Advertisement

Quality of Life Research

, Volume 28, Issue 5, pp 1119–1128 | Cite as

Patient-reported outcomes in stroke clinical trials 2002–2016: a systematic review

  • Eboni G. Price-HaywoodEmail author
  • Jewel Harden-Barrios
  • Christopher Carr
  • Laya Reddy
  • Lydia A. Bazzano
  • Mieke L. van Driel
Review

Abstract

Objective

Given the global and economic burden of stroke as a major cause of long-term disability, patient-reported outcomes (PRO) data from clinical trials can elucidate differential benefits/harms of interventions from patients’ perspectives and influence clinical decision making in stroke care management.

Methods

This systematic review examines stroke-related randomized controlled trials (RCT) published in 12 high-impact journals between 2002 and 2016 for (1) associations between trial characteristics and the reporting of PRO measures; and (2) psychometric properties of PRO instruments used in these studies. The study combines clinical trials identified in a prior review with trials identified with an updated literature search.

Results

Only 34 of 159 stroke-related RCTs reported PRO measures. Among the 34 trials, most were published in rehabilitation and general medical journals, were conducted in the United States or Europe, were funded by government/non-industry sponsors, and focused on post-stroke care. Thirty-one PRO instruments were employed in these studies. Only 5 instruments were stroke-specific measures, whereas the remaining 26 instruments were generic measures. Eight instruments assessed functional status, 9 measured quality of life, and 14 assessed symptoms. The most common health domains measured were emotional status and physical function.

Conclusions

This study highlights the paucity of information from patients’ perspective in stroke-related RCTs. This trend may change over time as researchers increase adherence to reporting guidelines for clinical trial protocols.

Keywords

Stroke Randomized controlled trial Patient-reported outcome measures 

Notes

Acknowledgements

The staff of the Ochsner Medical Library conducted the literature search. Jeffrey Burton, PhD (Ochsner Center for Applied Health Services Research) conducted the descriptive statistics. Richard Zweifler, MD (Ochsner Neurology Stroke Center) conducted a review of the manuscript. Abstracts of this work were presented at the 2017 Southern Society for Clinical Investigations regional conference and 2017 International Stroke Conference.

Compliance with ethical standards

Conflict of interest

None of the authors have financial disclosures or conflicts of interest to report with this study.

Supplementary material

11136_2018_2053_MOESM1_ESM.docx (32 kb)
Supplementary material 1 (DOCX 32 KB)

