Skip to main content
SpringerLink
Log in

Reliability, validity, and minimally important differences of the SF-6D in systemic sclerosis

  • Original Paper
  • Published:
Quality of Life Research Aims and scope Submit manuscript

Abstract

ObjectivesTo evaluate the reliability and validity and estimate the minimally important difference (MID) for the SF-6D in patients with systemic sclerosis (SSc). Subjects We used data from two clinical studies to analyze the SF-6D in patients with SSc: Study 1 was a cross-sectional observational study (N = 107) designed to assess three direct preference measures—the rating scale, time trade-off, and standard gamble (SG) in patients with diffuse SSc and limited SSc, and Study 2 was a 12-month randomized, placebo-controlled, clinical trial (N = 168) assessing oral bovine collagen versus placebo in diffuse SSc. Methods We assessed the test–retest reliability of the SF-6D in Study 2 over a mean (SD) 4.8 (3.0)-week interval and the agreement between the SF-6D and direct preference measures in Study 1 using intraclass correlations (ICC). The MID was estimated using three different anchors—the SF-36 change in health item (patients who answered “somewhat better” formed the MID group), the Health Assessment Questionnaire-Disability Index (HAQ-DI; change of ≥0.14 and ≥0.22) and the skin score (change of ≥5.3). Results The mean (SD) SF-6D scores were 0.61 (0.12) in Study 1 and 0.64 (0.13) in Study 2. Test–retest reliability for the SF-6D was high (ICC = 0.82 [95% CI: 0.76, 0.87]). Agreement between the SF-6D and three direct preferences measures was poor to moderate (0.16–0.52). The MID estimate for the SF-6D using the change in SF-36 item −0.012 and this level of change was similar to the no change group. The mean MID estimate for the SF-6D improvement using the HAQ-DI and skin score as anchors was 0.035 (effect size of 0.27). Conclusion This is the first study to assess the SF-6D in SSc. The SF-6D is reliable and valid in patients with SSc. We provide MID estimates that can aid in calculating sample size for clinical trials involving patients with diffuse SSc.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1

Similar content being viewed by others

References

  1. Mayes, M. D., Lacey, J. V., Jr., Beebe-Dimmer, J., Gillespie, B. W., Cooper, B., & Laing, T. J., et al. (2003). Prevalence, incidence, survival, and disease characteristics of systemic sclerosis in a large US population. Arthritis and Rheumatism, 48(8), 2246–2255.

    Article  PubMed  Google Scholar 

  2. Clements, P. J. (2000). Systemic sclerosis (scleroderma) and related disorders: Clinical aspects. Baillieres Best Practice & Research Clinical Rheumatology, 14(1), 1–16.

    Article  CAS  Google Scholar 

  3. Charles, C., Clements, P., & Furst, D. E. (2006). Systemic sclerosis: hypothesis-driven treatment strategies. Lancet, 367(9523), 1683–1691.

    Article  PubMed  Google Scholar 

  4. Altman, R. D., Medsger, T. A., Jr., Bloch, D. A., & Michel, B. A. (1991). Predictors of survival in systemic sclerosis (scleroderma). Arthritis and Rheumatism, 34(4), 403–413.

    Article  PubMed  CAS  Google Scholar 

  5. Malcarne, V. L. (2004). Psychological adjustment in systemic sclerosis. In P. J. Clements & D. E. Furst (Eds.), Systemic sclerosis (pp. 331–350). Philadelphia: Lippincott Williams and Wilkins.

    Google Scholar 

  6. Khanna, D. (2006). Health-related quality of life: A primer with focus on scleroderma. Scleroderma Care and Research, 3(2), 3–13 (Accessed at http://www.sctconline.org/pdfs/SCARV3N2.pdf on March 2nd, 2007).

  7. Ware, J., Kosinski, M., & Dewey, J. (2000). How to score version two of the SF-36 health survey. Lincoln, RI: Quality Metric Incorporated.

