MS-CANE: a computer-aided instrument for neurological evaluation of patients with multiple sclerosis: enhanced reliability of expanded disability status scale (EDSS) assessment

Abstract

Kurtzke's EDSS remains the most widely-used measure for clinical evaluation of MS patients. However, several studies have demonstrated the limited reliability of this tool. We introduce a computerized instrument, MS-CANE (Multiple Sclerosis Computer-Aided Neurological Examination), for clinical evaluation and follow up of patients with multiple sclerosis (MS) and to compare its reliability to that of conventional Expanded Disability Status Scale (EDSS) assessment. We developed a computerized interactive instrument, based on the following principles: structured gathering of neurological findings, reduction of compound notions to their basic components, use of precise definitions, priority setting and automated calculations of EDSS and functional systems scores. An expert panel examined the consistency of MS-CANE with Kurtzke's specifications. To determine the effect of MS-CANE on the reliability of EDSS assessment, 56 MS patients underwent paired conventional EDSS and MS-CANE-based evaluations. The inter-observer agreement in both methods was determined and compared using the kappa statistic. The expert panel judged the tool to be compatible with the basic concepts of Kurtzke's EDSS. The use of MS-CANE increased the reliability of EDSS assessment: Kappa statistic was found to be 0.42 (i.e. moderate agreement) for conventional EDSS assessment versus 0.69 (i.e. substantial agreement) for MS-CANE (P=0.002). We conclude that the use of this tool may contribute towards a standardized and reliable assessment of EDSS. Within clinical trials, this could increase the power to detect effects, thus reducing trial duration and the cohort size required.

Keywords

EDSS FSS multiple sclerosis reliability

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References

Amato MP et al. (1988) Interrater reliability in assessing functional systems and disability on the Kurtzke scale in multiple sclerosis . Arch Neurol 45: 746-748 .

Efron B. (1981) Non-parametric standard errors and confidence intervals . Canadian Journal of Statistics 9: 139-172 .

Fleiss JL. (1971) Measuring nominal scale agreement among many raters . Psychol Bull 76: 378-382 .

Francis DA , Bain P , Swan AV , Hughes AC. (1991) An assessment of disability rating scales used in multiple sclerosis . Arch Neurol 48: 229-301 .

Goodkin DE et al. (1992) Inter- and Intrarater scoring agreement using grades 1.0 to 3.5 of Kurtzke Expanded Disability Status Scale (EDSS) . Neurology 42: 859-863 .

Koran LM. (1975) The reliability of clinical methods, data and judgments . N Engl J Med 293: 642-646, 695-701 .

Kurtzke JF. (1983) Rating neurologic impairment in multiple sclerosis: An expanded disability status scale (EDSS) . Neurology 33: 1444-1452 .

Noseworthy JH , Vandervoort MK , Wong CJ , Ebers GC. (1990) Interrater variability with the Expanded Disability Status Scale (EDSS) and Functional Systems (FS) in a multiple sclerosis clinical trial . Neurology 40: 971-975 .

Watson CJ , Collin J. (1998) Estimates of distance by claudicants and vascular surgeons are inherently unreliable . Eur J Vasc Endovasc Surg 16: 429-430 .

10.

Paty D , Studney D , Redekop K , Lublin F. (1994) MS COSTAR: a computerized patient record adapted for clinical research purposes . Ann Neurol 36 (Suppl) S134-S135 .

11.

Rudick R et al. (1996) Clinical outcome assessment in multiple sclerosis . Ann Neurol 40: 469-479 .

12.

Rudick R et al. (1997) Recommendations from the clinical multiple sclerosis society clinical outcomes assessment task force . Ann Neurol 42: 379-382 .