References

  1. 1.
    Benjamin, E. J., Blaha, M. J., Chiuve, S. E., Cushman, M., Das, S. R., Deo, R., et al. American Heart Association Statistics Committee and Stroke Statistics Subcommittee. (2017). Heart disease and stroke statistics-2017 update: a report from the American Heart Association. Circulation, 135(10), e146–e603.CrossRefGoogle Scholar
  2. 2.
    Salinas, J., Sprinkhuizen, S. M., Ackerson, T., Bernhardt, J., Davie, C., George, M. G., et al. (2016). An international standard set of patient-centered outcome measures after stroke. Stroke, 47(1), 180–186.CrossRefGoogle Scholar
  3. 3.
    Food and Drug Administration. (2009). Guidance for industry: patient-reported outcome measures: use in medical product development to support labeling claims. U.S. Department of Health and Human Services. Retrieved 19 March, 2018, from https://www.fda.gov/downloads/drugs/guidancecomplianceregulatoryinformation/guidances/ucm193282.pdf.
  4. 4.
    Magin, P., Victoire, A., Zhen, X. M., Furler, J., Pirotta, M., Lasserson, D. S., et al. (2013). Under-reporting of socioeconomic status of patients in stroke trials: Adherence to CONSORT principles. Stroke, 44(10), 2920–2922.CrossRefGoogle Scholar
  5. 5.
    Ahmed, S., Berzon, R. A., Revicki, D. A., Lenderking, W. R., Moinpour, C. M., Basch, E., et al. International Society for Quality of Life Research (2012). The use of patient-reported outcomes (PRO) within comparative effectiveness research: Implications for clinical practice and health care policy. Med Care, 50(12), 1060–1070.CrossRefGoogle Scholar
  6. 6.
    Stewart, A. L., & Ware, J. E. (1992). Measuring functioning and well-being: The medical outcomes study approach. Durham: Duke University Press.Google Scholar
  7. 7.
    Firth, D., & “Bias (1993). Reduction of maximum likelihood estimates. Biometrika, 80, 27–38.CrossRefGoogle Scholar
  8. 8.
    van Straten, A., de Haan, R. J., Limburg, M., Schuling, J., Bossuyt, P. M., & van den Bos, G. A. M. (1997). A stroke-adapted 30-item version of the sickness impact profile to assess quality of life (sa-sip30). Stroke, 28, 2155–2161.CrossRefGoogle Scholar
  9. 9.
    Hilari, K., Byng, S., Lamping, D. L., & Smith, S. C. (2003). Stroke and aphasia quality of life scale-39 (saqol-39): Evaluation of acceptability, reliability, and validity. Stroke, 34, 1944–1950.CrossRefGoogle Scholar
  10. 10.
    Watkins, C., Leathley, M., & Davies, A. (1998). The stroke expectations questionnaire (seq): Identification of patients’ ideas about recovery. Clinical Rehabilitation, 12, 173–175.Google Scholar
  11. 11.
    Watkins, C., Leathley, M., & Davies, A. (1998). The stroke expectations questionnaire (seq): A predictor of outcome? Clinical Rehabilitation, 12, 173.Google Scholar
  12. 12.
    Duncan, P. W., Wallace, D., Lai, S. M., Johnson, D., Embretson, S., & Laster, L. J. (1999). The stroke impact scale version 2.0. Evaluation of reliability, validity, and sensitivity to change. Stroke, 30, 2131–2140.CrossRefGoogle Scholar
  13. 13.
    Jenkinson, C., Fitzpatrick, R., Crocker, H., & Peters, M. (2013). The stroke impact scale: Validation in a uk setting and development of a sis short form and sis index. Stroke, 44, 2532–2535.CrossRefGoogle Scholar
  14. 14.
    Botner, E. M., Miller, W. C., & Eng, J. J. (2005). Measurement properties of the activities-specific balance confidence scale among individuals with stroke. Disability and Rehabilitation, 27, 156–163.CrossRefGoogle Scholar
  15. 15.
    Pal, J., Hale, L. A., & Skinner, M. A. (2005). Investigating the reliability and validity of two balance measures in adults with stroke. International Journal of Therapy and Rehabilitation, 12, 308–315.CrossRefGoogle Scholar
  16. 16.
    Turnbull, J. C., Kersten, P., Habib, M., McLellan, L., Mullee, M. A., & George, S. (2000). Validation of the frenchay activities index in a general population aged 16 years and older. Archives of Physical Medicine and Rehabilitation, 81, 1034–1038.CrossRefGoogle Scholar
