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Criteria to Determine Disability Related to Multiple Sclerosis

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Summary (continued)


Future Research

Future research about work ability among individuals with MS can shed a great deal of light on factors that foster or hinder employment. Our full report,49 particularly the evidence reported on association of clinical findings and work ability, highlights significant evidence and information gaps concerning:

  • Patterns of MS patient reports regarding functional limitations.
  • Information commonly collected in medical encounters with MS patients (and therefore available to SSA).
  • Knowledge about the impact on performance of specific work tasks of commonly objectified parameters such as coordination, strength, and vision, and especially of factors such as fatigue or cognitive dysfunction, which are either difficult to measure or are less commonly assessed in detail.
  • Effective research methods for categorizing job or task demands in such a way as to isolate those demands that are likely to be "critical" for an SSDI applicant with MS.

In the context of these gaps, it may be productive to pursue research approaches that simultaneously address four domains:

  1. Subjective reports (this domain is not sufficient alone for SSDI determination purposes).
  2. Objective clinical data (ideally of the sort commonly encountered in medical records).
  3. In-depth objective measures (which may be available and not widely applied clinically, but which may be used with subsets of subjects to explore correlation with other domains).
  4. Work status measures (ideally longitudinal, with stratifications based on work demands).

Such an approach may apply to thermal sensitivity as well, with some additional specification and focus. Parallel assessment of concomitant ambient temperature, physical exertion, and core body temperature would address key relevant physiological exposure factors.

Outcome measures could include the domains outlined above, for example:

  • Self-perceived well-being and level of symptoms such as fatigue.
  • Clinical parameters such as walking speed or muscle strength.
  • In-depth measures such as potentially associated biomarkers or physiological parameters.
  • Work status measures, including absenteeism and disability benefits use.

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Availability of the Full Report

The full evidence report from which this summary was taken was prepared for the Agency for Healthcare Research and Quality (AHRQ) by the dukeepc.htm">Duke Evidence-based Practice Center, under Contract No. 290-02-0025. Printed copies may be obtained free of charge from the AHRQ Publications Clearinghouse by calling 800-358-9295. Requesters should ask for Evidence Report/Technology Assessment No. 100, Criteria to Determine Disability Related to Multiple Sclerosis.

The Evidence Report can also be downloaded as PDF File (5.4 MB). Plugin Software Help.

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References

1. Salan SZ. Understanding Social Security Disability Programs. Presentation at Multidisciplinary Experts Meeting for the study of Criteria to Determine Disability Related to Multiple Sclerosis, sponsored by the Agency for Healthcare Research & Quality Center for Outcomes and Evidence, Baltimore, MD, March 2003.

2. Social Security Administration. Disability Evaluation under Social Security January 2003. Baltimore, MD: Social Security Administration Office of Disability, 2003; SSA Pub. No. 64-039.

3. World Health Organization. International Classification of Impairments, Disabilities, and Handicaps: A Manual of Classification Relating to the Consequences of Disease. World Health Organization: Geneva, 1980.

4. Poser CM, Paty DW, Scheinberg L, et al. New diagnostic criteria for multiple sclerosis: guidelines for research protocols. Ann Neurol 1983;13(3):227-31.

5. McDonald WI, Compston A, Edan G, et al. Recommended diagnostic criteria for multiple sclerosis: guidelines from the International Panel on the Diagnosis of Multiple Sclerosis. Ann Neurol 2001;50(1):121-7.

6. Dalton CM, Brex PA, Miszkiel KA, et al. Application of the new McDonald criteria to patients with clinically isolated syndromes suggestive of multiple sclerosis. Ann Neurol 2002;52(1):47-53.

7. Tintoré M, Rovira A, Río J, et al. New diagnostic criteria for multiple sclerosis—application in first demyelinating episode. Neurology 2003;60(1):27-30.

8. Barkhof F, Filippi M, Miller DH, et al. Comparison of MRI criteria at first presentation to predict conversion to clinically definite multiple sclerosis. Brain 1997;120 (Pt 11):2059-69.

9. Filippi M, Horsfield MA, Morrissey SP, et al. Quantitative brain MRI lesion load predicts the course of clinically isolated syndromes suggestive of multiple sclerosis. Neurology 1994;44(4):635-41.

