Advertisement

Analysis of Health-Related Quality of Life and Patient-Reported Outcomes in Oncology

  • Bellinda L. King-Kallimanis
  • Roxanne E. Jensen
  • Laura C. Pinheiro
  • Diane L. Fairclough
Chapter

Abstract

This chapter complements the other chapters in this volume by discussing how to incorporate patient-reported outcome measures, such as health-related quality of life, in cancer studies, whether they be clinical trials or observational studies. As interest continues to grow for the inclusion of patient-reported outcomes, a systematic approach to the collection of such data is required. In this chapter we begin by introducing the types of patient-reported outcomes that are available for use in oncology research. We then discuss choosing a measure and the different administration options that are available. Next, design issues such as open-label and missing data are explored, with examples given. Some common methods for assessing data are presented, and finally, we note how the results from patient-reported outcome measures can be interpreted.

Keywords

Review Cancer Clinical trials critical appraisal Methodology 

References

  1. 1.
    American Society of Clinical Oncology. Outcomes of cancer treatment for technology assessment and cancer treatment guidelines. J Clin Oncol. 1996;14(2):671–9.  https://doi.org/10.1200/JCO.1996.14.2.671.CrossRefGoogle Scholar
  2. 2.
    Patrick DL, Burke LB, Powers JH, et al. Patient-reported outcomes to support medical product labeling claims: FDA perspective. Value Heal. 2007;10:S125–37.  https://doi.org/10.1111/j.1524-4733.2007.00275.x.CrossRefGoogle Scholar
  3. 3.
    Ware JJ, Sherbourne C. The MOS 36-item short-form health survey (SF-36). I. Conceptual framework and item selection. Med Care. 1992;30(6):473–83.  https://doi.org/10.1097/00005650-199206000-00002.CrossRefPubMedGoogle Scholar
  4. 4.
    EuroQol Group. EuroQol—a new facility for the measurement of health related quality of life. Health Policy (New York). 1990;16:199–208.  https://doi.org/10.1016/0168-8510(90)90421-9.CrossRefGoogle Scholar
  5. 5.
    EuroQol – EQ-5D-3L value sets. http://www.euroqol.org/about-eq-5d/valuation-of-eq-5d/eq-5d-3l-value-sets.html. Accessed 28 Apr 2017.
  6. 6.
    Aaronson NK, Ahmedzai S, Bergman B, et al. The European Organization for Research and Treatment of Cancer QLQ-C30: a quality-of-life instrument for use in international clinical trials in oncology. J Natl Cancer Inst. 1993;85(5):365–76.  https://doi.org/10.1093/JNCI/85.5.365.CrossRefPubMedGoogle Scholar
  7. 7.
    Bergman B, Aaronson NK, Ahmedzai S, Kaasa S, Sullivan M. The EORTC QLQ-LC13: a modular supplement to the EORTC core quality of life questionnaire (QLQ-C30) for use in lung cancer clinical trials. Eur J Cancer. 1994;30(5):635–42.  https://doi.org/10.1016/0959-8049(94)90535-5.CrossRefGoogle Scholar
  8. 8.
    Cella D, Tulsky DS, Gray G, et al. The Functional Assessment of Cancer Therapy Scale: development and validation of the general measure. J Clin Oncol. 1993;11(3):570–9. http://www.ncbi.nlm.nih.gov/pubmed/8445433 CrossRefPubMedGoogle Scholar
  9. 9.
    Luckett T, King MT, Butow PN, et al. Choosing between the EORTC QLQ-C30 and FACT-G for measuring health-related quality of life in cancer clinical research: issues, evidence and recommendations. Ann Oncol. 2011;22(10):2179–90.  https://doi.org/10.1093/annonc/mdq721.CrossRefPubMedGoogle Scholar
  10. 10.
    Bjordal K, De Graeff A, Fayers PM, et al. A 12 country field study of the EORTC QLQ-C30 (version 3.0) and the head and neck cancer specific module (EORTC QLQ-H and N35) in head and neck patients. Eur J Cancer. 2000;36(14):1796–807.  https://doi.org/10.1016/S0959-8049(00)00186-6.CrossRefPubMedGoogle Scholar
  11. 11.
