Abstract
This chapter has been created to provide an accessible introduction to the development and psychometric evaluation of patient-reported outcome (PRO) measures specifically designed to assess key endpoints in clinical trials, with the ultimate goal of supporting approval and/or labeling claims for pharmaceutical products. While many of our recommendations are broadly applicable to the development of PRO measures for use in clinical trials in any country and in other types of patient-based research (such as observational studies), this chapter will primarily focus on assembling and documenting the types of evidence needed to facilitate reviews of key study endpoints by the United States (US) Food and Drug Administration (FDA) .
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Andrich, D. (1988). Rasch models for measurement. Beverly Hills: Sage.
Baldwin, M., Spong, A., Doward, L., & Gnanasakthy, A. (2011). Patient-reported outcomes, patient-reported information: From randomized controlled trials to the social Web and beyond. Patient, 4, 1–7.
Bentler, P. M. (1989). EQS structural equations program manual. Los Angeles: BMDP Statistical Software.
Bobo, W. V., Angleró, G. C., Jenkins, G., Hall-Flavin, D. K., Weinshilboum, R., & Biernacka, J. M. (2016). Validation of the 17-item hamilton depression rating scale definition of response for adults with major depressive disorder using equipercentile linking to clinical global impression scale ratings: analysis of pharmacogenomic research network antidepressant medication pharmacogenomic study (PGRN-AMPS) data. Human Psychopharmacology, 31, 185–192.
Browne, M. W., & Cudeck, R. (1993). Alternative ways of assessing model fit. In K. A. Bollen & J. S. Long (Eds.), Testing structural equation models (pp. 136–162). Newbury Park: Sage.
Cappelleri, J. C., & Bushmakin, A. G. (2018). Advancing interpretation of patient-reported outcomes. In K. Peace, D.-G. Chen, & S. Menon (Eds.), Biopharmaceutical Applied Statistics Symposium, Vol. 2. pp. 69–89
Cappelleri, J. C., & Spielberg, S. P. (2015). Advances in clinical outcome assessments. Therapeutic Innovation and Regulatory Science, 49, 780–782.
Cappelleri, J. C., Zou, K. H., Bushmakin, A. G., Alvir, J. M. J., Alemayehu, D., & Symonds, T. (2013). Patient-reported outcomes—measurement, implementation, and interpretation. Boca Raton, Florida: Chapman and Hall/CRC Press.
Cappelleri, J. C., Lundy, J., & Hays, R. D. (2014). Overview of classical test theory and item response theory for quantitative assessment of items in developing patient-reported outcome measures. Clinical Therapeutics, 36, 648–662.
Cella, D., Bullinger, M., Scott, C., Barofsky, I., Clinical Significance Consensus Meeting Group. (2002). Group vs individual approaches to understanding the clinical significance of differences or changes in quality of life. Mayo Clinic Proceedings 77, 384–392.
Chen, W. C., McLeod, L. D., Nelson, L. M., Williams, V. S., & Fehnel, S. E. (2014). Quantitative challenges facing patient-centered outcomes research. Expert Review Pharmacoecon Outcomes Research, 14(3), 379–386.
Cook, K. F., Victorson, D. E., Cella, D., Schalet, B. D., & Miller, D. (2015). Creating meaningful cut-scores for Neuro-QOL measures of fatigue, physical functioning, and sleep disturbance using standard setting with patients and providers. Quality of Life Research, 24, 575–589.
Coon, C. D., & Cappelleri, J. C. (2016). Interpreting change in scores on patient-reported outcome instruments. Therapeutic Innovation and Regulatory Science, 50, 22–29.
Coons, S. J., Gwaltney, C. J., Hays, R. D., et al. (2009). Recommendations on evidence needed to support measurement equivalence between electronic and paper-based patient-reported outcome (PRO) measures: ISPOR ePRO good research practices task force report. Value Health, 12, 419–429.