10. O'Riordan JI, Thompson AJ, Kingsley DP, et al. The prognostic value of brain MRI in clinically isolated syndromes of the CNS. A 10-year follow-up. Brain 1998;121 (Pt 3):495-503.

11. Sastre-Garriga J, Tintoré M, Rovira A, et al. Conversion to multiple sclerosis after a clinically isolated syndrome of the brainstem: cranial magnetic resonance imaging, cerebrospinal fluid and neurophysiological findings. Mult Scler 2003;9(1):39-43.

12. Brex PA, Miszkiel KA, O'Riordan JI, et al. Assessing the risk of early multiple sclerosis in patients with clinically isolated syndromes: the role of a follow up MRI. J Neurol Neurosurg Psych 2001;70(3):390-3.

13. CHAMPS Study Group. MRI predictors of early conversion to clinically definite MS in the CHAMPS placebo group. Neurology 2002;59(7):998-1005.

14. Morrissey SP, Miller DH, Kendall BE, et al. The significance of brain magnetic resonance imaging abnormalities at presentation with clinically isolated syndromes suggestive of multiple sclerosis. A 5-year follow-up study. Brain 1993;116 (Pt 1):135-46.

15. Optic Neuritis Study Group. The 5-year risk of MS after optic neuritis: experience of the optic neuritis treatment trial. 1997. Neurology 2001;57(12 Suppl 5):S36-45.

16. Comi G, Filippi M, Barkhof F, et al. Effect of early interferon treatment on conversion to definite multiple sclerosis: a randomised study. Lancet 2001;357(9268):1576-82.

17. Ford HL, Johnson MH, Rigby AS. Variation between observers in classifying multiple sclerosis. J Neurol Neurosurg Psych 1996;61(4):418.

18. Zipoli V, Portaccio E, Siracusa G, et al. Interobserver agreement on Poser's and the new McDonald's diagnostic criteria for multiple sclerosis. Mult Scler 2003;9:481-5.

19. Goodkin DE, Hertsgaard D, Rudick RA. Exacerbation rates and adherence to disease type in a prospectively followed-up population with multiple sclerosis. Implications for clinical trials. Arch Neurol 1989;46(10):1107-12.

20. Cottrell DA, Kremenchutzky M, Rice GP, et al. The natural history of multiple sclerosis: a geographically based study. 6. Applications to planning and interpretation of clinical therapeutic trials in primary progressive multiple sclerosis. Brain 1999a;122 (Pt 4):641-7.

21. Cottrell DA, Kremenchutzky M, Rice GP, et al. The natural history of multiple sclerosis: a geographically based study. 5. The clinical features and natural history of primary progressive multiple sclerosis. Brain 1999b;122 (Pt 4):625-39.

22. Runmarker B, Andersson C, Odén A, et al. Prediction of outcome in multiple sclerosis based on multivariate models. J Neurol 1994;241(10):597-604.

23. Koziol JA, Wagner S, Sobel DF, et al. Predictive value of lesions for relapses in relapsing-remitting multiple sclerosis. Am J Neuroradiol 2001;22(2):284-91.

24. Rovaris M, Comi G, Ladkani D, et al. Short-term correlations between clinical and MR imaging findings in relapsing-remitting multiple sclerosis. Am J Neuroradiol 2003;24(1):75-81.

25. Stevenson VL, Leary SM, Losseff NA, et al. Spinal cord atrophy and disability in MS: a longitudinal study. Neurology 1998;51(1):234-8.

26. Chapman J, Sylantiev C, Nisipeanu P, et al. Preliminary observations on APOE epsilon4 allele and progression of disability in multiple sclerosis. Arch Neurol 1999;56(12):1484-7.

27. Trotter JL, Clifford DB, McInnis JE, et al. Correlation of immunological studies and disease progression in chronic progressive multiple sclerosis. Ann Neurol 1989;25(2):172-8.

28. Villar LM, Masjuan J, González-Porqué P, et al. Intrathecal IgM synthesis predicts the onset of new relapses and a worse disease course in MS. Neurology 2002;59(4):555-9.

29. Fuhr P, Borggrefe-Chappuis A, Schindler C, et al. Visual and motor evoked potentials in the course of multiple sclerosis. Brain 2001;124(Pt 11):2162-8.