    Sprangers MAG, Groenvald M, Arraras JI, et al. The European Organization for Research and Treatment of Cancer Breast cancer- specific quality-of-life questionnaire module: first results from a three-country field study. J Clin Oncol. 1996;14(10):2756–68.  https://doi.org/10.1200/jco.1996.14.10.2756.CrossRefPubMedGoogle Scholar
  12. 12.
    EORTC. Why do we need modules? http://groups.eortc.be/qol/why-do-we-need-modules. Accessed 28 Apr 2017.
  13. 13.
    Brady MJ, Cella DF, Mo F, et al. Reliability and validity of the functional assessment of cancer therapy-breast quality-of-life instrument. J Clin Oncol. 1997;15(3):974–86.CrossRefPubMedGoogle Scholar
  14. 14.
    FACIT. Questionnaires. http://www.facit.org/facitorg/questionnaires. Accessed 28 Apr 2017.
  15. 15.
    Brucker PS, Yost K, Cashy J, Webster K, Cella D. General population and cancer patient norms for the Functional Assessment of Cancer Therapy-General (FACT-G). Eval Health Prof. 2005;28(2):192–211.  https://doi.org/10.1177/0163278705275341.CrossRefPubMedGoogle Scholar
  16. 16.
    Sloan J, Aaronson N, Cappelleri JC, Fairclough DL, Varricchio C. Assessing the clinical significance of single items relative to summated scores. Mayo Clin Proc. 2002;77(5):479–87.  https://doi.org/10.1016/S0149-2918(02)85090-1.CrossRefPubMedGoogle Scholar
  17. 17.
    Basch E, Reeve B, Cleeland C, et al. Development of the patient-reported version of the common terminology criteria for adverse events (pro-CTCAE). Value Heal. 2010;13(7):A274–5.  https://doi.org/10.1016/S1098-3015(11)72017-4.CrossRefGoogle Scholar
  18. 18.
    Gershon R, Rothrock NE, Hanrahan RT, Jansky LJ, Harniss M, Riley W. The development of a clinical outcomes survey research application: Assessment Center. Qual Life Res. 2010;19(5):677–85.  https://doi.org/10.1007/s11136-010-9634-4.CrossRefPubMedPubMedCentralGoogle Scholar
  19. 19.
    Fries JF, Cella D, Rose M, Krishnan E, Bruce B. Progress in assessing physical function in arthritis: PROMIS short forms and computerized adaptive testing. J Rheumatol. 2009;36:2061–6.  https://doi.org/10.3899/jrheum.090358.CrossRefPubMedGoogle Scholar
  20. 20.
    Atkinson TM, Li Y, Coffey CW, et al. Reliability of adverse symptom event reporting by clinicians. Qual Life Res. 2012;21(7):1159–64.  https://doi.org/10.1007/s11136-011-0031-4.CrossRefPubMedGoogle Scholar
  21. 21.
    Jensen RE, Potosky AL, Moinpour CM, et al. United States population-based estimates of patient-reported outcomes measurement information system symptom and functional status reference values for individuals with cancer. J Clin Oncol. 2017;35(17):1913–20.  https://doi.org/10.1200/JCO.2016.71.4410.CrossRefPubMedPubMedCentralGoogle Scholar
  22. 22.
    Ruta DA, Garratt AM, Leng M, Russell IT, MacDonald LM. A new approach to the measurement of quality of life. The Patient-Generated Index. Med Care. 1994;32(11):1109–26.CrossRefPubMedGoogle Scholar
  23. 23.
    Macduff C, Russell E. The problem of measuring change in individual health-related quality of life by postal questionnaire: use of the patient-generated index in a disabled population. Qual Life Res. 1998;7(8):761–9.  https://doi.org/10.1023/A:1008831209706.CrossRefPubMedGoogle Scholar
  24. 24.
    Aburub AS, Gagnon B, Rodriguez AM, Mayo NE. Using a personalized measure (Patient Generated Index (PGI)) to identify what matters to people with cancer. Support Care Cancer. 2016;24(1):437–45.  https://doi.org/10.1007/s00520-015-2821-7.CrossRefPubMedGoogle Scholar
  25. 25.
