Skip to main content
Log in

Using QALYs in Cancer

A Review of the Methodological Limitations

  • Review Article
  • Published:
PharmacoEconomics Aims and scope Submit manuscript

Abstract

The objective of this paper is to examine how well the QALY captures the health gains generated by cancer treatments, with particular focus on the methods for constructing QALYs preferred by the UK National Institute for Health and Clinical Excellence (NICE). Data were obtained using a keyword search of the MEDLINE database and a hand search of articles written by leading researchers in the subject area (with follow up of the references in these articles). Key arguments were discussed and developed at an oncology workshop in September 2009 at the Office of Health Economics.

Three key issues emerged. First, the EQ-5D, NICE’s preferred measure of health-related quality of life (QOL) in adults, has been found to be relatively insensitive to changes in health status of cancer patients. Second, the time trade-off, NICEs preferred technique for estimating the values of health states, involves making assumptions that are likely to be violated in end-of-life scenarios. Third, the practice of using valuations of members of the general population, as recommended by NICE, is problematic because such individuals typically display a misunderstanding of what it is really like for patients to live with cancer.

Because of the way in which it is constructed, the QALY shows important limitations in terms of its ability to accurately capture the value of the health gains deemed important by cancer patients. A research agenda for addressing these limitations is proposed.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Table I

Similar content being viewed by others

References

  1. Boersma C, Broere A, Postma MJ. Quantification of the potential impact of cost-effectiveness thresholds on Dutch drug expenditures using retrospective analysis. Value Health 2010; 13: 853–6

    Article  PubMed  Google Scholar 

  2. Weinstein MC, Skinner JA. Comparative effectiveness and health care spending: implications for reform. N Engl J Med 2010; 362 (19): 460–5

    Article  PubMed  CAS  Google Scholar 

  3. NICE. Guide to the methods of technology appraisal. London: NICE, 2008 [online]. Available from URL: http://www.nice.org.uk/media/B52/A7/TAMethodsGuideUpdatedJune2008.pdf [Accessed 2009 Nov 16]

    Google Scholar 

  4. Brazier J, Ratcliffe J, Salomon J, et al. Measuring and valuing health benefits for economics evaluation. Oxford: Oxford University Press, 2007

    Google Scholar 

  5. Department of Health. Cancer reform strategy; 2007 [online]. Available from URL: http://www.dh.gov.uk/en/Publicationsandstatistics/Publications/PublicationsPolicyAndGuidance/DH_081013 [Accessed 2009 Nov 16]

    Google Scholar 

  6. National Institute for Health and Clinical Excellence. Technology appraisal guidance 178: bevacizumab (firstline), sorafenib (first- and second-line), sunitinib (secondline) and temsirolimus (first-line) for the treatment of advanced and/or metastatic renal cell carcinoma. London: NICE, 2009 [online]. Available from URL: http://guidance.nice.org.uk/TA178/Guidance/pdf/English [Accessed 2009 Nov 16]

    Google Scholar 

  7. Hawkes N. d35,000-a-year kidney drugs too costly for NHS: veto on basis of price is outrage to kidney patients, says specialist. The Times 2008 Aug 7 [online]. Available from URL: http://www.timesonline.co.uk/tol/life_and_style/health/article4474425.ece [Accessed 2009 Nov 16]

    Google Scholar 

  8. National Institute for Health and Clinical Excellence. Appraising life-extending, end of life treatments. London: NICE, 2009 [online]. Available from URL: http://www.nice.org.uk/aboutnice/howwework/devnicetech/endoflifetreatments.jsp?domedia=1&mid=88ACDAE5-19B9-E0B5-D422589714A8EC6D [Accessed 2009 Nov 16]

    Google Scholar 

  9. National Institute for Health and Clinical Excellence. Update report on the application of the ‘end-of-life’ supplementary advice in health technology appraisals. London: NICE, 2009 [online]. Available from URL: www.nice.org.uk/media/835/8E/ITEM7EndOfLifeTreatments.pdf [Accessed 2009 Nov 16]