    Google Scholar 

  8. Fries, J. F., Spitz, P., Kraines, R. G., & Holman, H. R. (1980). Measurement of patient outcome in arthritis. Arthritis and Rheumatism, 23(2), 137–145.

    Article  PubMed  CAS  Google Scholar 

  9. Torrance, G. (1986). Measurement of health state utilities for economic appraisal. Journal of Health Economics, 5, 1–30.

    Article  PubMed  CAS  Google Scholar 

  10. Von Neumann, J., & Morgenstern, O. (1953). Theory of games and economic behavior. New York: Wiley.

    Google Scholar 

  11. Froberg, D. G., & Kane, R. L. (1989). Methodology for measuring health-state preferences–II: Scaling methods. Journal of Clinical Epidemiology, 42(5), 459–471.

    Article  PubMed  CAS  Google Scholar 

  12. Brazier, J., Roberts, J., & Deverill, M. (2002). The estimation of a preference-based measure of health from the SF-36. Journal of Health Economics, 21(2), 271–292.

    Article  PubMed  Google Scholar 

  13. Khanna, D., Ahmed, M., Furst, D. E., Ginsburg, S. S., Park, G. S., & Hornung, R., et al. (2007). Health values of patients with systemic sclerosis. Arthritis and Rheumatism, 57(1), 86–93.

    Article  PubMed  Google Scholar 

  14. 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.

    Article  PubMed  CAS  Google Scholar 

  15. van Walraven, C., Mahon, J. L., Moher, D., Bohm, C., & Laupacis, A. (1999). Surveying physicians to determine the minimal important difference: Implications for sample-size calculation. Journal of Clinical Epidemiology, 52(8), 717–723.

    Article  PubMed  Google Scholar 

  16. Hays, R. D., Farivar, S., & Liu, H. (2005). Approaches and recommendations for estimating minimally important differences for health-related quality of life measures. COPD: Journal of Chronic Obstructive Pulmonary Disease, 2, 63–67.

    Google Scholar 

  17. Preliminary criteria for the classification of systemic sclerosis (scleroderma). (1980). Subcommittee for scleroderma criteria of the American Rheumatism Association Diagnostic and Therapeutic Criteria Committee. Arthritis and Rheumatism, 23(5), 581–590.

    Article  Google Scholar 

  18. Postlethwaite, A., Furst, D., Wong, W. K., & Clements, P. (2005). Oral tolerance (OT). Induction to type I collagen (CI) significantly reduces the skin score in patients with diffuse systemic sclerosis (SSc) with late-phase disease. Results of a NIAMS/NIAID multicenter phase II placebo-controlled double blind clinical trial. Arthritistis and Rheumatism [Abstract].

  19. Clements, P., Lachenbruch, P., Siebold, J., White, B., Weiner, S., & Martin, R., et al. (1995). Inter and intraobserver variability of total skin thickness score (modified Rodnan TSS) in systemic sclerosis. The Journal of Rheumatology, 22(7), 1281–1285.

    PubMed  CAS  Google Scholar 

  20. Crapo, R. O., Morris, A. H., & Gardner, R. M. (1981). Reference spirometric values using techniques and equipment that meet ATS recommendations. The American Review of Respiratory Disease, 123(6), 659–664.

    PubMed  CAS  Google Scholar 

  21. Khanna, D., Furst, D. E., Clements, P. J., Park, G. S., Hays, R. D., & Yoon, J., et al. (2005). Responsiveness of the SF-36 and the Health Assessment Questionnaire Disability Index in a systemic sclerosis clinical trial. Journal of Rheumatology, 32(5), 832–840.

    PubMed  Google Scholar 

  22. Steen, V. D., & Medsger, T. A., Jr. (1997). The value of the Health Assessment Questionnaire and special patient-generated scales to demonstrate change in systemic sclerosis patients over time. Arthritis and Rheumatism, 40(11), 1984–1991.

