Advertisement

Quality of Life Research

, Volume 22, Issue 3, pp 475–483 | Cite as

Methods for interpreting change over time in patient-reported outcome measures

  • K. W. WyrwichEmail author
  • J. M. Norquist
  • W. R. Lenderking
  • S. Acaster
  • the Industry Advisory Committee of International Society for Quality of Life Research (ISOQOL)
Article

Abstract

Purpose

Interpretation guidelines are needed for patient-reported outcome (PRO) measures’ change scores to evaluate efficacy of an intervention and to communicate PRO results to regulators, patients, physicians, and providers. The 2009 Food and Drug Administration (FDA) Guidance for Industry Patient-Reported Outcomes (PRO) Measures: Use in Medical Product Development to Support Labeling Claims (hereafter referred to as the final FDA PRO Guidance) provides some recommendations for the interpretation of change in PRO scores as evidence of treatment efficacy.

Methods

This article reviews the evolution of the methods and the terminology used to describe and aid in the communication of meaningful PRO change score thresholds.

Results

Anchor- and distribution-based methods have played important roles, and the FDA has recently stressed the importance of cross-sectional patient global assessments of concept as anchor-based methods for estimation of the responder definition, which describes an individual-level treatment benefit. The final FDA PRO Guidance proposes the cumulative distribution function (CDF) of responses as a useful method to depict the effect of treatments across the study population.

Conclusions

While CDFs serve an important role, they should not be a replacement for the careful investigation of a PRO’s relevant responder definition using anchor-based methods and providing stakeholders with a relevant threshold for the interpretation of change over time.

Keywords

Patient-reported outcome Interpretation Anchor-based Distribution-based Change over time Quality of life Cumulative distribution function Minimal important difference Responder definition 

Abbreviations

AQLQ

Asthma Quality of Life Questionnaire

CDF

Cumulative distribution function

CHQ

Chronic Heart Failure Questionnaire

CRQ

Chronic Respiratory Questionnaire

ECOG

Eastern Cooperative Oncology Group

ES

Effect size

FDA

Food and drug administration

IAC

Industry Advisory Committee

ISOQOL

International Society for Quality of Life Research

MCID

Minimal clinically important difference

MID

Minimal important difference

PRO

Patient-reported outcome

QOL

Quality of life

Notes

Acknowledgments

Members of the Industry Advisory Committee (IAC), the Board of Directors of the International Society for Quality of Life Research (ISOQOL), and two anonymous reviewers offered valuable suggestions that were incorporated into this paper.