    Google Scholar 

  10. Rabin R, de Charro F. EQ-5D: a measure of health status from the EuroQol Group. Ann Med 2001; 33: 337–43

    Article  PubMed  CAS  Google Scholar 

  11. Brazier J, Deverill M, Green C, et al. A review of the use of health status measures in economic evaluation. Health Technol Assess 1999; 3 (9): i-iv, 1–164

    Google Scholar 

  12. Dolan P. Modelling valuations for EuroQol health states. Med Care 1997; 35: 1095–108

    Article  PubMed  CAS  Google Scholar 

  13. Dolan P. The measurement of health related quality of life for use in resource allocation in health care. In: Culyer AJ, Newhouse JP, editors. Handbook of health economics. Vol. 1. Amsterdam: Elsevier Science, 2000

  14. Drummond MF, Sculpher MJ, Torrance GW, et al. Methods for the economic evaluation of health care programmes. 3rd ed. New York: Oxford University Press, 2005

    Google Scholar 

  15. Williams A. The role of the EuroQoL instrument in QALY calculations [CHE discussion paper 130]. York: Centre for Health Economics, University of York, 1995

    Google Scholar 

  16. 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: 15–23

    Article  PubMed  Google Scholar 

  17. Broeckel A, Jacobsen PB, Horton J, et al. Characteristics and correlates of fatigue after adjuvant chemotherapy for breast cancer. J Clin Oncol 1998; 16: 1689–96

    PubMed  CAS  Google Scholar 

  18. Stone P, Ream E, Richardson A, et al. Cancer-related fatigue: a different of opinion? Eur J Cancer Care 2003; 12: 20–7

    Article  CAS  Google Scholar 

  19. Esbensen BA, Osterlind K, Roer O, et al. Quality of life of elderly persons with newly diagnosed cancer. Eur J Cancer Care 2004; 13: 443–53

    Article  CAS  Google Scholar 

  20. Hofman M, Ryan JL, Figueroa-Moseley CD, et al. Cancerrelated fatigue: the scale of the problem. Oncologist 2007; 12: 4–10

    Article  PubMed  Google Scholar 

  21. Dobrez D, Cella D, Pickard S, et al. Estimation of patient preference-based utility weights from the functional assessment of cancer therapy: general. Value Health 2007; 10: 266–72

    Article  PubMed  Google Scholar 

  22. Kröz M, Büssing A, von Laue HB, et al. Reliability and validity of a new scale on internal coherence (ICS) of cancer patients. Health Qual Life Outcomes 2009 Jun 24; 7: 59

    Article  PubMed  Google Scholar 

  23. Feeny DH. The roles for preference-based measures in support of cancer research and policy. In: Lipscomb J, Gotay CC, Snyder C, editors. Outcomes assessment in cancer: measures, methods and applications. NewYork: Cambridge University Press, 2005

    Google Scholar 

  24. Bharmal M, Thomas J. Comparing the EQ-5D and the SF-6D descriptive systems to assess their ceiling effects in the US general population. Value Health 2006; 9: 262–71

    Article  PubMed  Google Scholar 

  25. Barton G, Sach T, Doherty M, et al. An assessment of the discriminative ability of the EQ-5D, SF-6D, and EQ VAS, using sociodemographic factors and clinical conditions. Eur J Health Econ 2008; 9: 237–49

    Article  PubMed  Google Scholar 

  26. van Agt H, Bonsel G. The number of levels in the descriptive system. In: Kind P, Brooks R, Rabin R, editors. EQ-5D concepts and methods: a developmental history. Dordrecht: Springer, 2005

    Google Scholar 

  27. Horsman J, Furlong W, Feeny D, et al. The Health Utilities Index (HUI): concepts, measurement properties and applications. Health Qual Life Outcomes 2003; 1 [online]. Available from URL: http://www.hqlo.com/content/1/1/54 [Accessed 2009 Nov 16]