    Calvert M, Blazeby J, Altman DG, et al. Reporting of patient-reported outcomes in randomized trials. JAMA. 2013;309(8):814.  https://doi.org/10.1001/jama.2013.879.CrossRefPubMedGoogle Scholar
  26. 26.
    Patrick D. Reporting of patient-reported outcomes in randomized trials: the CONSORT PRO extension. Value Heal. 2013;16(4):455–6.  https://doi.org/10.1016/j.jval.2013.04.001.CrossRefGoogle Scholar
  27. 27.
    Aaronson N, Choucair A, Elliott T. User’s guide to implementing patient-reported outcomes assessment in clinical practice. 2011 Jan:57. http://www.isoqol.org/UserFiles/file/UsersGuide.pdf.
  28. 28.
  29. 29.
    Gwaltney CJ, Shields AL, Shiffman S. Equivalence of electronic and paper-and-pencil administration of patient-reported outcome measures: a meta-analytic review. Value Heal. 2008;11(2):322–33.  https://doi.org/10.1111/j.1524-4733.2007.00231.x.CrossRefGoogle Scholar
  30. 30.
    Jensen RE, Rothrock NE, DeWitt EM, et al. The role of technical advances in the adoption and integration of patient-reported outcomes in clinical care. Med Care. 2015;53(2):153–9.  https://doi.org/10.1097/MLR.0000000000000289.CrossRefPubMedPubMedCentralGoogle Scholar
  31. 31.
    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.  https://doi.org/10.1097/01.MLR.0000062554.74615.4C.CrossRefPubMedGoogle Scholar
  32. 32.
    Wyrwich KW. Minimal important difference thresholds and the standard error of measurement: is there a connection? J Biopharm Stat. 2004;14(1):97–110.  https://doi.org/10.1081/BIP-120028508.CrossRefPubMedGoogle Scholar
  33. 33.
    Cocks K, King MT, Velikova G, Martyn St-James M, Fayers PM, Brown JM. Evidence-based guidelines for determination of sample size and interpretation of the European Organisation for the Research and Treatment of Cancer Quality of Life Questionnaire Core 30. J Clin Oncol. 2011;29(1):89–96.  https://doi.org/10.1200/JCO.2010.28.0107.CrossRefPubMedGoogle Scholar
  34. 34.
    Bernhard JURG, Gusset H, Rny CHU. Practical issues in quality of life assessment in multicentre trials conducted by the Swiss Group for Clinical Cancer Research. Stat Med. 1998;17:633–9.CrossRefPubMedGoogle Scholar
  35. 35.
    Mercieca-Bebber R, Palmer MJ, Brundage M, Calvert M, Stockler MR, King MT. Design, implementation and reporting strategies to reduce the instance and impact of missing patient-reported outcome (PRO) data: a systematic review. BMJ Open. 2016;6(6):e010938.  https://doi.org/10.1136/bmjopen-2015-010938.CrossRefPubMedPubMedCentralGoogle Scholar
  36. 36.
    Holm S. A simple sequentially rejective multiple test procedure. Scand J Stat. 1979;6:65–70. http://www.citeulike.org/user/santi515/article/4294367.
  37. 37.
    Hochberg Y. A sharper Bonferroni procedure for multiple tests of significance. Biometrika. 1988;75(4):800–2.  https://doi.org/10.1093/biomet/75.4.800.CrossRefGoogle Scholar
  38. 38.
    Benjamini Y, Hochberg Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J R Stat Soc Ser B. 1995;57(1).  https://doi.org/10.2307/2346101.
  39. 39.
    Rosenbaum PR, Rubin DB. The central role of the propensity score in observational studies for causal effects. Biometrika. 1983;70(1):41.  https://doi.org/10.2307/2335942.CrossRefGoogle Scholar
  40. 40.
    Reeve BB, Stover AM, Jensen RE, et al. Impact of diagnosis and treatment of clinically localized prostate cancer on health-related quality of life for older Americans: a population-based study. Cancer. 2012;118(22):5679–87.  https://doi.org/10.1002/cncr.27578.CrossRefPubMedPubMedCentralGoogle Scholar
  41. 41.