Cronbach, L. (1951). Coefficient alpha and the internal structure of tests. Psychometrika, 16, 297–334.
de Vet, H. C. W., Terwee, C. B., Mokkink, L. B., & Knol, D. L. (2011). Measurement in medicine: A practical guide. Cambridge: Cambridge University Press.
DeMuro, C. D., Lewis, S. A., DiBenedetti, D. B., Price, M. A., & Fehnel, S. E. (2012). Successful implementation of cognitive interviews in special populations. Expert Review Pharmacoecon Outcomes Research, 12(2), 181–187.
Deyo, R. A., Diehr, P., & Patrick, D. L. (1991). Reproducibility and responsiveness of health status measures: Statistics and strategies for evaluation. Controlled Clinical Trial, 12, 142S–158S.
Edelen, M. O., & Reeve, B. B. (2007). Applying item response theory (IRT) modeling to questionnaire development, evaluation, and refinement. Quality of Life Research, 16, 5–18.
European Medicines Agency (EMA). (2005). Reflection paper on the regulatory guidance for the use of health related quality of life (HRQL) measures in the evaluation of medicinal products. London: European Medicines Agency.
Fayers, P. M., & Hays, R. D. (Eds.). (2005). Assessing quality of life in clinical trials: Methods and practice. Oxford: Oxford University Press.
Fayers, P. M., & Hays, D. R. (2014). Don’t middle your MIDs: regression to the mean shrinks estimates of minimally important differences. Quality of Life Research, 23, 1–4.
Fayers, P. M., & Machin, D. (2016). Quality of life: The assessment, analysis and reporting of patient-reported outcomes (3rd ed.). Chichester: Wiley.
Food and Drug Administration (FDA). (2007). Guidance for industry. Developing products for weight management. https://www.fda.gov/downloads/Drugs/Guidances/ucm071612.pdf. Accessed June, 01 2017.
Food and Drug Administration (FDA). (2009). Guidance for industry. Patient-reported outcome measures: use in medical product development to support labeling claims. http://www.fda.gov/downloads/Drugs/GuidanceComplianceRegulatoryInformation/Guidances/UCM193282.pdf. Accessed January, 3 2017.
Food and Drug Administration (FDA). (2013a). Roadmap to patient-focused outcome measurement in clinical trials. http://www.fda.gov/Drugs/DevelopmentApprovalProcess/DrugDevelopmentToolsQualificationProgram/ucm284077.htm. Accessed January 5, 2017.
Food and Drug Administration (FDA). (2013b). Center for Drug Evaluation and Research. Drug Development Tool Number: COA DDT 003 Study Endpoints and Labeling Development (SEAL) Review. SEALD Tracking Number: 2013–055. http://www.fda.gov/downloads/Drugs/DevelopmentApprovalProcess/DrugDevelopmentToolsQualificationProgram/UCM386244.pdf. Accessed January 28, 2017.
Food and Drug Administration (FDA). (2016). Clinical outcome assessment compendium. http://www.fda.gov/Drugs/DevelopmentApprovalProcess/DevelopmentResources/ucm459231.htm. Accessed January, 8 2017.
Frost, M. H., Reeve, B. B., Liepa, A. M., Stauffer, J. W., Hays, R. D.; Mayo/FDA Patient-Reported Outcomes Consensus Meeting Group. (2007). What is sufficient evidence for the reliability and validity of patient-reported outcome measures? Value Health 10, S94–S105.
Gnanasakthy, A., Mordin, M., Clark, M., et al. (2012). A review of patient-reported outcome labels in the United States: 2006–2010. Value Health, 15(3), 437–442.
Gnanasakthy, A., Mordin, M., Evans, E., Doward, L., & DeMuro, C. (2017). A review of patient-reported outcome labeling in the United States (2011–2015). Value Health, 20(3), 420–429. https://doi.org/10.1016/j.jval.2016.10.006.
Gorsuch, R. L. (1983). Factor analysis (2nd ed.). Hillsdale: Lawrence Erlbaum.