References

  1. 1.
    Patient-Centered Outcomes Research Institute (PCORI). Available at: http://www.pcori.org/home.html.
  2. 2.
    King, M. T. (2011). A point of minimal important difference (MID): A critique of terminology and methods. Expert review of pharmacoeconomics & outcomes research, 11(2), 171–184.CrossRefGoogle Scholar
  3. 3.
    Food and Drug Administration. (2009). Guidance for industry on patient-reported outcome measures: Use in medical product development to support labeling claims. Federal Register, 74(235), 65132–65133.Google Scholar
  4. 4.
    Burke, L. B., & Trenacosti, A. M. (2010). Interpretation of PRO trial results to support FDA labelling claims: the regulator perspective. International Society for Pharmacoecomomics and Outcomes Research 15th Annual International Meeting. Atlanta: GA.Google Scholar
  5. 5.
    Jaeschke, R., Singer, J., & Guyatt, G. H. (1989). Measurement of health status. Ascertaining the minimal clinically important difference. Controlled Clinical Trials, 10(4), 407–415.PubMedCrossRefGoogle Scholar
  6. 6.
    Guyatt, G. H., Berman, L. B., & Townsend, M. (1987). Long-term outcome after respiratory rehabilitation. Canadian Medical Association Journal, 137(12), 1089–1095.PubMedGoogle Scholar
  7. 7.
    Guyatt, G. H., Townsend, M., Nogradi, S., Pugsley, S. O., Keller, J. L., & Newhouse, M. T. (1988). Acute response to bronchodilator. An imperfect guide for bronchodilator therapy in chronic airflow limitation. Archives of Internal Medicine, 148(9), 1949–1952.PubMedCrossRefGoogle Scholar
  8. 8.
    Guyatt, G. H., Sullivan, M. J., Fallen, E. L., Tihal, H., Rideout, E., Halcrow, S., et al. (1988). A controlled trial of digoxin in congestive heart failure. American Journal of Cardiology, 61(4), 371–375.PubMedCrossRefGoogle Scholar
  9. 9.
    Guyatt, G. H., Berman, L. B., Townsend, M., Pugsley, S. O., & Chambers, L. W. (1987). A measure of quality of life for clinical trials in chronic lung disease. Thorax, 42(10), 773–778.PubMedCrossRefGoogle Scholar
  10. 10.
    Guyatt, G. H., Nogradi, S., Halcrow, S., Singer, J., Sullivan, M. J., & Fallen, E. L. (1989). Development and testing of a new measure of health status for clinical trials in heart failure. Journal of General Internal Medicine, 4(2), 101–107.PubMedCrossRefGoogle Scholar
  11. 11.
    Juniper, E. F., Guyatt, G. H., Willan, A., & Griffith, L. E. (1994). Determining a minimal important change in a disease-specific Quality of Life Questionnaire. Journal of Clinical Epidemiology, 47(1), 81–87.PubMedCrossRefGoogle Scholar
  12. 12.
    Sloan, J. A., Cella, D., Frost, M., Guyatt, G. H., Sprangers, M., & Symonds, T. (2002). Assessing clinical significance in measuring oncology patient quality of life: Introduction to the symposium, content overview, and definition of terms. Mayo Clinic Proceedings, 77(4), 367–370.PubMedCrossRefGoogle Scholar
  13. 13.
    Guyatt, G. H., Osoba, D., Wu, A. W., Wyrwich, K. W., & Norman, G. R. (2002). Methods to explain the clinical significance of health status measures. Mayo Clinic Proceedings, 77(4), 371–383.PubMedCrossRefGoogle Scholar
  14. 14.
    Cella, D., Bullinger, M., Scott, C., & Barofsky, I. (2002). Group vs individual approaches to understanding the clinical significance of differences or changes in quality of life. Mayo Clinic Proceedings, 77(4), 384–392.PubMedCrossRefGoogle Scholar
  15. 15.
    Sloan, J. A., Aaronson, N., Cappelleri, J. C., Fairclough, D. L., & Varricchio, C. (2002). Assessing the clinical significance of single items relative to summated scores. Mayo Clinic Proceedings, 77(5), 479–487.PubMedGoogle Scholar
  16. 16.
    Frost, M. H., Bonomi, A. E., Ferrans, C. E., Wong, G. Y., & Hays, R. D. (2002). Patient, clinician, and population perspectives on determining the clinical significance of quality-of-life scores. Mayo Clinic Proceedings, 77(5), 488–494.PubMedGoogle Scholar
  17. 17.
    Sprangers, M. A., Moinpour, C. M., Moynihan, T. J., Patrick, D. L., & Revicki, D. A. (2002). Assessing meaningful change in quality of life over time: A users’ guide for clinicians. Mayo Clinic Proceedings, 77(6), 561–571.PubMedCrossRefGoogle Scholar
  18. 18.
    Symonds, T., Berzon, R., Marquis, P., & Rummans, T. A. (2002). The clinical significance of quality-of-life results: Practical considerations for specific audiences. Mayo Clinic Proceedings, 77(6), 572–583.PubMedCrossRefGoogle Scholar
  19. 19.