    Keating NL, Norredam M, Landrum MB, Huskamp HA, Meara E. Physical and mental health status of older long-term cancer survivors. J Am Geriatr Soc. 2005;53(12):2145–52.  https://doi.org/10.1111/j.1532-5415.2005.00507.x.CrossRefPubMedGoogle Scholar
  42. 42.
    Wang S-Y, Hsu SH, Gross CP, et al. Association between time since cancer diagnosis and health-related quality of life: a population-level analysis. Value Heal. 2016;19(5):631–8.  https://doi.org/10.1016/j.jval.2016.02.010.CrossRefGoogle Scholar
  43. 43.
    Fromme EK, Eilers KM, Mori M, Hsieh YC, Beer TM. How accurate is clinician reporting of chemotherapy adverse effects? A comparison with patient-reported symptoms from the Quality-of-Life Questionnaire C30. J Clin Oncol. 2004;22(17):3485–90.  https://doi.org/10.1200/JCO.2004.03.025.CrossRefPubMedGoogle Scholar
  44. 44.
    Pakhomov SV, Jacobsen SJ, Chute CG, Roger VL. Agreement between patient-reported symptoms and their documentation in the medical record. Am J Manag Care. 2008;14(8):530–9.  https://doi.org/10.1016/j.bbi.2008.05.010.CrossRefPubMedPubMedCentralGoogle Scholar
  45. 45.
    Basch E, Jia X, Heller G, et al. Adverse symptom event reporting by patients vs clinicians: Relationships with clinical outcomes. J Natl Cancer Inst. 2009;101(23):1624–32.  https://doi.org/10.1093/jnci/djp386.CrossRefPubMedPubMedCentralGoogle Scholar
  46. 46.
    Quinten C, Maringwa J, Gotay CC, et al. Patient self-reports of symptoms and clinician ratings as predictors of overall cancer survival. J Natl Cancer Inst. 2010;103(24):1851–8.  https://doi.org/10.1093/jnci/djr485.CrossRefGoogle Scholar
  47. 47.
    Gotay CC, Kawamoto CT, Bottomley A, Efficace F. The prognostic significance of patient-reported outcomes in cancer clinical trials. J Clin Oncol. 2008;26(8):1338–45.  https://doi.org/10.1200/JCO.2007.13.9337.CrossRefGoogle Scholar
  48. 48.
    Diouf M, Filleron T, Barbare J-C, et al. The added value of quality of life (QoL) for prognosis of overall survival in patients with palliative hepatocellular carcinoma. J Hepatol. 2013;58(3):509–21.  https://doi.org/10.1016/j.jhep.2012.11.019.CrossRefPubMedGoogle Scholar
  49. 49.
    European Medicines Agency. Guideline on missing data in confirmatory clinical trials; 2008. http://www.ema.europa.eu/docs/en_GB/document_library/Scientific_guideline/2010/09/WC500096793.pdf.
  50. 50.
  51. 51.
    Pauler DK, McCoy S, Moinpour C. Pattern mixture models for longitudinal quality of life studies in advanced stage disease. Stat Med. 2003;22(5):795–809.  https://doi.org/10.1002/sim.1397.CrossRefPubMedGoogle Scholar
  52. 52.
    Raboud JM, Singer J, Thorne A, Schechter MT, Shafran SD. Estimating the effect of treatment on quality of life in the presence of missing data due to drop-out and death. Qual Life Res. 1998;7(6):487–94.  https://doi.org/10.1023/A:1008870223350.CrossRefPubMedGoogle Scholar
  53. 53.
    Fairclough DL, Fetting JH, Cella D, Wonson W, Moinpour CM. Quality of life and quality adjusted survival for breast cancer patients receiving adjuvant therapy. Qual Life Res. 1999;8(8):723–31.  https://doi.org/10.1023/A:1008806828316.CrossRefPubMedGoogle Scholar
  54. 54.
    Kurland BF, Johnson LL, Egleston BL, Diehr PH. Longitudinal data with follow-up truncated by death: match the analysis method to research aims. Stat Sci. 2009;24(2):211–22.  https://doi.org/10.1214/09-STS293.CrossRefPubMedPubMedCentralGoogle Scholar
  55. 55.
