The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
Using gadolinium‐enhanced magnetic resonance imaging lesions to monitor disease activity in multiple sclerosis
Abstract
The highly variable clinical course and the lack of a direct measurement of disease activity have made evaluation of experimental therapies in multiple sclerosis (MS) difficult. Recent studies indicate that clinically silent lesions can be demonstrated by magnetic resonance imaging (MRI) in patients with mild relapsing‐remitting MS. Thus, MRI may provide a means for monitoring therapeutic trials in the early phase of MS. We studied 12 patients longitudinally for 12 to 21 months with monthly gadolinium (Gd)‐enhanced MRIs. The data have been used to identify the most effective design of a clinical trial using Gd‐enhanced lesions as the outcome measure. Frequent (>1/mo) Gd‐enhancing lesions were observed in 9 of the 12 patients, indicating that the disease is active even during the early phase of the illness. The frequency of the lesions was not constant; there was marked fluctuation in lesion number from month to month. However, the magnitude of the peak number of lesions and the frequency of the peaks varied among patients. Because of this variability, the most effective use of Gd‐enhancing lesions as an outcome measure in a clinical trial was a crossover design with study arms of sufficient duration to allow accurate estimation of lesion frequency. Monitoring Gd‐enhancing lesions may be an effective tool to assist in the assessment of experimental therapies in early MS.
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McCullagh, P., & Nelder, J. A. (1989) · doi:10.1007/978-1-4899-3242-6 · Cited by 16,836
Rating neurologic impairment in multiple sclerosis: An expanded disability status scale (EDSS)
Kurtzke, J. F. (1983) · Neurology · doi:10.1212/wnl.33.11.1444 · Cited by 15,011
The Jackknife, the Bootstrap and Other Resampling Plans
Efron, B. (1982) · Society for Industrial and Applied Mathematics eBooks · doi:10.1137/1.9781611970319 · Cited by 8,120
Statistical data analysis in the computer age
Efron, B., & Tibshirani, R. (1991) · Science · doi:10.1126/science.253.5018.390 · Cited by 1,192
Cited by
Axonal transection in the lesions of multiple sclerosis
Trapp, B. D., Peterson, J., Ransohoff, R. M., Rudick, R., Mörk, S., & Bö, L. (1998) · New England Journal of Medicine · doi:10.1056/nejm199801293380502 · Cited by 4,029
Truyen, L., van Waesberghe, J. H. T. M., van Walderveen, M. A. A., van Oosten, B. W., Polman, C. H., Hommes, O. R., Ader, H. J. A., & Barkhof, F. (1996) · Neurology · doi:10.1212/wnl.47.6.1469 · Cited by 462
Miller, D. H., Albert, P. S., Barkhof, F., Francis, G., Frank, J. A., Hodgkinson, S., Lublin, F. D., Paty, D. W., Reingold, S. C., & Simon, J. (1996) · Annals of Neurology · doi:10.1002/ana.410390104 · Cited by 444
Self-citationTreatment of multiple sclerosis with the pregnancy hormone estriol
Sicotte, N. L., Liva, S. M., Klutch, R., Pfeiffer, P., Bouvier, S., Odesa, S., Wu, T. C. J., & Voskuhl, R. R. (2002) · Annals of Neurology · doi:10.1002/ana.10301 · Cited by 435
Edan, G., Miller, D., Clanet, M., Confavreux, C., Lyon-Caen, O., Lubetzki, C., Brochet, B., Berry, I., Rolland, Y., Froment, J. C., et al. (1997) · Journal of Neurology, Neurosurgery & Psychiatry · doi:10.1136/jnnp.62.2.112 · Cited by 425
Metadata
- Authors
- McFarland, H. F., Frank, J. A., Albert, P. S., Smith, M. E., Martin, R., Harris, J. O., Patronas, N., Maloni, H., & McFarlin, D. E.
- Venue
- Annals of Neurology
- Publisher
- Wiley
- Published
- 1992-12
- Volume
- 32
- Issue
- 6
- Pages
- 758-766
- ISSN
- 0364-5134 (ISSN-L)
- 1531-8249
- OpenAlex
- W2048159994
- Cited by
- 346
- References
- 4
- FWCI
- 8.54
- Type
- journal article
- Language
- en
- Open access
- closed
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- McFarland, H. F., Frank, J. A., Albert, P. S., Smith, M. E., Martin, R., Harris, J. O., Patronas, N., Maloni, H., & McFarlin, D. E. (1992). Using gadolinium‐enhanced magnetic resonance imaging lesions to monitor disease activity in multiple sclerosis. Annals of Neurology. https://doi.org/10.1002/ana.410320609
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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