-
Something wrong with this record ?
Combining clinical and magnetic resonance imaging markers enhances prediction of 12-year disability in multiple sclerosis
T. Uher, M. Vaneckova, L. Sobisek, M. Tyblova, Z. Seidl, J. Krasensky, D. Ramasamy, R. Zivadinov, E. Havrdova, T. Kalincik, D. Horakova,
Language English Country Great Britain
Document type Journal Article
Grant support
NT12385
MZ0
CEP Register
NT13237
MZ0
CEP Register
- MeSH
- Atrophy MeSH
- Biomarkers analysis MeSH
- Adult MeSH
- Interferon beta-1a therapeutic use MeSH
- Middle Aged MeSH
- Humans MeSH
- Magnetic Resonance Imaging * methods MeSH
- Brain diagnostic imaging MeSH
- Follow-Up Studies MeSH
- Disability Evaluation MeSH
- Predictive Value of Tests MeSH
- Disease Progression MeSH
- Multiple Sclerosis diagnostic imaging drug therapy pathology MeSH
- Check Tag
- Adult MeSH
- Middle Aged MeSH
- Humans MeSH
- Male MeSH
- Female MeSH
- Publication type
- Journal Article MeSH
BACKGROUND: Disease progression and treatment efficacy vary among individuals with multiple sclerosis. Reliable predictors of individual disease outcomes are lacking. OBJECTIVE: To examine the accuracy of the early prediction of 12-year disability outcomes using clinical and magnetic resonance imaging (MRI) parameters. METHODS: A total of 177 patients from the original Avonex-Steroids-Azathioprine study were included. Participants underwent 3-month clinical follow-ups. Cox models were used to model the associations between clinical and MRI markers at baseline or after 12 months with sustained disability progression (SDP) over the 12-year observation period. RESULTS: At baseline, T2 lesion number, T1 and T2 lesion volumes, corpus callosum (CC), and thalamic fraction were the best predictors of SDP (hazard ratio (HR) = 1.7-4.6; p ⩽ 0.001-0.012). At 12 months, Expanded Disability Status Scale (EDSS) and its change, number of new or enlarging T2 lesions, and CC volume % change were the best predictors of SDP over the follow-up (HR = 1.7-3.5; p ⩽ 0.001-0.017). A composite score was generated from a subset of the best predictors of SDP. Scores of ⩾4 had greater specificity (90%-100%) and were associated with greater cumulative risk of SDP (HR = 3.2-21.6; p < 0.001) compared to the individual predictors. CONCLUSION: The combination of established MRI and clinical indices with MRI volumetric predictors improves the prediction of SDP over long-term follow-up and may provide valuable information for therapeutic decisions.
References provided by Crossref.org
- 000
- 00000naa a2200000 a 4500
- 001
- bmc18011268
- 003
- CZ-PrNML
- 005
- 20181024090323.0
- 007
- ta
- 008
- 180404s2017 xxk f 000 0|eng||
- 009
- AR
- 024 7_
- $a 10.1177/1352458516642314 $2 doi
- 035 __
- $a (PubMed)27053635
- 040 __
- $a ABA008 $b cze $d ABA008 $e AACR2
- 041 0_
- $a eng
- 044 __
- $a xxk
- 100 1_
- $a Uher, Tomáš $u Department of Neurology and Center of Clinical Neuroscience, First Faculty of Medicine and General University Hospital, Charles University, Prague, Czech Republic. $7 xx0189534
- 245 10
- $a Combining clinical and magnetic resonance imaging markers enhances prediction of 12-year disability in multiple sclerosis / $c T. Uher, M. Vaneckova, L. Sobisek, M. Tyblova, Z. Seidl, J. Krasensky, D. Ramasamy, R. Zivadinov, E. Havrdova, T. Kalincik, D. Horakova,
- 520 9_
- $a BACKGROUND: Disease progression and treatment efficacy vary among individuals with multiple sclerosis. Reliable predictors of individual disease outcomes are lacking. OBJECTIVE: To examine the accuracy of the early prediction of 12-year disability outcomes using clinical and magnetic resonance imaging (MRI) parameters. METHODS: A total of 177 patients from the original Avonex-Steroids-Azathioprine study were included. Participants underwent 3-month clinical follow-ups. Cox models were used to model the associations between clinical and MRI markers at baseline or after 12 months with sustained disability progression (SDP) over the 12-year observation period. RESULTS: At baseline, T2 lesion number, T1 and T2 lesion volumes, corpus callosum (CC), and thalamic fraction were the best predictors of SDP (hazard ratio (HR) = 1.7-4.6; p ⩽ 0.001-0.012). At 12 months, Expanded Disability Status Scale (EDSS) and its change, number of new or enlarging T2 lesions, and CC volume % change were the best predictors of SDP over the follow-up (HR = 1.7-3.5; p ⩽ 0.001-0.017). A composite score was generated from a subset of the best predictors of SDP. Scores of ⩾4 had greater specificity (90%-100%) and were associated with greater cumulative risk of SDP (HR = 3.2-21.6; p < 0.001) compared to the individual predictors. CONCLUSION: The combination of established MRI and clinical indices with MRI volumetric predictors improves the prediction of SDP over long-term follow-up and may provide valuable information for therapeutic decisions.