    Schluchter MD. Methods for the analysis of informatively censored longitudinal data. Stat Med. 1992;11(14–15):1861–70. http://www.ncbi.nlm.nih.gov/pubmed/1480878.CrossRefPubMedGoogle Scholar
  56. 56.
    Ribaudo HJ, Thompson SG, Allen-Mersh TG. A joint analysis of quality of life and survival using a random effect selection model. Stat Med. 2000;19(23):3237–50. http://www.ncbi.nlm.nih.gov/pubmed/11113957.CrossRefPubMedGoogle Scholar
  57. 57.
    Touloumi G, Pocock SJ, Babiker AG, Darbyshire JH. Estimation and comparison of rates of change in longitudinal studies with informative drop-outs. Stat Med. 1999;18(10):1215–33. http://www.ncbi.nlm.nih.gov/pubmed/10363341.CrossRefPubMedGoogle Scholar
  58. 58.
    Vonesh EF, Greene T, Schluchter MD. Shared parameter models for the joint analysis of longitudinal data and event times. Stat Med. 2006;25(1):143–63.  https://doi.org/10.1002/sim.2249.CrossRefPubMedGoogle Scholar
  59. 59.
    Chi Y-Y, Ibrahim JG. Joint models for multivariate longitudinal and multivariate survival data. Biometrics. 2006;62(2):432–45.  https://doi.org/10.1111/j.1541-0420.2005.00448.x.CrossRefPubMedGoogle Scholar
  60. 60.
    Elashoff RM, Li G, Li N. An approach to joint analysis of longitudinal measurements and competing risks failure time data. Stat Med. 2007;26(14):2813–35.  https://doi.org/10.1002/sim.2749.CrossRefPubMedPubMedCentralGoogle Scholar
  61. 61.
    Law NJ, Taylor JMG, Sandler H. The joint modeling of a longitudinal disease progression marker and the failure time process in the presence of cure. Biostatistics. 2002;3(4):547–63.  https://doi.org/10.1093/biostatistics/3.4.547.CrossRefPubMedGoogle Scholar
  62. 62.
    Yu M, Law NJ, Taylor JMG, Sandler HM. Joint longitudinal-survival-cure models and their application to prostate cancer. Stat Sin. 2004;14:835–62. http://www3.stat.sinica.edu.tw/statistica/oldpdf/A14n310.pdf.
  63. 63.
    Dempster AP, Laird NM, Rubin DB. Maximum likelihood from incomplete data via the EM algorithm. J R Stat Soc Ser B Methodol. 1977;39(1):1–38.  https://doi.org/10.2307/2984875.CrossRefGoogle Scholar
  64. 64.
    Jennrich RI, Schluchter MD. Unbalanced repeated-measures models with structured covariance matrices. Biometrics. 1986;42(4):805–20. http://www.ncbi.nlm.nih.gov/pubmed/3814725.CrossRefPubMedGoogle Scholar
  65. 65.
    Siddiqui O, Hung HMJ, O’Neill R. MMRM vs. LOCF: a comprehensive comparison based on simulation study and 25 NDA datasets. J Biopharm Stat. 2009;19(2):227–46.  https://doi.org/10.1080/10543400802609797.CrossRefPubMedGoogle Scholar
  66. 66.
    Anota A, Hamidou Z, Paget-Bailly S, et al. Time to health-related quality of life score deterioration as a modality of longitudinal analysis for health-related quality of life studies in oncology: do we need RECIST for quality of life to achieve standardization? Qual Life Res. 2015;24(1):5–18.  https://doi.org/10.1007/s11136-013-0583-6.CrossRefPubMedGoogle Scholar
  67. 67.
    Bonnetain F, Dahan L, Maillard E, et al. Time until definitive quality of life score deterioration as a means of longitudinal analysis for treatment trials in patients with metastatic pancreatic adenocarcinoma. Eur J Cancer. 2010;46(15):2753–62.  https://doi.org/10.1016/j.ejca.2010.07.023.CrossRefPubMedGoogle Scholar
  68. 68.
    Osoba D, Rodrigues G, Myles J, Zee B, Pater J. Interpreting the significance of changes in health-related quality-of-life scores. J Clin Oncol. 1998;16(1):139–44.  https://doi.org/10.1200/JCO.1998.16.1.139.CrossRefPubMedGoogle Scholar
  69. 69.