    Food and Drug Administration. (2006). Draft guidance for industry on patient-reported outcome measures: Use in medical product development to support labeling claims. Federal Register, 71(23), 5862–5863.Google Scholar
  20. 20.
    Hamilton, M. (1967). Development of a rating scale for primary depressive illness. The British Journal of Social and Clinical Psychology, 6(4), 278–296.PubMedCrossRefGoogle Scholar
  21. 21.
    Revicki, D. A., Erickson, P. A., Sloan, J. A., Dueck, A., Guess, H., & Santanello, N. C. (2007). Interpreting and reporting results based on patient-reported outcomes. Value Health, 10(Suppl 2), S116–S124.PubMedCrossRefGoogle Scholar
  22. 22.
    Patrick, D. L., Burke, L. B., Powers, J. H., Scott, J. A., Rock, E. P., Dawisha, S., et al. (2007). Patient-reported outcomes to support medical product labeling claims: FDA perspective. Value Health, 10(Suppl 2), S125–S137.PubMedCrossRefGoogle Scholar
  23. 23.
    Lydick, E., & Epstein, R. S. (1993). Interpretation of quality of life changes. Quality of Life Research, 2(3), 221–226.PubMedCrossRefGoogle Scholar
  24. 24.
    Revicki, D., Hays, R. D., Cella, D., & Sloan, J. (2008). Recommended methods for determining responsiveness and minimally important differences for patient-reported outcomes. Journal of Clinical Epidemiology, 61(2), 102–109.PubMedCrossRefGoogle Scholar
  25. 25.
    Sloan, J. A., Frost, M. H., Berzon, R., Dueck, A., Guyatt, G., Moinpour, C., et al. (2006). The clinical significance of quality of life assessments in oncology: A summary for clinicians. Supportive Care in Cancer, 14(10), 988–998.PubMedCrossRefGoogle Scholar
  26. 26.
    Farrar, J. T., Young, J. P., Jr, LaMoreaux, L., Werth, J. L., & Poole, R. M. (2001). Clinical importance of changes in chronic pain intensity measured on an 11-point numerical pain rating scale. Pain, 94(2), 149–158.PubMedCrossRefGoogle Scholar
  27. 27.
    Norman, G. R., Stratford, P., & Regehr, G. (1997). Methodological problems in the retrospective computation of responsiveness to change: The lesson of Cronbach. Journal of Clinical Epidemiology, 50(8), 869–879.PubMedCrossRefGoogle Scholar
  28. 28.
    Walters, S. J., & Brazier, J. E. (2005). Comparison of the minimally important difference for two health state utility measures: EQ-5D and SF-6D. Quality of Life Research, 14(6), 1523–1532.PubMedCrossRefGoogle Scholar
  29. 29.
    Metz, S. M., Wyrwich, K. W., Babu, A. N., Kroenke, K., Tierney, W. M., & Wolinsky, F. D. (2007). Validity of patient-reported health-related quality of life global ratings of change using structural equation modeling. Quality of Life Research, 16(7), 1193–1202.PubMedCrossRefGoogle Scholar
  30. 30.
    Wyrwich, K., Harnam, N., Revicki, D. A., Locklear, J. C., Svedsater, H., & Endicott, J. (2009). Assessing health-related quality of life in generalized anxiety disorder using the Quality Of Life Enjoyment and Satisfaction Questionnaire. International Clinical Psychopharmacology, 24(6), 289–295.PubMedCrossRefGoogle Scholar
  31. 31.
    Brozek, J. L., Guyatt, G. H., & Schunemann, H. J. (2006). How a well-grounded minimal important difference can enhance transparency of labelling claims and improve interpretation of a patient reported outcome measure. Health and Quality of Life Outcomes, 4, 69.PubMedCrossRefGoogle Scholar
  32. 32.
    Kosinski, M., Zhao, S. Z., Dedhiya, S., Osterhaus, J. T., & Ware, J. E., Jr. (2000). Determining minimally important changes in generic and disease-specific health-related quality of life questionnaires in clinical trials of rheumatoid arthritis. Arthritis and Rheumatism, 43(7), 1478–1487.PubMedCrossRefGoogle Scholar
  33. 33.
    Eton, D. T., Cella, D., Yost, K. J., Yount, S. E., Peterman, A. H., Neuberg, D. S., et al. (2004). A combination of distribution- and anchor-based approaches determined minimally important differences (MIDs) for four endpoints in a breast cancer scale. Journal of Clinical Epidemiology, 57(9), 898–910.PubMedCrossRefGoogle Scholar
  34. 34.
    Cohen, J. (1988). Statistical Power Analysis for the Behavioral Sciences. Hillsdale, NJ: Lawrence Erlbaum Associates.Google Scholar
  35. 35.
    Kazis, L. E., Anderson, J. J., & Meenan, R. F. (1989). Effect sizes for interpreting changes in health status. Medical Care, 27(3 Suppl), S178–S189.PubMedCrossRefGoogle Scholar
  36. 36.
    Norman, G. R., Wyrwich, K. W., & Patrick, D. L. (2007). The mathematical relationship among different forms of responsiveness coefficients. Quality of Life Research, 16(5), 815–822.PubMedCrossRefGoogle Scholar
  37. 37.
