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Defining brain volume cutoffs to identify clinically relevant atrophy in RRMS.
Sormani, Maria Pia; Kappos, Ludwig; Radue, Ernst-Wilhelm; Cohen, Jeffrey; Barkhof, Frederik; Sprenger, Till; Piani Meier, Daniela; Häring, Dieter; Tomic, Davorka; De Stefano, Nicola.
Afiliação
  • Sormani MP; Biostatistics Unit, Department of Health Sciences (DISSAL), University of Genoa, Genoa, Italy.
  • Kappos L; Neurological Clinic and Polyclinic, Departments of Medicine, Clinical Research, Biomedicine and Biomedical Engineering, University Hospital Basel, Basel, Switzerland.
  • Radue EW; Medical Image Analysis Center (MIAC), University Hospital Basel, Basel, Switzerland.
  • Cohen J; Neurological Institute, The Cleveland Clinic Foundation, Cleveland, OH, USA.
  • Barkhof F; Department of Radiology, VU University Medical Center, Amsterdam, Netherlands.
  • Sprenger T; Department of Neurology, DKD Helios Klinik Wiesbaden, Wiesbaden, Germany.
  • Piani Meier D; Novartis Pharma AG, Basel, Switzerland.
  • Häring D; Novartis Pharma AG, Basel, Switzerland.
  • Tomic D; Novartis Pharma AG, Basel, Switzerland.
  • De Stefano N; University of Siena, Siena, Italy.
Mult Scler ; 23(5): 656-664, 2017 Apr.
Article em En | MEDLINE | ID: mdl-27411701
ABSTRACT

OBJECTIVE:

To define values of normalized brain volume (NBV) that can be categorized as low, medium, or high, according to baseline characteristics of relapsing-remitting multiple sclerosis (RRMS) patients.

METHODS:

Expected NBV (eNBV) was calculated for each patient based on age, disease duration, sex, baseline Expanded Disability Status Scale (EDSS), and T2-lesion volume, entering these variables into a multiple regression model run on 2342 RRMS patients (pooled FREEDOMS/FREEDOMS-II population). According to the difference between their observed NBV and their eNBV, patients were classified as having low NBV, medium NBV, or high NBV. We evaluated whether these NBV categories were clinically meaningful by assessing correlation with disability worsening.

RESULTS:

The distribution of differences between observed NBV and eNBV was used to categorize patients as having low NBV, medium NBV or high NBV. Taking the high-NBV group as reference, the hazard ratios (HRs) for 2-year disability worsening, adjusted for treatment effect, were 1.23 (95% confidence interval (CI) 0.92-1.63, p = 0.16) for the medium NBV and 1.75 (95% CI 1.26-2.44, p = 0.001) for the low NBV. The predictive value of NBV groups was preserved over 4 years. Treatment effect appeared more evident in low-NBV patients (HR = 0.58) than in medium-NBV (HR = 0.72) and in high-NBV (HR = 0.80) patients; however, the difference was not significant ( p = 0.57).

CONCLUSION:

RRMS patients can be categorized into disability risk groups based on individual eNBV values according to baseline demographics and clinical characteristics.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Encéfalo / Imageamento por Ressonância Magnética / Esclerose Múltipla Recidivante-Remitente Tipo de estudo: Prognostic_studies Limite: Adolescent / Adult / Female / Humans / Male / Middle aged Idioma: En Ano de publicação: 2017 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Encéfalo / Imageamento por Ressonância Magnética / Esclerose Múltipla Recidivante-Remitente Tipo de estudo: Prognostic_studies Limite: Adolescent / Adult / Female / Humans / Male / Middle aged Idioma: En Ano de publicação: 2017 Tipo de documento: Article