  28. Pickard AS, De Leon MC, Kohlmann T, et al. Psychometric comparison of the standard EQ-5D to a 5 level version in cancer patients. Med Care 2007; 45: 259–63

    Article  PubMed  Google Scholar 

  29. Pickard AS, Kohlmann T, Janssen MF, et al. Evaluating equivalency between response systems: application of the Rasch model to a 3-level and 5-level EQ-5D. Med Care 2007; 45: 812–9

    Article  PubMed  Google Scholar 

  30. Kind P. Size matters: EQ-5D in transition. Med Care 2007; 45: 809–11

    Article  PubMed  Google Scholar 

  31. Janssen MF, Birnie E, Haagsma JA, et al. Comparing the standard EQ-5D three-level system with a five-level version. Value Health 2008; 11: 275–84

    Article  PubMed  Google Scholar 

  32. Kind P, Macran S. Eliciting social preferences weights for functional assessment of cancer therapy-lung health states. Pharmacoeconomics 2005; 23 (11): 1143–53

    Article  PubMed  Google Scholar 

  33. Krahn M, Bremner KE, Tomlinson G, et al. Responsiveness of disease-specific and generic utility instruments in prostate cancer patients. Quality Life Res 2007; 16: 509–22

    Article  Google Scholar 

  34. Neyt M. Towards more consistent use of generic quality-oflife instruments. Pharmacoeconomics 2010; 28 (4): 345–6

    Article  PubMed  Google Scholar 

  35. Brazier J, Yang Y, Tsuchiya A. Review of methods for mapping between condition specific measures onto generic measures of health. Report of the Office of Health Economics Commission on NHS outcomes, performance and productivity; 2008 [online]. Available from URL: http://www.ohe.org/page/Commissionreport.cfm [Accessed 2009 Nov 16]

  36. Brazier J, Tsuchiya A. Preference-based condition-specific measures of health: what happens to cross programme comparability? Health Econ 2010; 19: 125–9

    Article  PubMed  Google Scholar 

  37. Brazier J, Czoski-Murray C, Roberts J, et al. Estimation of a preference-based index from a condition-specific measure: the Kings Health Questionnaire. Med Decis Making 2008; 28: 113–26

    Article  PubMed  Google Scholar 

  38. Rowen D, Brazier JE, Young TA, et al. Deriving a preference-based measure for cancer using the EORTC QLQC30. HEDS Discussion Paper 10/01; 2010 [online]. Available from URL: http://eprints.whiterose.ac.uk/10872/ [Accessed 2010 Jul 23]

  39. Torrance GW, Thomas W, Sackett D. A utility maximization model for evaluation of health care programs. Health Serv Res 1972; 7: 118–33

    PubMed  CAS  Google Scholar 

  40. Dolan P, Stalmeier P. The validity of time trade-off values in calculating QALYs: constant proportional time trade-off versus the proportional heuristic. J Health Econ 2003; 22: 445–58

    Article  PubMed  Google Scholar 

  41. Gudex C. Time trade-off user manual: props and self-completion methods. Centre for Health Economics Working Paper No 020cheop [online]. Available from URL: http://www.york.ac.uk/media/che/documents/papers/occasionalpapers/CHE%20Occasional%20Paper%2020.pdf [Accessed 2011 Mar 22]

  42. Robinson A, Spencer A. Exploring challenges to TTO utilities: valuing states worse than dead. Health Econ 2006; 15: 393–402

    Article  PubMed  Google Scholar 

  43. Stalmeier P, Bezembinder T, Unic I. Proportional heuristics in time tradeoff and conjoint measurement. Med Decis Making 1996; 16: 36–44