    Article  PubMed  CAS  Google Scholar 

  23. UMaker User’s Manual. (1999). UMDNJ Technical Report.

  24. Arias, E. (2004). United States life tables, 2002. National Vital Statistics Reports, 53(6), 1–38.

    Google Scholar 

  25. Nunnally, J. (1978). Psychometric theory. New York: McGraw-Hill.

    Google Scholar 

  26. Franzblau, A. (1958). A primer of statistics for non-statisticians. New York: Brace & World.

  27. Khanna, D., Clements, P. J., Furst, D. E., Chon, Y., Elashoff, R., & Roth, M. D., et al. (2005). Correlation of the degree of dyspnea with health-related quality of life, functional abilities, and diffusing capacity for carbon monoxide in patients with systemic sclerosis and active alveolitis: Results from the Scleroderma Lung Study. Arthritis and Rheumatism, 52(2), 592–600.

    Article  PubMed  Google Scholar 

  28. Clements, P. J., Wong, W. K., Hurwitz, E. L., Furst, D. E., Mayes, M., & White, B., et al. (2001). The Disability Index of the Health Assessment Questionnaire is a predictor and correlate of outcome in the high-dose versus low-dose penicillamine in systemic sclerosis trial. Arthritis and Rheumatism, 44(3), 653–661.

    Article  PubMed  CAS  Google Scholar 

  29. Osoba, D., Bezjak, A., Brundage, M., Zee, B., Tu, D., & Pater, J. (2005). Analysis and interpretation of health-related quality-of-life data from clinical trials: Basic approach of The National Cancer Institute of Canada Clinical Trials Group. European Journal of Cancer, 41(2), 280–287.

    Article  PubMed  Google Scholar 

  30. Cole, J. C., Khanna, D., Clements, P. J., Seibold, J. R., Tashkin, D. P., & Paulus, H. E., et al. (2006). Single-factor scoring validation for the Health Assessment Questionnaire-Disability Index (HAQ-DI) in patients with systemic sclerosis and comparison with early rheumatoid arthritis patients. Quality of Life Research, 15(8), 1383–1394.

    Article  PubMed  Google Scholar 

  31. Wells, G. A., Tugwell, P., Kraag, G. R., Baker, P. R., Groh, J., & Redelmeier, D. A. (1993). Minimum important difference between patients with rheumatoid arthritis: The patient’s perspective. Journal of Rheumatology, 20(3), 557–560.

    PubMed  CAS  Google Scholar 

  32. Khanna, D., Furst, D. E., Hays, R. D., Park, G. S., Wong, W. K., & Seibold, J. R., et al. (2006, October). Minimally important difference in diffuse systemic sclerosis – results from the d-penicillamine study. Annals of the Rheumatic Diseases, 65(10), 1325–1329.

    Google Scholar 

  33. Becker, L. A. (2000). Effect size. Accessed on October 12, 2006 from http://web.uccs.edu/lbecker/Psy590/es.htm.

  34. Cohen, J. (1992). A power primer. Psychological Bulletin, 112, 155–159.

    Article  Google Scholar 

  35. Kopec, J. A., & Willison, K. D. (2003). A comparative review of four preference-weighted measures of health-related quality of life. Journal of Clinical Epidemiology, 56(4), 317–325.

    Article  PubMed  Google Scholar 

  36. Marra, C. A., Esdaile, J. M., Guh, D., Kopec, J. A., Brazier, J. E., & Koehler, B. E., et al. (2004). A comparison of four indirect methods of assessing utility values in rheumatoid arthritis. Medical Care, 42(11), 1125–1131.

    Article  PubMed  Google Scholar 

  37. Brazier, J., Roberts, J., Tsuchiya, A., & Busschbach, J. (2004). A comparison of the EQ-5D and SF-6D across seven patient groups. Health Economics, 13(9), 873–884.

    Article  PubMed  Google Scholar 

  38. Hays, R. D. (2005). Reliability and validity (including responsiveness). In P. Fayers & R. D. Hays (Eds.), Assessing quality of life in clinical trials (pp. 25–39). New York: Oxford.

