Skip to main content

Advertisement

Log in

Interpreting Change in Scores on Patient-Reported Outcome Instruments

  • Special Section on Clinical Outcome Assessments: Meeting Report
  • Published:
Therapeutic Innovation & Regulatory Science Aims and scope Submit manuscript

Abstract

Interpreting change in scores on patient-reported outcome instruments is a key aspect of instrument development. Without interpretation guidelines, the clinical meaning of significant improvements observed within a treatment group cannot be ascertained. While the field has contemplated this topic for several decades, there remains inconsistency in terminology, methods, and application. Careful selection of methods can result in determining when change is meaningful, but researchers must keep an open mind to the methods that best fit their study and instrument. In many cases, anchor-based methods are appropriate, but the statistical model that evaluates them should be defensible (eg, linear regression, repeated-measures modeling, logistic regression). Sometimes, researchers must entertain the use of novel methods that may be more appropriate for their planned studies and instrument (eg, standard setting, exit interviews, conjoint analysis). The selection of the method is best supported by clear, transparent communication with the regulatory agency to ensure that the method can support its goals.

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.

Similar content being viewed by others

References

  1. Jaeschke R, Singer J, Guyatt GH. Measurement of health status: ascertaining the minimal clinically important difference. Control Clin Trials. 1989;10(4):407–415.

    Article  CAS  Google Scholar 

  2. Lydick E, Epstein R. Interpretation of quality of life changes. Qual Life Res. 1993;2:221–226.

    Article  CAS  Google Scholar 

  3. Cella D, Bullinger M, Scott C, Barofsky I. Group vs individual approaches to understanding the clinical significance of differences or changes in quality of life. Mayo Clin Proc. 2002;77(4):384–392.

    Article  Google Scholar 

  4. US Food and Drug Administration. Draft guidance for industry on patient-reported outcome measures: use in medical product development to support labeling claims. Fed Regist. 2006;71(23):5862–5863.

    Google Scholar 

  5. 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):81–87.

    Article  CAS  Google Scholar 

  6. US Food and Drug Administration. Guidance for industry on patient-reported outcome measures: use in medical product development to support labeling claims. Fed Regist. 2009;74(235):65132–65133.

    Google Scholar 

  7. Wyrwich KW, Norquist JM, Lenderking WR, Acaster S. Methods for interpreting change over time in patient-reported outcome measures. Qual Life Res. 2013;22(3):475–483.

    Article  CAS  Google Scholar 

  8. Cappelleri JC, Zou KH, Bushmakin AG, Alvir JMJ, Alemayehu D, Symonds T. Patient-Reported Outcomes: Measurement, Implementation and Interpretation. Boca Raton, Florida: Chapman & Hall/CRC; 2013.

    Book  Google Scholar 

  9. Cappelleri JC, Bushmakin AG. Interpretation of patient-reported outcomes. Stat Methods Med Res. 2013;23(5):460–483.

    Article  Google Scholar 

  10. King MT. A point of minimal important difference (MID): a critique of terminology and methods. Expert Rev Pharmacoecon Outcomes Res. 2011;11:171–184.

    Article  Google Scholar 

  11. Marquis P, Chassany O, Abetz L. A comprehensive strategy for the interpretation of quality-of-life data based on existing methods. Value Health. 2004;7:93–104.

    Article  Google Scholar 

  12. McLeod LD, Coon CD, Martin SA, Fehnel SE, Hays RD. Interpreting patient-reported outcome results: US FDA guidance and emerging methods. Expert Rev Pharmacoecon Outcomes Res. 2011;11:163–169.

    Article  Google Scholar 

  13. Revicki D, Erickson PA, Sloan JA, Dueck A, Guess H, Santanello NC, and the Mayo/FDA Patient-Reported Outcomes Consensus Meeting Group. Interpreting and reporting results based on patient-reported outcomes. Value Health. 2007;10:S116–S124.

    Article  Google Scholar 

  14. 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):102–109.

    Article  Google Scholar 

  15. Yost KJ, Eton DT, Garcia SF, Cella D. Minimally important differences were estimated for six Patient-Reported Outcomes Measurement Information System-Cancer scales in advanced-stage cancer patients. J Clin Epidemiol. 2011;64(5):507–516.

    Article  Google Scholar 

  16. Gerlinger C, Schumacher U, Faustmann T, Colligs A, Schmitz H, Seitz C. Defining a minimal clinically important difference for endometriosis-associated pelvic pain measured on a visual analog scale: analyses of two placebo-controlled, randomized trials. Health Qual Life Outcomes. 2010;8(1):138.