  17. 17.
    Wade, D. T., Legh-Smith, J., & Langton Hewer, R. (1985). Social activities after stroke: Measurement and natural history using the frenchay activities index. International Rehabilitation Medicine, 7, 176–181.CrossRefGoogle Scholar
  18. 18.
    Schuling, J., de Haan, R., Limburg, M., & Groenier, K. H. (1993). The frenchay activities index. Assessment of functional status in stroke patients. Stroke, 24, 1173–1177.CrossRefGoogle Scholar
  19. 19.
    Uswatte, G., Taub, E., Morris, D., Light, K., & Thompson, P. A. (2006). The motor activity log-28: Assessing daily use of the hemiparetic arm after stroke. Neurology, 67, 1189–1194.CrossRefGoogle Scholar
  20. 20.
    Uswatte, G., Taub, E., Morris, D., Vignolo, M., & McCulloch, K. (2005). Reliability and validity of the upper-extremity motor activity log-14 for measuring real-world arm use. Stroke, 36, 2493–2496.CrossRefGoogle Scholar
  21. 21.
    Gladman, J. R., Lincoln, N. B., & Adams, S. A. (1993). Use of the extended adl scale with stroke patients. Age and Ageing, 22, 419–424.CrossRefGoogle Scholar
  22. 22.
    Nouri, F., & Lincoln, N. (1987). An extended activities of daily living scale for stroke patients. Clinical Rehabilitation, 1, 301–305.CrossRefGoogle Scholar
  23. 23.
    Lennon, S., & Johnson, L. (2000). The modified rivermead mobility index: Validity and reliability. Disability and Rehabilitation, 22, 833–839.CrossRefGoogle Scholar
  24. 24.
    Drummond, A. E., Parker, C. J., Gladman, J. R., Logan, P. A., & Group, T. S. (2001). Development and validation of the Nottingham leisure questionnaire (nlq). Clinical Rehabilitation, 15, 647–656.CrossRefGoogle Scholar
  25. 25.
    Rimmer, J. H., Riley, B. B., & Rubin, S. S. (2001). A new measure for assessing the physical activity behaviors of persons with disabilities and chronic health conditions: The physical activity and disability survey. American Journal of Health Promotion: AJHP, 16, 34–42.CrossRefGoogle Scholar
  26. 26.
    Washburn, R. A., Smith, K. W., Jette, A. M., & Janney, C. A. (1993). The physical activity scale for the elderly (pase): Development and evaluation. Journal of Clinical Epidemiology, 46, 153–162.CrossRefGoogle Scholar
  27. 27.
    Dorman, P. J., Waddell, F., Slattery, J., Dennis, M., & Sandercock, P. (1997). Is the euroqol a valid measure of health-related quality of life after stroke? Stroke, 28, 1876.CrossRefGoogle Scholar
  28. 28.
    Wilke, C. T., Pickard, A. S., Walton, S. M., Moock, J., Kohlmann, T., & Lee, T. A. (2010). Statistical implications of utility weighted and equally weighted hrql measures: An empirical study. Health Economics, 19, 101–110.Google Scholar
  29. 29.
    Goldberg, D. P., & Hillier, V. F. (1979). A scaled version of the general health questionnaire. Psychological Medicine, 9, 139–145.CrossRefGoogle Scholar
  30. 30.
    Goldberg, D. P., Gater, R., Sartorius, N., Ustun, T. B., Piccinelli, M., Gureje, O., et al. (1997). The validity of two versions of the GHQ in the who study of mental illness in general health care. Psychological Medicine, 27, 191–197.CrossRefGoogle Scholar
  31. 31.
    Cheak-Zamora, N. C., Wyrwich, K. W., & McBride, T. D. (2009). Reliability and validity of the sf-12v2 in the medical expenditure panel survey. Quality of Life Research, 18, 727–735.CrossRefGoogle Scholar
  32. 32.
    Gandek, B., Ware, J. E., Aaronson, N. K., Apolone, G., Bjorner, J. B., Brazier, J. E., et al. (1998). Cross-validation of item selection and scoring for the sf-12 health survey in nine countries: Results from the iqola project. International quality of life assessment. Journal of Clinical Epidemiology, 51, 1171–1178.CrossRefGoogle Scholar
  33. 33.
    Bohannon, R. W., Maljanian, R., Lee, N., & Ahlquist, M. (2004). Measurement properties of the short form (sf)-12 applied to patients with stroke. International Journal of Rehabilitation Research, 27, 151–154.CrossRefGoogle Scholar
