Literature DB >> 19949029

Callosal lesion predicts future attacks after clinically isolated syndrome.

N Jafari1, K L Kreft, H Z Flach, A C J W Janssens, R Q Hintzen.   

Abstract

BACKGROUND: Current MRI criteria can help predict a second attack after a clinically isolated syndrome (CIS). Given the known association between corpus callosum lesions (CC) and multiple sclerosis (MS), such lesions on MRI could provide additional predictive information. This study assessed whether the presence of CC lesion on MRI could, next to the modified Barkhof criteria, further enhance prediction of conversion from CIS to MS.
METHODS: Follow-up study of 158 patients with CIS who underwent MRI after CIS was performed. MRI were scored for the Barkhof criteria and CC lesion. Patients were classified as having MS according to Poser criteria. Cox regression models were used for the time to conversion from CIS to MS.
RESULTS: The Barkhof criteria and CC lesion were strongly associated with conversion to MS with hazard ratios (HR), respectively, of 2.6 (95% confidence interval [CI] 1.5-4.3) and 2.7 (95% CI 1.6-4.5). The HRs of CC lesion adjusted for the Barkhof criteria and the Barkhof criteria adjusted for CC lesion were similar (HRs 1.8, not significant). The combined prediction of the Barkhof criteria and CC lesion was 3.3 (95% CI 1.9-5.7). Patients not fulfilling the Barkhof criteria had a fourfold increased risk of MS (HR 3.8, 95% CI 1.5-9.3) when they had a lesion in the CC.
CONCLUSIONS: Corpus callosum (CC) lesion and the Barkhof criteria both predicted conversion to multiple sclerosis (MS). When both variables were combined, the association was stronger. The assessment of CC lesion may be a useful additional tool for predicting conversion to MS in patients with clinically isolated syndrome.

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Year:  2009        PMID: 19949029     DOI: 10.1212/WNL.0b013e3181c3fccf

Source DB:  PubMed          Journal:  Neurology        ISSN: 0028-3878            Impact factor:   9.910


  4 in total

Review 1.  The prognostic utility of MRI in clinically isolated syndrome: a literature review.

Authors:  C Odenthal; A Coulthard
Journal:  AJNR Am J Neuroradiol       Date:  2014-05-15       Impact factor: 3.825

2.  Predicting outcome in clinically isolated syndrome using machine learning.

Authors:  V Wottschel; D C Alexander; P P Kwok; D T Chard; M L Stromillo; N De Stefano; A J Thompson; D H Miller; O Ciccarelli
Journal:  Neuroimage Clin       Date:  2014-12-04       Impact factor: 4.881

3.  Conversion of clinically isolated syndrome to multiple sclerosis: a prospective multi-center study in Eastern India.

Authors:  T K Banerjee; M Saha; E Ghosh; A Hazra; A Das; D Choudhury; S Ojha; A Haldar; A Mukherjee; S S Nandi; A Ghosh; A Mukherjee; A Chatterjee; A Datta; S Purakayastha
Journal:  Mult Scler J Exp Transl Clin       Date:  2019-05-13

4.  Lesion topographies in multiple sclerosis diagnosis: A reappraisal.

Authors:  Georgina Arrambide; Mar Tintore; Cristina Auger; Jordi Río; Joaquín Castilló; Angela Vidal-Jordana; Ingrid Galán; Carlos Nos; Manuel Comabella; Raquel Mitjana; Patricia Mulero; Andrea de Barros; Breogán Rodríguez-Acevedo; Luciana Midaglia; Jaume Sastre-Garriga; Alex Rovira; Xavier Montalban
Journal:  Neurology       Date:  2017-11-03       Impact factor: 9.910

  4 in total

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