of General Internal Medicine. https://doi.org/10.1007/s11606-020-06492-9CrossRefPubMedPubMedCentral

27.

Hanmer, J. (2020). Cross-sectional validation of the PROMIS-preference scoring system by its association with social determinants of health. Quality of Life Research. https://doi.org/10.1007/s11136-020-02691-3CrossRefPubMedPubMedCentral

28.

Revicki, D. A., Kawata, A. K., Harnam, N., Chen, W. H., Hays, R. D., & Cella, D. (2009). Predicting EuroQol (EQ-5D) scores from the patient-reported outcomes measurement information system (PROMIS) global items and domain item banks in a United States sample. Quality of Life Research, 18(6), 783–791.PubMedPubMedCentral

29.

Shaw, J. W., Johnson, J. A., & Coons, S. J. (2005). US valuation of the EQ-5D health states: Development and testing of the D1 valuation model. Medical Care, 43(3), 203–220.PubMed

30.

Hartman, J. D., & Craig, B. M. (2018). Comparing and transforming PROMIS utility values to the EQ-5D. Quality of Life Research, 27(3), 725–733.PubMed

31.

Hanmer, J., Dewitt, B., Yu, L., Tsevat, J., Roberts, M., Revicki, D., Pilkonis, P. A., Hess, R., Hays, R. D., Fischhoff, B., Feeny, D., Condon, D., & Cella, D. (2018). Cross-sectional validation of the PROMIS-preference scoring system. PLoS One, 13(7), e0201093.PubMedPubMedCentral

32.

The Economics Network. Available from: https://www.economicsnetwork.ac.uk/health/EQ_5D_index_calculator.xls. Retrieved 29 May, 2020.

33.

Khanna, D., Serrano, J., Berrocal, V. J., Silver, R. M., Cuencas, P., Newbill, S. L., Battyany, J., Maxwell, C., Alore, M., Dyas, L., Riggs, R., Connolly, K., Kellner, S., Fisher, J. J., Bush, E., Sachdeva, A., Evnin, L., Raisch, D. W., & Poole, J. L. (2019). Randomized controlled trial to evaluate an internet-based self-management program in systemic sclerosis. Arthritis Care & Research, 71(3), 435–447.

34.

Murphy, S. L., Whibley, D., Kratz, A. L., Poole, J. L., & Khanna, D. (2020). Fatigue predicts future reduced social participation, not reduced physical function or quality of life in people with systemic sclerosis. Journal of Scleroderma and Related Disorders. https://doi.org/10.1177/2397198320965383CrossRefPubMedPubMedCentral

35.

Pickard, A. S., Law, E. H., Jiang, R., Pullenayegum, E., Shaw, J. W., Xie, F., Oppe, M., Boye, K. S., Chapman, R. H., Gong, C. L., Balch, A., & Busschbach, J. J. V. (2019). United States valuation of EQ-5D-5L health states using an international protocol. Value Health, 22(8), 931–941.PubMed

36.

VandenWyngaert, K., Van Craenenbroeck, A. H., Eloot, S., Calders, P., Celie, B., Holvoet, E., & Van Biesen, W. (2020). Associations between the measures of physical function, risk of falls and the quality of life in haemodialysis patients: A cross-sectional study. BMC Nephrology, 21(1), 7.

37.

Dunn, S. L., DeVon, H. A., Buursma, M. P., Boven, E., & Tintle, N. L. (2020). Reliability and validity of the state-trait hopelessness scale in patients with heart disease and moderate to severe hopelessness. Journal of Cardiovascular Nursing, 35(2), 126–130.PubMed

38.

Klapproth, C. P., van Bebber, J., Sidey-Gibbons, C. J., Valderas, J. M., Leplege, A., Rose, M., & Fischer, F. (2020). Predicting EQ-5D-5L crosswalk from the PROMIS-29 profile for the United Kingdom, France, and Germany. Health and Quality of Life Outcomes, 18(1), 389.PubMedPubMedCentral

39.

van Hout, B., Janssen, M. F., Feng, Y.-S., Kohlmann, T., Busschbach, J., Golicki, D., Lloyd, A., Scalone, L., Kind, P., & Pickard, A. S. (2012). Interim scoring for the EQ-5D-5L: Mapping the EQ-5D-5L to EQ-5D-3L value sets. Value in Health, 15(5), 708–715.PubMed

40.

Kempton, C. L., Michaels Stout, M., Barry, V., Figueroa, J., Buckner, T. W., Gillespie, S., Ellen Lynch, M., Mattis, S., Whitten, S., & McCracken, C. (2021). Validation of a new instrument to measure disease-related distress among patients with haemophilia. Haemophilia, 27(1), 60–68.PubMed

41.

Yount, S. E., Cella, D., & Blozis, S. (2019). PROMIS(R): Standardizing the patient voice in health psychology research and practice. Health Psychology, 38(5), 343–346.PubMed

42.

Richardson, J., Iezzi, A., Khan, M. A., & Maxwell, A. (2014). Validity and reliability of the assessment of quality of life (AQoL)-8D multi-attribute utility instrument. Patient, 7(1), 85–96.PubMed

43.