Guyatt, G. H., Osoba, D., Wu, A. W., Wyrwich, K. W., Norman, G. R.; Clinical Significance Consensus Meeting Group. (2002). Methods to explain the clinical significance of health status measures. Mayo Clin Proceedings 77, 371–383.
Hays, R. D., Brodsky, M., Johnston, M. F., Spritzer, K. L., & Hui, K. (2005). Evaluating the statistical significance of health-related quality of life change in individual patients. Evaluation and the Health Professions, 28, 160–171.
Hays, R. D., Revicki, D. (2005). Reliability and validity (including responsiveness). In P. M. Fayers, R. D. Hays (Eds.) Assessing quality of life in clinical trials: methods and practice. Oxford: Oxford University Press, pp. 25–39.
King, M. T. (2011). A point of minimal important difference (MID): a critique of terminology and methods. Expert Review Pharmacoecon Outcomes Research, 11, 171–184.
Marquis, P., Chassany, O., & Abetz, L. (2004). A comprehensive strategy for the interpretation of quality-of-life data based on existing methods. Value Health, 7, 93–104.
McGraw, K. O., & Wong, S. P. (1996). Forming inferences about some intraclass correlation coefficients. Psychological Methods, 1, 30–46.
McLeod, L. D., Cappelleri, J. C., & Hays, R. D. (2016). Best (but oft-forgotten) practices: expressing and interpreting associations and effect sizes in clinical outcome assessments. The American Journal of Clinical Nutrition 103(3), 685–693 (with erratum in The American Journal of Clinical Nutrition 2017;105:241).
McLeod, L. D., Coon, C. D., Martin, S. A., Fehnel, S. E., & Hays, R. D. (2011). Interpreting patient-reported outcome results: US FDA guidance and emerging methods. Expert Review Pharmacoecon Outcomes Research, 11, 163–169.
Messick, S. (1989). Validity. Educational measurement (3rd ed., pp. 13–103). New York: Macmillan.
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, 4, 582–592.
Norquist, J. M., Girman, C., Fehnel, S., DeMuro-Mercon, C., & Santanello, N. (2012). Choice of recall period for patient-reported outcome (PRO) measures: Criteria for consideration. Quality of Life Research, 21(6), 1013–1020.
Nunnally, J. C., & Bernstein, I. H. (1994). Psychometric theory (3rd ed.). New York: McGraw-Hill.
Odom, D., McLeod, L., Sherif, B., Nelson, L., McSorley, D. (Under review). Longitudinal modeling approaches to assess the association between changes in a patient-reported outcome and a clinical endpoint.
Odom, D., McLeod, L., Sherif, B., Nelson, L., McSorley, D. (2017). Longitudinal modeling approaches to assess the association between changes in 2 clinical outcome assessments. Ther Innov Regul Sci. 2017 Sep 26.
Patrick, D. L., Burke, L. B., Gwaltney, C. J., et al. (2011a). Content validity–establishing and reporting the evidence in newly developed patient-reported outcomes (PRO) instruments for medical product evaluation: ISPOR PRO good research practices task force report: part 1–eliciting concepts for a new PRO instrument. Value Health, 14, 967–977.
Patrick, D. L., Burke, L. B., Gwaltney, C. J., et al. (2011b). Content validity–establishing and reporting the evidence in newly developed patient-reported outcomes (PRO) instruments for medical product evaluation: ISPOR PRO good research practices task force report: part 2—assessing respondent understanding. Value Health, 14, 978–988.
Reeve, B. B., Wyrwich, K. W., Wu, A. W., et al. (2013). ISOQOL recommends minimum standards for patient-reported outcome measures used in patient-centered outcomes and comparative effectiveness research. Quality of Life Research, 22, 1889–1905.
Revicki, D. A., Erickson, P. A., Sloan, J. A., et al; Mayo/FDA Patient-Reported Outcomes Consensus Meeting Group. (2007). Interpreting and reporting results based on patient-reported outcomes. Value Health 10, S116–24.