    Liang, M. H. (1995). Evaluating measurement responsiveness. Journal of Rheumatology, 22(6), 1191–1192.PubMedGoogle Scholar
  38. 38.
    Norman, G. R., Sloan, J. A., & Wyrwich, K. W. (2003). Interpretation of changes in health-related quality of life: The remarkable universality of half a standard deviation. Medical Care, 41(5), 582–592.PubMedGoogle Scholar
  39. 39.
    Nunnally, J. C., & Bernstein, I. H. (1994). Psychometric Theory. New York: McGraw-Hill.Google Scholar
  40. 40.
    Wyrwich, K. W., Tierney, W. M., & Wolinsky, F. D. (1999). Further evidence supporting an SEM-based criterion for identifying meaningful intra-individual changes in health-related quality of life. Journal of Clinical Epidemiology, 52(9), 861–873.PubMedCrossRefGoogle Scholar
  41. 41.
    Wyrwich, K. W. (2004). Minimal important difference thresholds and the standard error of measurement: Is there a connection? Journal of Biopharmaceutical Statistics, 14(1), 97–110.PubMedCrossRefGoogle Scholar
  42. 42.
    Wyrwich, K. W., Tierney, W. M., & Wolinsky, F. D. (2002). Using the standard error of measurement to identify important changes on the Asthma Quality of Life Questionnaire. Quality of Life Research, 11(1), 1–7.PubMedCrossRefGoogle Scholar
  43. 43.
    Cella, D., Eton, D. T., Fairclough, D. L., Bonomi, P., Heyes, A. E., Silberman, C., et al. (2002). What is a clinically meaningful change on the Functional Assessment of Cancer Therapy-Lung (FACT-L) Questionnaire? Results from Eastern Cooperative Oncology Group (ECOG) Study 5592. Journal of Clinical Epidemiology, 55(3), 285–295.PubMedCrossRefGoogle Scholar
  44. 44.
    Crosby, R. D., Kolotkin, R. L., & Williams, G. R. (2004). An integrated method to determine meaningful changes in health-related quality of life. Journal of Clinical Epidemiology, 57(11), 1153–1160.PubMedCrossRefGoogle Scholar
  45. 45.
    Yost, K. J., Cella, D., Chawla, A., Holmgren, E., Eton, D. T., Ayanian, J. Z., et al. (2005). Minimally important differences were estimated for the Functional Assessment of Cancer Therapy-Colorectal (FACT-C) instrument using a combination of distribution- and anchor-based approaches. Journal of Clinical Epidemiology, 58(12), 1241–1251.PubMedCrossRefGoogle Scholar
  46. 46.
    ARICEPT Oral Solution (Donepezil Hydrochloride) [approval label]. Available at: http://www.accessdata.fda.gov/drugsatfda_docs/label/2004/21719lbl.pdf.
  47. 47.
    Copay, A. G., Subach, B. R., Glassman, S. D., Polly, D. W., Jr, & Schuler, T. C. (2007). Understanding the minimum clinically important difference: A review of concepts and methods. Spine Journal, 7(5), 541–546.PubMedCrossRefGoogle Scholar
  48. 48.
    Sprangers, M. A., & Schwartz, C. E. (1999). Integrating response shift into health-related quality of life research: A theoretical model. Social Science and Medicine, 48(11), 1507–1515.PubMedCrossRefGoogle Scholar
  49. 49.
    Rapkin, B. D., & Schwartz, C. E. (2004). Toward a theoretical model of quality-of-life appraisal: Implications of findings from studies of response shift. Health and Quality of Life Outcomes, 2, 14.PubMedCrossRefGoogle Scholar
  50. 50.
    Barclay-Goddard, R., Epstein, J. D., & Mayo, N. E. (2009). Response shift: A brief overview and proposed research priorities. Quality of Life Research, 18(3), 335–346.PubMedCrossRefGoogle Scholar
  51. 51.
    Sprangers, M. A., & Aaronson, N. K. (1992). The role of health care providers and significant others in evaluating the quality of life of patients with chronic disease: A review. Journal of Clinical Epidemiology, 45(7), 743–760.PubMedCrossRefGoogle Scholar
  52. 52.
    von Essen, L. (2004). Proxy ratings of patient quality of life–factors related to patient-proxy agreement. Acta Oncologica, 43(3), 229–234.CrossRefGoogle Scholar
  53. 53.
    van der Linden, F. A., Kragt, J. J., van Bon, M., Klein, M., Thompson, A. J., van der Ploeg, H. M., et al. (2008). Longitudinal proxy measurements in multiple sclerosis: Patient-proxy agreement on the impact of MS on daily life over a period of two years. BMC Neurol, 8, 2.PubMedCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2012

Authors and Affiliations

  • K. W. Wyrwich
    • 1
    Email author
  • J. M. Norquist
    • 2
  • W. R. Lenderking
    • 1
  • S. Acaster
    • 3
  • the Industry Advisory Committee of International Society for Quality of Life Research (ISOQOL)
  1. 1.United BioSource CorporationBethesdaUSA
  2. 2.Merck Sharp & Dohme, Inc.North WalesUSA
  3. 3.Oxford Outcomes LtdOxfordUK

Personalised recommendations