- 650 _2
- $a dospělí $7 D000328
- 650 _2
- $a atrofie $7 D001284
- 650 _2
- $a biologické markery $x analýza $7 D015415
- 650 _2
- $a mozek $x diagnostické zobrazování $7 D001921
- 650 _2
- $a posuzování pracovní neschopnosti $7 D004185
- 650 _2
- $a progrese nemoci $7 D018450
- 650 _2
- $a ženské pohlaví $7 D005260
- 650 _2
- $a následné studie $7 D005500
- 650 _2
- $a lidé $7 D006801
- 650 _2
- $a interferon beta 1a $x terapeutické užití $7 D000068556
- 650 12
- $a magnetická rezonanční tomografie $x metody $7 D008279
- 650 _2
- $a mužské pohlaví $7 D008297
- 650 _2
- $a lidé středního věku $7 D008875
- 650 _2
- $a roztroušená skleróza $x diagnostické zobrazování $x farmakoterapie $x patologie $7 D009103
- 650 _2
- $a prediktivní hodnota testů $7 D011237
- 655 _2
- $a časopisecké články $7 D016428
- 700 1_
- $a Vaněčková, Manuela, $u Department of Radiology, First Faculty of Medicine and General University Hospital, Charles University, Prague, Czech Republic. $d 1973- $7 mzk2007377403
- 700 1_
- $a Sobisek, Lukas $u Department of Statistics and Probability, University of Economics, Prague, Czech Republic.
- 700 1_
- $a Týblová, Michaela $u Department of Neurology and Center of Clinical Neuroscience, First Faculty of Medicine and General University Hospital, Charles University, Prague, Czech Republic. $7 xx0121850
- 700 1_
- $a Seidl, Zdeněk, $u Department of Radiology, First Faculty of Medicine and General University Hospital, Charles University, Prague, Czech Republic. $d 1950- $7 mzk2004258727
- 700 1_
- $a Krásenský, Jan $u Department of Radiology, First Faculty of Medicine and General University Hospital, Charles University, Prague, Czech Republic. $7 xx0096156
- 700 1_
- $a Ramasamy, Deepa $u Buffalo Neuroimaging Analysis Center, Department of Neurology, School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NY, USA.
- 700 1_
- $a Zivadinov, Robert $u Buffalo Neuroimaging Analysis Center, Department of Neurology, School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NY, USA/MR Imaging Clinical Translational Research Center, School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NY, USA.
- 700 1_
- $a Kubala Havrdová, Eva, $u Department of Neurology and Center of Clinical Neuroscience, First Faculty of Medicine and General University Hospital, Charles University, Prague, Czech Republic. $d 1955- $7 nlk19990073204
- 700 1_
- $a Kalincik, Tomas $u Department of Medicine, University of Melbourne, Melbourne, VIC, Australia/Department of Neurology, Royal Melbourne Hospital, Melbourne, VIC, Australia.
- 700 1_
- $a Horáková, Dana $u Department of Neurology and Center of Clinical Neuroscience, First Faculty of Medicine and General University Hospital, Charles University, Prague, Czech Republic. $7 xx0076527
- 773 0_
- $w MED00006389 $t Multiple sclerosis (Houndmills, Basingstoke, England) $x 1477-0970 $g Roč. 23, č. 1 (2017), s. 51-61
- 856 41
- $u https://pubmed.ncbi.nlm.nih.gov/27053635 $y Pubmed
- 910 __
- $a ABA008 $b sig $c sign $y a $z 0
- 990 __
- $a 20180404 $b ABA008
- 991 __
- $a 20181024090831 $b ABA008
- 999 __
- $a ok $b bmc $g 1288753 $s 1008080
- BAS __
- $a 3
- BAS __
- $a PreBMC
- BMC __
- $a 2017 $b 23 $c 1 $d 51-61 $e 20160711 $i 1477-0970 $m Multiple sclerosis $n Mult Scler $x MED00006389
- GRA __
- $a NT12385 $p MZ0
- GRA __
- $a NT13237 $p MZ0
- LZP __
- $a Pubmed-20180404