Revicki, D., Hays, R., Cella, D., & Sloan, J. (2008). Recommended methods for determining responsiveness and minimally important differences for patient-reported outcomes. Journal of Clinical Epidemiology, 61, 102–109.
Rothman, M., Gnanasakthy, A., Wicks, P., & Papadopoulos, E. J. (2015). Can we use social media to support content validity of patient-reported outcome instruments in medical product development? Value Health, 18, 1–4.
Schuck, P. (2004). Assessing reproducibility for interval data in health-related quality of life questionnaires: Which coefficient should be used? Quality of Life Research, 13, 571–586.
Streiner, D. L., Norman, G. R., & Cairney, J. (2015). Health measurement scales: A practical guide to their development and use (5th ed.). New York: Oxford University Press.
Sudman, S., & Bradburn, N. M. (1982). Asking questions: A practical guide to questionnaire design. San Francisco: Jossey-Bass.
Thissen, D., Steinberg, L., & Wainer, H. (1993). Detection of differential item functioning using the parameters of item response models. In P. W. Holland & H. Wainer (Eds.), Differential item functioning (pp. 67–113). Hillsdale, NJ: Lawrence Erlbaum.
Tucker, L. R., & Lewis, C. (1973). A reliability coefficient for maximum likelihood factor analysis. Psychometrika, 38, 1–10.
Walton, M. K., Powers, J. H., Hobart, J., et al. (2015). Clinical outcome assessments: Conceptual foundation. Report of the ISPOR clinical outcomes assessment – Emerging good practices for outcomes research task force. Value Health 18, 741–752. https://doi.org/10.1016/j.jval.2015.08.006.
Wild, D., Grove, A., Martin, M., et al. (2005). Principles of good practice for the translation and cultural adaptation process for patient-reported outcomes (PRO) measures: Report of the ISPOR task force for translation and cultural adaptation. Value Health, 8, 94–104.
Williams, V., McLeod, L., & Nelson, L. (2015). Advances in the evaluation of longitudinal construct validity of clinical outcome assessments. Therapeutic Innovation and Regulatory Science, 49, 805–812.
Willis, G. B. (2005). Cognitive interviewing: a tool for improving questionnaire design. Thousand Oaks: Sage.
Willis, G. B. (2015). Analysis of the cognitive interview in questionnaire design. understanding qualitative research. New York: Oxford University Press.
Wyrwich, K. W., Norquist, J. M., Lenderking, W. R., Acaster, S.; Industry Advisory Committee of International Society for Quality of Life Research (ISOQOL). (2013). Methods for interpreting change over time in patient-reported outcome measures. Quality of Life Research 22, 475–483.
Wyrwich, K. W., Krishnan, S., Poon, J. L., et al. (2015). Interpreting important health-related quality of life change using the Haem-A-QoL. Haemophilia, 21, 578–584. https://doi.org/10.1111/hae.12642.
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. J Clin Epidemiol, 52:861–873.
Acknowledgements
We thank Lauren Nelson for helpful comments on earlier versions of this chapter. In addition, we thank Lindsey Norcross and Jason Mathes for their editorial and graphical support.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer Nature Singapore Pte Ltd.
About this chapter
Cite this chapter
McLeod, L.D., Fehnel, S.E., Cappelleri, J.C. (2018). Patient-Reported Outcome Measures: Development and Psychometric Evaluation. In: Peace, K., Chen, DG., Menon, S. (eds) Biopharmaceutical Applied Statistics Symposium . ICSA Book Series in Statistics. Springer, Singapore. https://doi.org/10.1007/978-981-10-7829-3_13
Download citation
DOI: https://doi.org/10.1007/978-981-10-7829-3_13
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-10-7828-6
Online ISBN: 978-981-10-7829-3
eBook Packages: Mathematics and StatisticsMathematics and Statistics (R0)