    Article  Google Scholar 

  17. Stull DE, Wasiak R, Kreif N, et al. Validation of the SF-36 in patients with endometriosis. Qual Life Res. 2014;23(1):103–117.

    Article  Google Scholar 

  18. 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):139–144.

    Article  CAS  Google Scholar 

  19. Smelt AFH, Assendelft WJJ, Terwee CB, Ferrari MD, Blom JW. What is a clinically relevant change on the HIT-6 questionnaire? An estimation in a primary-care population of migraine patients. Cephalalgia. 2014;34(1):29–36.

    Article  Google Scholar 

  20. Farrar JT, Young JP, LaMoreaux L, Werth JL, Poole RM. Clinical importance of changes in chronic pain intensity measured on an 11-point numerical pain rating scale. Pain. 2001;94(2):149–158.

    Article  CAS  Google Scholar 

  21. Lyrica [product labeling]. New York, NY: Pfizer Inc; 2013.

  22. Mamolo CM, Bushmakin AG, Cappelleri JC. Application of the Itch Severity Score in patients with moderate-to-severe plaque psoriasis: clinically important difference and responder analyses. J Dermatolog Treat. 2015;26(2):121–123.

    Article  Google Scholar 

  23. Burke LB, Trenacosti AM. Interpretation of PRO trial results to support FDA labelling claims: the regulator perspective. Presented at: International Society for Pharmacoecomomics and Outcomes Research 15th Annual International Meeting. May 15–19, 2010; Atlanta, GA.

  24. Cella D, Choi S, Garcia S, et al. Setting standards for severity of common symptoms in oncology using the PROMIS item banks and expert judgment. Qual Life Res. 2014:2651–2661.

    Article  Google Scholar 

  25. Cook KF, Victorson DE, Cella D, Schalet BD, Miller D. Creating meaningful cut-scores for Neuro-QOL measures of fatigue, physical functioning, and sleep disturbance using standard setting with patients and providers. Qual Life Res. 2014;24(3):575–589.

    Article  Google Scholar 

  26. Messick S. Test validity: a matter of consequence. Soc Indic Res. 1998;45(1–3):35–44.

    Article  Google Scholar 

  27. Cook KF, Kallen MA, Victorson D, Miller D. How much change really matters? Development and comparison of two novel approaches to defining clinically important differences in fatigue scores. Qual Life Res. 2015; 24:157–158.

    Google Scholar 

  28. Tashakkori A, Creswell J. The new era of mixed methods. J Mix Methods Res. 2007;1(1):3–8.

    Article  Google Scholar 

  29. Mohamed AF, Hauber AB, Johnson FR, Coon CD. Patient preferences and linear scoring rules for patient-reported outcomes. Patient. 2010;3(4):217–227.

    Article  Google Scholar 

  30. Coon CD, Hauber AB, Mohamed AF, McLeod LD. Using choice-format conjoint analysis to assign meaning to PRO scores. Qual Life Res. 2010; 19:126–127.

    Google Scholar 

  31. Hauber AB, Mohamed AF, Reed Johnson F, Oyelowo O, Curtis BH, Coon C. Estimating importance weights for the IWQOL-Lite using conjoint analysis. Qual Life Res. 2010;19(5):701–709.

    Article  Google Scholar 

  32. Uryniak T, Chan ISF, Fedorov VV, et al. Responder analyses—a PhRMA position paper. Stat Biopharm Res. 2011;3(3):476–487.

    Article  Google Scholar 

  33. Revicki DA, Cella D, Hays RD, Sloan JA, Lenderking WR, Aaronson NK. Responsiveness and minimal important differences for patient reported outcomes. Health Qual Life Outcomes. 2006;4:70.

    Article  Google Scholar 

  34. Hays RD, Woolley JM. The concept of clinically meaningful difference in health-related quality of life research. Pharmacoeconomics. 2000;18:419–422.

    Article  CAS  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Cheryl D. Coon PhD.

Additional information

Author Note

This work was presented as a session at the 6th Annual PRO Consortium Workshop, Silver Spring, MD, April 29–30, 2015. The panel consisted of Cheryl D. Coon, Joseph C. Cappelleri, Laura Lee Johnson, and Scott Komo.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Coon, C.D., Cappelleri, J.C. Interpreting Change in Scores on Patient-Reported Outcome Instruments. Ther Innov Regul Sci 50, 22–29 (2016). https://doi.org/10.1177/2168479015622667

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1177/2168479015622667

Keywords

Navigation