    Fiteni F, Anota A, Bonnetain F, et al. Health-related quality of life in elderly patients with advanced non-small cell lung cancer comparing carboplatin and weekly paclitaxel doublet chemotherapy with monotherapy. Eur Respir J. 2016;48(3):861–72.  https://doi.org/10.1183/13993003.01695-2015.CrossRefPubMedGoogle Scholar
  70. 70.
    Gelber RD, Goldhirsch A. A new endpoint for the assessment of adjuvant therapy in postmenopausal women with operable breast cancer. J Clin Oncol. 1986;4(12):1772–9.  https://doi.org/10.1200/JCO.1986.4.12.1772.CrossRefPubMedGoogle Scholar
  71. 71.
    Satoh T, Bang YJ, Gotovkin EA, Hamamoto Y, Kang YK, Moiseyenko VM, et al. Quality of life in the trastuzumab for gastric cancer trial. Oncologist. 2014;19(7):712–9.CrossRefPubMedPubMedCentralGoogle Scholar
  72. 72.
    Revicki DA, Feeny D, Hunt TL, Cole BF. Analyzing oncology clinical trial data using the Q-TWiST method: clinical importance and sources for health state preference data. Qual Life Res. 2006;15(3):411–23.  https://doi.org/10.1007/s11136-005-1579-7.CrossRefPubMedGoogle Scholar
  73. 73.
    Arora NK. Importance of patient-centered care in enhancing patient well-being: a cancer survivor’s perspective. Qual Life Res. 2009;18(1):1–4.  https://doi.org/10.1007/s11136-008-9415-5.CrossRefPubMedGoogle Scholar
  74. 74.
    Greenhalgh J. The applications of PROs in clinical practice: what are they, do they work, and why? Qual Life Res. 2009;18(1):115–23.  https://doi.org/10.1007/s11136-008-9430-6.CrossRefPubMedGoogle Scholar
  75. 75.
    Brundage M, Feldman-Stewart D, Leis A, et al. Communicating quality of life information to cancer patients: a study of six presentation formats. J Clin Oncol. 2005;23(28):6949–56.  https://doi.org/10.1200/JCO.2005.12.514.CrossRefPubMedGoogle Scholar
  76. 76.
    Snyder CF, Smith KC, Bantug ET, et al. What do these scores mean? Presenting patient-reported outcomes data to patients and clinicians to improve interpretability. Cancer. 2017;123(10):1848–59.  https://doi.org/10.1002/cncr.30530.CrossRefPubMedPubMedCentralGoogle Scholar
  77. 77.
    Jaeschke R, Singer J, Guyatt GH. Measurement of health status. Ascertaining the minimal clinically important difference. Control Clin Trials. 1989;10(4):407–15. http://www.ncbi.nlm.nih.gov/pubmed/2691207.CrossRefPubMedGoogle Scholar
  78. 78.
    Guyatt G, Walter S, Norman G. Measuring change over time: assessing the usefulness of evaluative instruments. J Chronic Dis. 1987;40(2):171–8. http://www.ncbi.nlm.nih.gov/pubmed/3818871.CrossRefPubMedGoogle Scholar
  79. 79.
    Guyatt GH, Osoba D, Wu AW, Wyrwich KW, Norman GR, Clinical Significance Consensus Meeting Group. Methods to explain the clinical significance of health status measures. Mayo Clin Proc. 2002;77(4):371–83.  https://doi.org/10.1016/S0025-6196(11)61793-X.CrossRefPubMedGoogle Scholar
  80. 80.
    Schünemann HJ, Guyatt GH. Commentary—goodbye M(C)ID! Hello MID, where do you come from? Health Serv Res. 2005;40(2):593–7.  https://doi.org/10.1111/j.1475-6773.2005.00374.x.CrossRefPubMedPubMedCentralGoogle Scholar
  81. 81.
    Wyrwich KW, Bullinger M, Aaronson N, et al. Estimating clinically significant differences in quality of life outcomes. Qual Life Res. 2005;14(2):285–95. http://www.ncbi.nlm.nih.gov/pubmed/15892420.CrossRefPubMedGoogle Scholar
  82. 82.
    de Vet HCW, Beckerman H, Terwee CB, Terluin B, Bouter LM. Definition of clinical differences. J Rheumatol. 2006;33(2):434. Author reply 435. http://www.ncbi.nlm.nih.gov/pubmed/16465677.