30. Nortvedt MW, Riise T, Myhr KM, et al. Quality of life as a predictor for change in disability in MS. Neurology 2000;55(1):51-4.

31. Canadian MS Research Group. A randomized controlled trial of amantadine in fatigue associated with multiple sclerosis. Can J Neurol Sci 1987;14(3):273-8.

32. Cohen RA, Fisher M. Amantadine treatment of fatigue associated with multiple sclerosis. Arch Neurol 1989;46(6):676-80.

33. Krupp LB, Coyle PK, Doscher C, et al. Fatigue therapy in multiple sclerosis: results of a double-blind, randomized, parallel trial of amantadine, pemoline, and placebo. Neurology 1995;45(11):1956-61.

34. Geisler MW, Sliwinski M, Coyle PK, et al. The effects of amantadine and pemoline on cognitive functioning in multiple sclerosis. Arch Neurol 1996;53(2):185-8.

35. Weinshenker BG, Penman M, Bass B, et al. A double-blind, randomized, crossover trial of pemoline in fatigue associated with multiple sclerosis. Neurology 1992;42(8):1468-71.

36. Rossini PM, Pasqualetti P, Pozzilli C, et al. Fatigue in progressive multiple sclerosis: results of a randomized, double-blind, placebo-controlled, crossover trial of oral 4-aminopyridine. Mult Scler 2001;7(6):354-8.

37. Rammohan KW, Rosenberg JH, Lynn DJ, et al. Efficacy and safety of modafinil (Provigil) for the treatment of fatigue in multiple sclerosis: a two centre phase 2 study. J Neurol Neurosurg Psych 2002;72(2):179-83.

38. Fredrikson S. Nasal spray desmopressin treatment of bladder dysfunction in patients with multiple sclerosis. Acta Neurol Scand 1996;94(1):31-4.

39. Hilton P, Hertogs K, Stanton SL. The use of desmopressin (DDAVP) for nocturia in women with multiple sclerosis. J Neurol Neurosurg Psych 1983;46(9):854-5.

40. Hoverd PA, Fowler CJ. Desmopressin in the treatment of daytime urinary frequency in patients with multiple sclerosis. J Neurol Neurosurg Psych 1998;65(5):778-80.

41. Kinn AC, Larsson PO. Desmopressin: a new principle for symptomatic treatment of urgency and incontinence in patients with multiple sclerosis. Scand J Urol Nephrol 1990;24(2):109-12.

42. Valiquette G, Herbert J, Maede-D'Alisera P. Desmopressin in the management of nocturia in patients with multiple sclerosis. A double-blind, crossover trial. Arch Neurol 1996;53(12):1270-5.

43. Vahtera T, Haaranen M, Viramo-Koskela AL, et al. Pelvic floor rehabilitation is effective in patients with multiple sclerosis. Clin Rehab 1997;11(3):211-9.

44. Prasad RS, Smith SJ, Wright H. Lower abdominal pressure versus external bladder stimulation to aid bladder emptying in multiple sclerosis: a randomized controlled study. Clin Rehab 2003;17(1):42-7.

45. Hammond SR, McLeod JG, Macaskill P, et al. Multiple sclerosis in Australia: socioeconomic factors. J Neurol Neurosurg Psych 1996;61(3):311-3.

46. LaRocca N, Kalb R, Kendall P, et al. The role of disease and demographic factors in the employment of patients with multiple sclerosis. Arch Neurol 1982;39(4):256.

47. Rao SM, Leo GJ, Ellington L, et al. Cognitive dysfunction in multiple sclerosis. II. Impact on employment and social functioning. Neurology 1991;41(5):692-6.

48. Gulick EE, Yam M, Touw MM. Work performance by persons with multiple sclerosis: conditions that impede or enable the performance of work. Internat J Nurs Stud 1989;26(4):301-11.

49. McCrory DC, Pompeii LA, Skeen MB, et al. Criteria to Determine Disability Related to Multiple Sclerosis, Evidence Report/Technology Assessment No. 100. Duke Evidence-based Practice Center, Contract #290-02-0025. AHRQ Publication No. 04-E019-2, May 2004.

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AHRQ Publication No. 04-E019-1
Current as of May 2004

 

The information on this page is archived and provided for reference purposes only.

 

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