Rowen, D., Brazier, J., Tsuchiya, A., & Alava, M. H. (2012). Valuing states from multiple measures on the same visual analogue sale: A feasibility study. Health Economics, 21(6), 715–729.PubMed

44.

Whitehurst, D. G., Bryan, S., & Lewis, M. (2011). Systematic review and empirical comparison of contemporaneous EQ-5D and SF-6D group mean scores. Medical Decision Making, 31(6), E34-44.PubMed

45.

Dakin, H., Abel, L., Burns, R., & Yang, Y. (2018). Review and critical appraisal of studies mapping from quality of life or clinical measures to EQ-5D: An online database and application of the MAPS statement. Health and Quality of Life Outcomes, 16(1), 31.PubMedPubMedCentral

46.

Whitehurst, D. G. T., Stirling, B., & Lewis, M. (2011). Systematic review and empirical comparison of contemporaneous EQ-5D and SF-6D group mean scores. Medical Decision Making, 31(6), E34-44.PubMed

47.

Thompson, A. J., & Turner, A. J. (2020). A Comparison of the EQ-5D-3L and EQ-5D-5L. Pharmacoeconomics. https://doi.org/10.1007/s40273-018-0623-8CrossRefPubMed

48.

Feng, Y., Devlin, N., & Herdman, M. (2015). Assessing the health of the general population in England: How do the three- and five-level versions of EQ-5D compare? Health and Quality of Life Outcomes, 13, 171.PubMedPubMedCentral

49.

Buchholz, I., Janssen, M. F., Kohlmann, T., & Feng, Y. S. (2018). A systematic review of studies comparing the measurement properties of the three-level and five-level versions of the EQ-5D. PharmacoEconomics, 36(6), 645–661.PubMedPubMedCentral

50.

Janssen, M. F., Pickard, A. S., Golicki, D., Gudex, C., Niewada, M., Scalone, L., Swinburn, P., & Busschbach, J. (2013). Measurement properties of the EQ-5D-5L compared to the EQ-5D-3L across eight patient groups: A multi-country study. Quality of Life Research, 22(7), 1717–1727.PubMed

51.

Janssen, M., Bonsel, G., & Luo, N. (2018). Is EQ-5D-5L better than EQ-5D-3L? A head-to-head comparison of descriptive systems and value sets from seven countries. Pharmacoeconomics. https://doi.org/10.1007/s40273-018-0623-8CrossRefPubMedPubMedCentral

52.

Agborsangaya, C. B., Lahtinen, M., Cooke, T., & Johnson, J. A. (2014). Comparing the EQ-5D 3L and 5L: Measurement properties and association with chronic conditions and multimorbidity in the general population. Health and Quality of Life Outcomes, 12, 74.PubMedPubMedCentral

53.

Klapproth, C. P., Leplege, A., Gibbons, C., Coste, J., Valderas, J. M., Rose, M., & Fischer, F. (2017). Predicting EQ-5D index scores from PROMIS Profile 29 in the United Kingdom, France, and Germany. Quality of Life Research, 26(1), 49–49.

54.

Thompson, N. R., Lapin, B. R., & Katzan, I. L. (2017). Mapping PROMIS global health items to EuroQol (EQ-5D) utility scores using linear and equipercentile equating. PharmacoEconomics, 35(11), 1167–1176.PubMed

55.

Mulhern, B., Feng, Y., Shah, K., Janssen, M. F., Herdman, M., van Hout, B., & Devlin, N. (2018). Comparing the UK EQ-5D-3L and English EQ-5D-5L value sets. PharmacoEconomics, 36(6), 699–713.PubMedPubMedCentral

56.

Health Measures. (2020). Available translations: PROMIS® measures are available in languages other than English. Retrieved 29 May, 2020, from http://www.healthmeasures.net/explore-measurement-systems/promis/intro-to-promis/available-translations

57.

Hays, R. D., Revicki, D. A., Feeny, D., Fayers, P., Spritzer, K. L., & Cella, D. (2016). Using linear equating to map PROMIS global health items and the PROMIS-29 V. 2 profile measure to the health utilities index—mark 3. Pharmacoeconomics, 34(10), 1015–1022.PubMedPubMedCentral

58.

Brazier, J. E., Yang, Y., Tsuchiya, A., & Rowen, D. L. (2010). A review of studies mapping (or cross walking) non-preference based measures of health to generic preference-based measures. The European Journal of Health Economics, 11(2), 215–225.PubMed

59.

Mulhern, B., Pan, T., Norman, R., Tran-Duy, A., Hanmer, J., Viney, R., & Devlin, N. (2021). Are generic measures of health related quality of life comparable? Understanding the measurement relationship between EQ-5D-5L, PROMIS-29 and PROPr. In: EuroQol Academy Virtual Meeting, 2021.

Titel: Evidence on the relationship between PROMIS-29 and EQ-5D: a literature review
Auteurs: Tianxin Pan
Brendan Mulhern
Rosalie Viney
Richard Norman
An Tran-Duy
Janel Hanmer
Nancy Devlin
Publicatiedatum: 28-06-2021
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/s11136-021-02911-4

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