    Google Scholar 

  39. Feeny, D., Wu, L., & Eng, K. (2004). Comparing short form 6D, standard gamble, and Health Utilities Index Mark 2 and Mark 3 utility scores: Results from total hip arthroplasty patients. Quality of Life Research, 13(10), 1659–1670.

    Article  PubMed  Google Scholar 

  40. Ariza-Ariza, R., Hernandez-Cruz, B., Carmona, L., Dolores Ruiz-Montesinos, M., Ballina, J., & Navarro-Sarabia, F. (2006). Assessing utility values in rheumatoid arthritis: A comparison between time trade-off and the EuroQol. Arthritis and Rheumatism, 55(5), 751–756.

    Article  PubMed  Google Scholar 

  41. Khanna, D., Yan, X., Tashkin, D. P., Furst, D. E., Elashoff, D., Roth, M., et al. (2007). Impact of oral cyclophosphamide on health-related quality of life in patients with active scleroderma lung disease-results from the scleroderma lung study. Arthritis and Rheumatism (in press).

  42. 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.

    Article  PubMed  Google Scholar 

  43. Guyatt, G. H., Feeny, D. H., & Patrick, D. L. (1993). Measuring health-related quality of life. Annals of Internal Medicine, 118(8), 622–629.

    PubMed  CAS  Google Scholar 

  44. Guyatt, G. H., Norman, G. R., Juniper, E. F., & Griffith, L. E. (2002). A critical look at transition ratings. Journal of Clinical Epidemiology, 55(9), 900–908.

    Article  PubMed  Google Scholar 

  45. 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.

    Article  PubMed  Google Scholar 

  46. Yost, K. J., Sorensen, M. V., Hahn, E. A., Glendenning, G. A., Gnanasakthy, A., & Cella, D. (2005). Using multiple anchor- and distribution-based estimates to evaluate clinically meaningful change on the Functional Assessment of Cancer Therapy-Biologic Response Modifiers (FACT-BRM) instrument. Value Health, 8(2), 117–127.

    Article  PubMed  Google Scholar 

  47. Tsevat, J., Weeks, J. C., Guadagnoli, E., Tosteson, A. N., Mangione, C. M., & Pliskin, J. S., et al. (1994). Using health-related quality-of-life information: Clinical encounters, clinical trials, and health policy. Journal of General Internal Medicine, 9(10), 576–582.

    Article  PubMed  CAS  Google Scholar 

  48. Patrick, D. L., & Erickson, P. (1993). Health status and health policy : Quality of life in health care evaluation and resource allocation. New York: Oxford University Press.

    Google Scholar 

  49. Drummond, M. (2001). Introducing economic and quality of life measurements into clinical studies. Annals of Medicine, 33(5), 344–349.

    PubMed  CAS  Google Scholar 

  50. Hays, R. D., & Woolley, J. M. (2000). The concept of clinically meaningful difference in health-related quality-of-life research. How meaningful is it? Pharmacoeconomics, 18(5), 419–423.

    Article  PubMed  CAS  Google Scholar 

  51. Torrance, G. W. (1997). Preferences for health outcomes and cost-utility analysis. The American Journal of Managed Care, 3(Suppl.), S8–S20.

    PubMed  Google Scholar 

  52. Revicki, D., & Fairclough, D. L. (2005). Preventing missing data. In P. Fayers & R. D. Hays (Eds.), Assessing quality of life in clinical trials (pp. 167–178). New York: Oxford University Press.

    Google Scholar 

  53. Crosby, R. D., Kolotkin, R. L., & Williams, G. R. (2003). Defining clinically meaningful change in health-related quality of life. Journal of Clinical Epidemiology, 56(5), 395–407.