  34. 34.
    McHorney, C. A., Ware, J. E. Jr., Lu, J. F., & Sherbourne, C. D. (1994). The mos 36-item short-form health survey (sf-36): III. Tests of data quality, scaling assumptions, and reliability across diverse patient groups. Medical Care, 32, 40–66.CrossRefGoogle Scholar
  35. 35.
    McHorney, C. A., Ware, J. E. Jr., & Raczek, A. E. (1993). The mos 36-item short-form health survey (sf-36): II. Psychometric and clinical tests of validity in measuring physical and mental health constructs. Medical Care, 31, 247–263.CrossRefGoogle Scholar
  36. 36.
    McHorney, C. A., Ware, J. E. Jr., Rogers, W., Raczek, A. E., & Lu, J. F. (1992). The validity and relative precision of mos short- and long-form health status scales and dartmouth coop charts. Results from the medical outcomes study. Medical Care, 30, Ms253–M265.CrossRefGoogle Scholar
  37. 37.
    Beck, A. T., Steer, R. A., & Garbin, M. G. (1988). Psychometric properties of the beck depression inventory: Twenty-five years of evaluation. Clinical Psychology Review, 8, 77–100.CrossRefGoogle Scholar
  38. 38.
    Segal, D. L., Coolidge, F. L., Cahill, B. S., & O’Riley, A. A. (2008). Psychometric properties of the beck depression inventory II (BDI-II) among community-dwelling older adults. Behavior Modification, 32, 3–20.CrossRefGoogle Scholar
  39. 39.
    Radloff, L. S. (1977). The ces-d scale: A self-report depression scale for research in the general population. Applied Psychological Measurement, 1, 385–401.CrossRefGoogle Scholar
  40. 40.
    Van Dam, N. T., & Earleywine, M. (2011). Validation of the center for epidemiologic studies depression scale–revised (cesd-r): Pragmatic depression assessment in the general population. Psychiatry Research, 186, 128–132.CrossRefGoogle Scholar
  41. 41.
    Worm-Smeitink, M., Gielissen, M., Bloot, L., van Laarhoven, H. W. M., van Engelen, B. G. M., van Riel, P., et al. (2017). The assessment of fatigue: Psychometric qualities and norms for the checklist individual strength. Journal of Psychosomatic Research, 98, 40–46.CrossRefGoogle Scholar
  42. 42.
    Beurskens, A., Bultmann, U., Kant, I., Vercoulen, J., Bleijenberg, G., & Swaen, G. (2000). Fatigue among working people: Validity of a questionnaire measure. Occupational and Environmental Medicine, 57, 353–357.CrossRefGoogle Scholar
  43. 43.
    Lerdal, A., & Kottorp, A. (2011). Psychometric properties of the fatigue severity scale-rasch analyses of individual responses in a norwegian stroke cohort. International Journal of Nursing Studies, 48, 1258–1265.CrossRefGoogle Scholar
  44. 44.
    Nadarajah, M., Mazlan, M., Abdul-Latif, L., & Goh, H. T. (2016) Test-retest reliability, internal consistency and concurrent validity of fatigue severity scale in measuring post-stroke fatigue. European Journal of Physical and Rehabilitation Medicine, 53(5), 703–709.Google Scholar
  45. 45.
    Yesavage, J. A., & Sheikh, J. I. (2008). 9/geriatric depression scale (gds). Clinical Gerontologist, 5, 165–173.CrossRefGoogle Scholar
  46. 46.
    Brown, L. M., & Schinka, J. A. (2005). Development and initial validation of a 15-item informant version of the geriatric depression scale. International Journal of Geriatric Psychiatry, 20, 911–918.CrossRefGoogle Scholar
  47. 47.
    Bjelland, I., Dahl, A. A., Haug, T. T., & Neckelmann, D. (2002). The validity of the hospital anxiety and depression scale. An updated literature review. Journal of Psychosomatic Research, 52, 69–77.CrossRefGoogle Scholar
  48. 48.
    Zigmond, A. S., & Snaith, R. P. (1983). The hospital anxiety and depression scale. Acta Psychiatrica Scandinavica, 67, 361–370.CrossRefGoogle Scholar
  49. 49.
    Johnston, M., Pollard, B., & Hennessey, P. (2000). Construct validation of the hospital anxiety and depression scale with clinical populations. Journal of Psychosomatic Research, 48, 579–584.CrossRefGoogle Scholar
