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The Multiple Sclerosis Performance Test (MSPT): An iPad-Based Disability Assessment Tool
Published on: June 30, 2014
Integrating the tools for an individualized prognosis in multiple sclerosis
1Institute of Clinical Neurosciences, Hospital Regional Universitario Carlos Haya, Avenida Carlos Haya s/n, 29010, Málaga, Spain. oscar.fernandez.sspa@juntadeandalucia.es
Journal of the Neurological Sciences
|May 23, 2013
Summary
Predicting multiple sclerosis (MS) prognosis requires biomarkers. Clinical and imaging markers, alongside biological and functional measures, aid in forecasting disease progression and treatment response for personalized patient care.
Area of Science:
- Neurology
- Biomarker Research
- Medical Prognostics
Background:
- Multiple sclerosis (MS) patient management necessitates reliable prognostic biomarkers.
- Current clinical and imaging data offer insights into disease progression.
- Pharmacogenetics/genomics shows promise for future MS prognostication.
Purpose of the Study:
- To review current clinical, imaging, biological, and functional markers for predicting MS prognosis.
- To highlight the need for objective biomarkers for individualized patient management.
- To discuss the potential of emerging technologies in MS prognosis.
Main Methods:
- Review of clinical epidemiological studies on MS prognostic markers.
- Analysis of biological markers in cerebrospinal fluid (CSF) and blood.
- Evaluation of magnetic resonance imaging (MRI) findings and functional measures (OCT, evoked potentials).
Main Results:
- Clinical markers of good prognosis include female sex, young age of onset, and specific initial symptoms.
- Potential biological markers include IgM, neurofilaments, antimyelin, and chitinase 3-like 1.
- MRI measures like lesion load, atrophy, and black holes correlate with worse MS outcomes.
Conclusions:
- A combination of clinical, imaging, biological, and functional markers can aid in predicting MS prognosis.
- Objective biomarkers are crucial for tailoring treatment strategies and managing patient expectations.
- Further research into mathematical models and advanced imaging techniques is warranted for improved risk stratification.
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