    Article  PubMed  Google Scholar 

Download references

Acknowledgments

Dr. Khanna is supported by the Scleroderma Foundation (New Investigator Award), and a National Institutes of Health Building Interdisciplinary Research careers in Women’s Health (BIRCWH) Award (grant#HD051953). Drs. Furst, Wong, and Postlethwaite are partially supported by the Scleroderma Foundation (Established Investigator Award). Dr. Tsevat is supported in part by a National Center for Complementary and Alternative Medicine award (grant # K24 AT001676). Dr. Hays is supported in part by a grant from the National Institute of Aging (P01-AG-02-079), the UCLA/DREW Project EXPORT, National Institutes of Health, National Center on Minority Health & Health Disparities (P20-MD00148-01) and the UCLA Center for Health Improvement in Minority Elders/Resource Centers for Minority Aging Research, National Institute of Aging (AG-02-004). The Oral Type 1 Collagen in Scleroderma Study was sponsored by the National Institutes of Health (NIH)/National Institute of Arthritis and Musculoskeletal and Skin Diseases (grant #N01AR092242).

Author information

Authors and Affiliations

  1. Division of Immunology, Department of Internal Medicine, University of Cincinnati Medical Center, P.O. Box 670563, Cincinnati, OH, 45267-0563, USA

    Dinesh Khanna, Mansoor Ahmed & Shaari Ginsburg

  2. Institute for the Study of Health, University of Cincinnati, Cincinnati, OH, USA

    Dinesh Khanna & Joel Tsevat

  3. Veterans Affairs Medical Center, Cincinnati, OH, USA

    Dinesh Khanna, Joel Tsevat, Mansoor Ahmed & Shaari Ginsburg

  4. Division of Rheumatology, Department of Medicine, David Geffen School of Medicine, Los Angeles, CA, USA

    Daniel E. Furst, Philip J. Clements & Grace S. Park

  5. Department of Biostatistics, David Geffen School of Medicine, Los Angeles, CA, USA

    Weng Kee Wong & Grace S. Park

  6. Division of General Internal Medicine, Department of Internal Medicine, University of Cincinnati Medical Center, Cincinnati, OH, USA

    Joel Tsevat

  7. Division of Rheumatology, Department of Internal Medicine, University of Tennessee, Memphis, TN, USA

    Arnold E. Postlethwaite

  8. Division of General Internal Medicine and Health Services Research, David Geffen School of Medicine, Los Angeles, CA, USA

    Ron D. Hays

  9. RAND Corporation, Santa Monica, CA, USA

    Ron D. Hays

Authors
  1. Dinesh Khanna
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Daniel E. Furst
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Weng Kee Wong
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Joel Tsevat
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Philip J. Clements
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Grace S. Park
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Arnold E. Postlethwaite
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Mansoor Ahmed
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Shaari Ginsburg
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Ron D. Hays
    View author publications

    You can also search for this author in PubMed Google Scholar

Consortia

for the Scleroderma Collagen Type 1 Study Group

Corresponding author

Correspondence to Dinesh Khanna.

Additional information

On behalf of the Oral Type 1 Collagen in Scleroderma Study Group, the following investigators also participated:

University of Tennessee, Memphis: Andrew B. Kang, MD;

Boston University, Boston, Massachusetts: Robert Simms, MD; Joseph Korn, MD; Peter Merkel, MD, MPH;

Medical University of South Carolina, Charleston, South Carolina: Edwin Smith, MD;

Johns Hopkins School of Medicine, Baltimore, Maryland: Fred Wigley, MD; Barbara White, MD;

Georgetown University, Washington, DC: Virginia Steen, MD;

University of Texas Houston, Houston, Texas: Maureen Mayes, MD, MPH;

University of Alabama, Birmingham, Alabama: Larry Moreland, MD; Barri Fessler, MD;

Virginia Mason Research Center, Seattle, Washington: Jerry Molitor, MD, PhD;

University of Connecticut Health Center, Farmington, Connecticut: Naomi Rothfield, MD;

Hospital for Special Surgery, New York City, New York: Robert Spiera, MD.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Khanna, D., Furst, D.E., Wong, W.K. et al. Reliability, validity, and minimally important differences of the SF-6D in systemic sclerosis. Qual Life Res 16, 1083–1092 (2007). https://doi.org/10.1007/s11136-007-9207-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11136-007-9207-3

Keywords

Search

Navigation