    Article  PubMed  CAS  Google Scholar 

  44. Stalmeier PFM, Chapman GB, de Boer AGM, et al. A fallacy of the multiplicative QALY model for low quality weights in students and patients judging hypothetical health states. Int J Technol Assess Health Care 2001; 17: 488–96

    Article  PubMed  CAS  Google Scholar 

  45. Stalmeier PFM, Lamers LM, Busschbach JJV, et al. On the assessment of preferences for health and duration:maximal endurable time and better than dead preferences. Med Care 2007; 45: 835–41

    Article  PubMed  Google Scholar 

  46. Miyamoto JM, Eraker SA. A multiplicative model of the utility of survival duration and health quality. J Exp Psychol 1988; 117: 3–20

    Article  CAS  Google Scholar 

  47. Attema AE, Brouwer WBF. On the (not so) constant proportional trade-off in TTO. Qual Life Res 2010; 19: 489–97

    Article  PubMed  Google Scholar 

  48. Sutherland HJ, Llewelyn-Thomas H, Boyd NF, et al. Attitudes towards quality of survival: the concept of ‘maximum endurable time’. Med Decis Making 1982; 2: 299–309

    Article  PubMed  CAS  Google Scholar 

  49. Dolan P. Modelling valuations for health states: the effect of duration. Health Policy 1996; 38: 189–203

    Article  PubMed  CAS  Google Scholar 

  50. Stiggelbout AM, Kiebert GM, Kievit J, et al. The ‘utility’ of the time trade-off method in cancer patients: feasibility and proportional trade-off. J Clin Epidemiol 1995; 48: 1207–14

    Article  PubMed  CAS  Google Scholar 

  51. van Nooten FE, Koolman X, Brouwer WBF. The influence of subjective life expectancy on health state valuations using a 10 year TTO. Health Econ 2008; 18: 548–58

    Google Scholar 

  52. Buckingham K, Devlin N. A note on the nature of utility in time and health and implications for cost utility analysis. Soc Sci Med 2009; 68: 362–7

    Article  PubMed  Google Scholar 

  53. Sharma R, Stano M. Implications of an economic model of health states worse than dead. J Health Econ 2010; 29: 536–40

    Article  PubMed  Google Scholar 

  54. Gold MR, Siegel JE, Russell LB, et al. Cost-effectiveness in health andmedicine. New York: Oxford University Press, 1996

    Google Scholar 

  55. Ubel PA, Loewenstein G, Jepson C. Whose quality of life? A commentary exploring discrepancies between health state evaluations of patients and the general public. Qual Life Res 2003; 12: 599–607

    Article  PubMed  Google Scholar 

  56. Insinga RP, Fryback DG. Understanding differences between self-ratings and population ratings for health in the EuroQOL. Qual Life Res 2003; 12: 611–9

    Article  PubMed  Google Scholar 

  57. Schkade DA, Kahneman D. Does living in California make people happy? A focusing illusion in judgments of life satisfaction. Psychol Sci 1998; 9: 340–6

    Article  Google Scholar 

  58. Kahneman D, Tversky A. Prospect theory: an analysis of decision under risk. Econometrica 1979; 47: 263–91

    Article  Google Scholar 

  59. Dolan P, Kahneman D. Interpretations of utility and their implications for the valuation of health. Econ J 2008; 118: 215–34

    Article  Google Scholar 

  60. Menzel P, Dolan P, Richardson J, et al. The role of adaptation to disability and disease in health state valuation: a preliminary normative analysis. Soc Sci Med 2002; 55: 2149–58

    Article  PubMed  Google Scholar 

  61. de Wit GA, Busschbach JJ, de Charro FT. Sensitivity and perspective in the valuation of health status: whose values count? Health Econ 2000; 9 (2): 109–26

    Article  PubMed  Google Scholar 

  62. Giesinger JM, Golser M, Erharter A, et al. Do neurooncological patients and their significant others agree on quality of life ratings? Health Qual Life Outcomes 2009; 7: 87