  83. 83.
    Wyrwich KW, Tierney WM, Wolinsky FD. Further evidence supporting an SEM-based criterion for identifying meaningful intra-individual changes in health-related quality of life. J Clin Epidemiol. 1999;52(9):861–73. http://www.ncbi.nlm.nih.gov/pubmed/10529027.CrossRefPubMedGoogle Scholar
  84. 84.
    Beaton DE, Bombardier C, Katz JN, et al. Looking for important change/differences in studies of responsiveness. OMERACT MCID Working Group. Outcome measures in rheumatology. Minimal clinically important difference. J Rheumatol. 2001;28(2):400–5. http://www.ncbi.nlm.nih.gov/pubmed/11246687.
  85. 85.
    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(1):54.  https://doi.org/10.1186/1477-7525-4-54.CrossRefPubMedPubMedCentralGoogle Scholar
  86. 86.
    Beckerman H, Roebroeck ME, Lankhorst GJ, Becher JG, Bezemer PD, Verbeek AL. Smallest real difference, a link between reproducibility and responsiveness. Qual Life Res. 2001;10(7):571–8. http://www.ncbi.nlm.nih.gov/pubmed/11822790.
  87. 87.
    Angst F, Aeschlimann A, Stucki G. Smallest detectable and minimal clinically important differences of rehabilitation intervention with their implications for required sample sizes using WOMAC and SF-36 quality of life measurement instruments in patients with osteoarthritis of the lower extremities. Arthritis Rheum. 2001;45(4):384–91.  https://doi.org/10.1002/1529-0131(200108)45:4<384::AID-ART352>3.0.CO;2-0.CrossRefPubMedGoogle Scholar
  88. 88.
    King MT. A point of minimal important difference (MID): a critique of terminology and methods. Expert Rev Pharmacoecon Outcomes Res. 2011;11(2):171–84.  https://doi.org/10.1586/erp.11.9.CrossRefPubMedGoogle Scholar
  89. 89.
    Johnston BC, Ebrahim S, Carrasco-Labra A, et al. Minimally important difference estimates and methods: a protocol. BMJ Open. 2015;5(10):e007953.  https://doi.org/10.1136/bmjopen-2015-007953.CrossRefPubMedPubMedCentralGoogle Scholar
  90. 90.
    Eton DT, Cella D, Yost KJ, et al. A combination of distribution- and anchor-based approaches determined minimally important differences (MIDs) for four endpoints in a breast cancer scale. J Clin Epidemiol. 2004;57(9):898–910.  https://doi.org/10.1016/j.jclinepi.2004.01.012.CrossRefPubMedGoogle Scholar
  91. 91.
    Cella D, Hahn EA, Dineen K. Meaningful change in cancer-specific quality of life scores: differences between improvement and worsening. Qual Life Res. 2002;11(3):207–21.  https://doi.org/10.1023/A:1015276414526.CrossRefPubMedGoogle Scholar
  92. 92.
    Cocks K, King MT, Velikova G, De Castro G, St-James MM, Fayers PM, Brown JM. Evidence-based guidelines for interpreting change scores for the European organisation for the research and treatment of cancer quality of life questionnaire core 30. Eur J Cancer. 2012;48(11):1713–21.CrossRefPubMedGoogle Scholar
  93. 93.
    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.  https://doi.org/10.1016/j.jclinepi.2007.03.012.CrossRefPubMedGoogle Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Bellinda L. King-Kallimanis
    • 1
  • Roxanne E. Jensen
    • 2
  • Laura C. Pinheiro
    • 3
  • Diane L. Fairclough
    • 4
  1. 1.Pharmerit InternationalBostonUSA
  2. 2.Department of OncologyGeorgetown UniversityWashingtonUSA
  3. 3.Division of General Internal MedicineWeill Cornell MedicineNew YorkUSA
  4. 4.Department of Biostatistics and InformaticsColorado School of Public HealthAuroraUSA

Personalised recommendations