  50. 50.
    Snaith, R. P., & Taylor, C. M. (1985). Rating scales for depression and anxiety: A current perspective. British Journal of Clinical Pharmacology, 19(Suppl 1), 17 s–20 s.CrossRefGoogle Scholar
  51. 51.
    Winkens, I., Van Heugten, C. M., Fasotti, L., & Wade, D. T. (2009). Reliability and validity of two new instruments for measuring aspects of mental slowness in the daily lives of stroke patients. Neuropsychological Rehabilitation, 19, 64–85.CrossRefGoogle Scholar
  52. 52.
    Wikberg, C., Nejati, S., Larsson, M. E., Petersson, E. L., Westman, J., Ariai, N., et al. Comparison between the montgomery-asberg depression rating scale-self and the beck depression inventory ii in primary care. The Primary Care Companion for CNS Disorders. 2015;17.Google Scholar
  53. 53.
    McNair, D. M., Lorr, M., & Droppleman, L. F. (1971). Manual for the profile of mood states. San Diego: Educational and Industrial Testing Services.Google Scholar
  54. 54.
    Lievaart, M., Franken, I. H., & Hovens, J. E. (2016). Anger assessment in clinical and nonclinical populations: Further validation of the state-trait anger expression inventory-2. Journal of Clinical Psychology, 72, 263–278.CrossRefGoogle Scholar
  55. 55.
    Mahoney, J., Drinka, T. J., Abler, R., Gunter-Hunt, G., Matthews, C., Gravenstein, S., et al. (1994). Screening for depression: Single question versus GDS. Journal of the American Geriatrics Society, 42, 1006–1008.CrossRefGoogle Scholar
  56. 56.
    Calvert, M., Blazeby, J., Altman, D. G., Revicki, D. A., Moher, D., & Brundage, M. D., CONSORT PRO Group. (2013). Reporting of patient-reported outcomes in randomized trials: The CONSORT PRO extension. JAMA, 309(8), 814–822.CrossRefGoogle Scholar
  57. 57.
    Vodicka, E., Kim, K., Devine, E. B., Gnanasakthy, A., Scoggins, J. F., & Patrick, D. L. (2015). Inclusion of patient-reported outcome measures in registered clinical trials: Evidence from ClinicalTrials.gov (2007–2013). Contemporary Clinical Trials, 43, 1–9.CrossRefGoogle Scholar
  58. 58.
    Mercieca-Bebber, R., Rouette, J., Calvert, M., King, M. T., McLeod, L., Holch, P., Palmer, M. J., & Brundage, M. (2017). International Society for Quality of Life Research (ISOQOL) best practice for PROs—reporting taskforce. Preliminary evidence on the uptake, use and benefits of the CONSORT-PRO extension. Quality of Life Research, 26(6), 1427–1437.CrossRefGoogle Scholar
  59. 59.
    Calvert, M., Kyte, D., Mercieca-Bebber, R., Slade, A., Chan, A. W., King, M. T., et al. (2018). Guidelines for inclusion of patient-reported outcomes in clinical trial protocols: The SPIRIT-PRO extension. JAMA, 319(5), 483–494.CrossRefGoogle Scholar
  60. 60.
    Kane, R. L., & Radosevich, D. M. (LLC 2011). Conducting health outcomes research. Sudbury: Johns & Bartlett Learning.Google Scholar
  61. 61.
    Cella, D., Nowinski, C., Peterman, A., Victorson, D., Miller, D., Lai, J.-S., et al. (2011). The neurology quality of life measurement initiative. Archives of Physical Medicine and Rehabilitation, 92(10 Suppl), S28–S36.CrossRefGoogle Scholar
  62. 62.
    Gershon, R. C., Wagster, M. V., Hendrie, H. C., Fox, N. A., Cook, K. F., & Nowinski, C. J. (2013). NIH toolbox for assessment of neurological and behavioral function. Neurology, 80(11), S2–S6.CrossRefGoogle Scholar
  63. 63.
    Reeve, B. B., Wyrwich, K. W., Wu, A. W., Velikova, G., Terwee, C. B., Snyder, C. F., 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(8), 1889–1905.CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  1. 1.Center for Applied Health Services ResearchOchsner Health SystemNew OrleansUSA
  2. 2.Ochsner Clinical SchoolUniversity of QueenslandNew OrleansUSA
  3. 3.Tulane University School of Public Health and Tropical MedicineNew OrleansUSA
  4. 4.Primary Care Clinical Unit, Faculty of MedicineUniversity of QueenslandBrisbaneAustralia

Personalised recommendations