    Article  PubMed  Google Scholar 

  63. Polsky D, Willke RJ, Scott K, et al. A comparison of scoring weights for the EuroQol derived from patients and the general public. Health Econ 2001; 10 (1): 27–37

    Article  PubMed  CAS  Google Scholar 

  64. Ratcliffe J, Brazier J, Palfreyman S, et al. A comparison of patient and population values for health states in varicose veins patients. Health Econ 2007; 16: 395–405

    Article  PubMed  Google Scholar 

  65. Mann R, Brazier J, Tsuchiya A. A comparison of patient and general population weightings of EQ-5D dimensions. Health Econ 2008; 18: 363–72

    Article  Google Scholar 

  66. Lacey HP, Fagerlin A, Loewenstein G, et al. It must be awful for them: perspective and task context affects ratings for health conditions. Judgm Decis Mak 2006; 1: 146–52

    Google Scholar 

  67. O’Leary JF, Fairclough DL, Jankowski MK, et al. Comparison of time-tradeoff utilities and rating scale values of cancer patients and their relatives: evidence for a possible plateau relationship. Med Decis Making 1995; 15: 132–7

    Article  PubMed  Google Scholar 

  68. Tang ST, McCorkle R. Use of family proxies in quality of life research for cancer patients at the end of life: a literature review. Cancer Investig 2002; 20: 1086–104

    Article  Google Scholar 

  69. Ditto PH, Hawkins NA, Pizarro DA. Imagining the end of life: on the psychology of advance decision making. Motiv Emot 2005; 29: 481–502

    Article  Google Scholar 

  70. Harris J. QALYfying the value of human life. J Med Ethics 1987; 13: 117–23

    Article  PubMed  CAS  Google Scholar 

  71. Brazier J, Akehurst R, Brennan A, et al. Should patients have a greater role in valuing health states? Appl Health Econ Health Policy 2005; 4 (4): 201–8

    Article  PubMed  Google Scholar 

  72. Slevin ML, Stubbs L, Plant JJ, et al. Attitudes to chemotherapy: comparing views of patients with cancer with those of doctors, nurses, and general public. BMJ 1990; 300: 1458–60

    Article  PubMed  CAS  Google Scholar 

  73. Roberts T, Bryan S, Heginbotham C, et al. Public involvement in health care priority setting: an economic perspective. Health Expect 1999; 2: 235–44

    Article  PubMed  Google Scholar 

  74. Dolan P, Lee H, King D, et al. How does NICE value health? BMJ 2009; 339: 371–3

    Article  Google Scholar 

  75. Tengs TO. Cost-effectiveness versus cost-utility analysis of interventions for cancer: does adjusting for health-related quality of life really matter? Value Health 2004; 1: 70–8

    Article  Google Scholar 

  76. EuroQol. What is EQ-5D [online]. Available from URL: http://www.euroqol.org/home.html [Accessed 2010 Mar 8]

  77. Shah KK, editor. Assessing and appraising oncology medicines: what are the key areas of methodological research to pursue? OHE workshop summary; 2009 [online]. Available from URL: http://www.ohe.org/fileadmin/user_upload/Other_materials/OncologyWorkshop_Dec2009.pdf [Accessed 2011 May 12]

Download references

Acknowledgements

The authors are grateful for the contributions of Claire Devaney, Nancy Devlin, the anonymous reviewers and participants at the Office of Health Economics oncology workshop in September 2009.

This paper is based on part of a consulting project commissioned and funded by the Pharmaceutical Oncology Initiative (POI) group. The material presented in this paper is independent of the funders. There are no conflicts of interest to declare.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Koonal K. Shah.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Garau, M., Shah, K.K., Mason, A.R. et al. Using QALYs in Cancer. Pharmacoeconomics 29, 673–685 (2011). https://doi.org/10.2165/11588250-000000000-00000

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.2165/11588250-000000000-00000

Keywords

Navigation