{
  "abstract": "Background A growing arsenal of treatment options for relapsing multiple sclerosis (RMS) emphasises the need for early prognostic biomarkers. While evidence for individual markers exists, comprehensive analyses at the time of diagnosis are sparse.Methods Brain and spinal cord lesion numbers, cerebrospinal fluid parameters, initial symptoms, and Expanded Disability Status Scale (EDSS) score were determined at the time of diagnosis. Confirmed disability accumulation (CDA), defined as a sustained EDSS increase over 6 months, was determined during a 5-year follow-up. All-subsets multivariable logistic regression was performed to identify predictors of CDA. Model performance was assessed via receiver operating characteristic analysis, and individual risks were calculated. Analyses were repeated with progression independent of relapse activity (PIRA) as an outcome.Results 113/417 (27.1%) people with RMS experienced CDA on follow-up. Intrathecal IgG synthesis, a higher number of spinal cord lesions, age and polysymptomatic manifestation were identified as independent predictors of CDA. The resulting prediction model yielded an area under the curve (AUC) of 0.75 with a 95% CI of 0.70 to 0.80. Individuals exceeding the optimal thresholds for the three most significant predictors had a 61.8% likelihood of experiencing CDA, whereas those below all three thresholds had a CDA rate of 4.5%. The only significant baseline predictor differentiating PIRA from relapse-associated worsening was a higher number of spinal cord lesions (AUC=0.64, 95% CI 0.54 to 0.74).Conclusions Intrathecal IgG synthesis, spinal cord lesion number, age and polysymptomatic manifestation are independent predictors of early CDA in newly diagnosed RMS.",
  "authors": [
    {
      "affiliations": [
        "Department of Neurology, School of Medicine and Health, Technical University of Munich, Munich, Germany",
        "TUM-Neuroimaging Center, School of Medicine and Health, Technical University of Munich, Munich, Germany"
      ],
      "name": "Markus Lauerer"
    },
    {
      "affiliations": [
        "Department of Neurology, School of Medicine and Health, Technical University of Munich, Munich, Germany",
        "TUM-Neuroimaging Center, School of Medicine and Health, Technical University of Munich, Munich, Germany"
      ],
      "name": "Tun Wiltgen"
    },
    {
      "affiliations": [
        "Department of Neurology, School of Medicine and Health, Technical University of Munich, Munich, Germany"
      ],
      "name": "Carolin Brückner"
    },
    {
      "affiliations": [
        "Department of Neurology, School of Medicine and Health, Technical University of Munich, Munich, Germany"
      ],
      "name": "Christina Engl"
    },
    {
      "affiliations": [
        "Department of Neurology, School of Medicine and Health, Technical University of Munich, Munich, Germany"
      ],
      "name": "Katrin Giglhuber"
    },
    {
      "affiliations": [
        "Department of Neurology, School of Medicine and Health, Technical University of Munich, Munich, Germany"
      ],
      "name": "Sebastian Lambrecht"
    },
    {
      "affiliations": [
        "Department of Neurology, School of Medicine and Health, Technical University of Munich, Munich, Germany",
        "TUM-Neuroimaging Center, School of Medicine and Health, Technical University of Munich, Munich, Germany"
      ],
      "name": "Viola Pongratz"
    },
    {
      "affiliations": [
        "Department of Neurology, School of Medicine and Health, Technical University of Munich, Munich, Germany"
      ],
      "name": "Achim Berthele"
    },
    {
      "affiliations": [
        "Department of Neurology, School of Medicine and Health, Technical University of Munich, Munich, Germany"
      ],
      "name": "Christiane Gasperi"
    },
    {
      "affiliations": [
        "Department of Neuroradiology, School of Medicine and Health, Technical University of Munich, Munich, Germany"
      ],
      "name": "Jan S Kirschke"
    },
    {
      "affiliations": [
        "Department of Neuroradiology, School of Medicine and Health, Technical University of Munich, Munich, Germany"
      ],
      "name": "Claus Zimmer"
    },
    {
      "affiliations": [
        "Department of Neurology, School of Medicine and Health, Technical University of Munich, Munich, Germany",
        "Munich Cluster for Systems Neurology (SyNergy), Munich, Germany"
      ],
      "name": "Bernhard Hemmer"
    },
    {
      "affiliations": [
        "Department of Neurology, School of Medicine and Health, Technical University of Munich, Munich, Germany",
        "TUM-Neuroimaging Center, School of Medicine and Health, Technical University of Munich, Munich, Germany"
      ],
      "name": "Mark Mühlau"
    }
  ],
  "title": "Predictors of early disability accumulation in newly diagnosed multiple sclerosis: clinical, imaging and cerebrospinal fluid measures",
  "uid": "036f4363-14a1-5c6a-9b6b-7fefd37c1029"
}