Long-term disability trajectories in primary progressive MS patients: A latent class growth analysis
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11110%2F18%3A10375560" target="_blank" >RIV/00216208:11110/18:10375560 - isvavai.cz</a>
Alternative codes found
RIV/00064165:_____/18:10375560
Result on the web
<a href="https://doi.org/10.1177/1352458517703800" target="_blank" >https://doi.org/10.1177/1352458517703800</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1177/1352458517703800" target="_blank" >10.1177/1352458517703800</a>
Alternative languages
Result language
angličtina
Original language name
Long-term disability trajectories in primary progressive MS patients: A latent class growth analysis
Original language description
Background: Several natural history studies on primary progressive multiple sclerosis (PPMS) patients detected a consistent heterogeneity in the rate of disability accumulation. Objectives: To identify subgroups of PPMS patients with similar longitudinal trajectories of Expanded Disability Status Scale (EDSS) over time. Methods: All PPMS patients collected within the MSBase registry, who had their first EDSS assessment within 5 years from onset, were included in the analysis. Longitudinal EDSS scores were modeled by a latent class mixed model (LCMM), using a nonlinear function of time from onset. LCMM is an advanced statistical approach that models heterogeneity between patients by classifying them into unobserved groups showing similar characteristics. Results: A total of 853 PPMS (51.7% females) from 24 countries with a mean age at onset of 42.4 years (standard deviation (SD): 10.8 years), a median baseline EDSS of 4 (interquartile range (IQR): 2.5-5.5), and 2.4 years of disease duration (SD: 1.5 years) were included. LCMM detected three different subgroups of patients with a mild (n = 143; 16.8%), moderate (n = 378; 44.3%), or severe (n = 332; 38.9%) disability trajectory. The probability of reaching EDSS 6 at 10 years was 0%, 46.4%, and 81.9% respectively. Conclusion: Applying an LCMM modeling approach to long-term EDSS data, it is possible to identify groups of PPMS patients with different prognosis.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
30103 - Neurosciences (including psychophysiology)
Result continuities
Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2018
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Multiple Sclerosis Journal
ISSN
1352-4585
e-ISSN
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Volume of the periodical
24
Issue of the periodical within the volume
5
Country of publishing house
GB - UNITED KINGDOM
Number of pages
11
Pages from-to
642-652
UT code for WoS article
000432098100013
EID of the result in the Scopus database
2-s2.0-85032873925