title: Usefulness of data from magnetic resonance imaging to improve prediction of dementia: population based cohort study.
abstract: OBJECTIVE
  To determine whether the addition of data derived from magnetic resonance imaging (MRI) of the brain to a model incorporating conventional risk variables improves prediction of dementia over 10 years of follow-up.
  
  
  METHODS
  Population based cohort study of individuals aged ≥ 65.
  
  
  METHODS
  The Dijon magnetic resonance imaging study cohort from the Three-City Study, France.
  
  
  METHODS
  1721 people without dementia who underwent an MRI scan at baseline and with known dementia status over 10 years' follow-up.
  
  
  METHODS
  Incident dementia (all cause and Alzheimer's disease).
  
  
  RESULTS
  During 10 years of follow-up, there were 119 confirmed cases of dementia, 84 of which were Alzheimer's disease. The conventional risk model incorporated age, sex, education, cognition, physical function, lifestyle (smoking, alcohol use), health (cardiovascular disease, diabetes, systolic blood pressure), and the apolipoprotein genotype (C statistic for discrimination performance was 0.77, 95% confidence interval 0.71 to 0.82). No significant differences were observed in the discrimination performance of the conventional risk model compared with models incorporating data from MRI including white matter lesion volume (C statistic 0.77, 95% confidence interval 0.72 to 0.82; P=0.48 for difference of C statistics), brain volume (0.77, 0.72 to 0.82; P=0.60), hippocampal volume (0.79, 0.74 to 0.84; P=0.07), or all three variables combined (0.79, 0.75 to 0.84; P=0.05). Inclusion of hippocampal volume or all three MRI variables combined in the conventional model did, however, lead to significant improvement in reclassification measured by using the integrated discrimination improvement index (P=0.03 and P=0.04) and showed increased net benefit in decision curve analysis. Similar results were observed when the outcome was restricted to Alzheimer's disease.
  
  
  CONCLUSIONS
  Data from MRI do not significantly improve discrimination performance in prediction of all cause dementia beyond a model incorporating demographic, cognitive, health, lifestyle, physical function, and genetic data. There were, however, statistical improvements in reclassification, prognostic separation, and some evidence of clinical utility.
authors.affiliation: Institute of Health and Society, Newcastle University, Newcastle, UK.
authors.forename: Blossom C M
authors.initials: BC
authors.lastname: Stephan
authors.affiliation: Inserm Research Centre for Epidemiology and Biostatistics (U897), Team Neuroepidemiology, F-33000 Bordeaux, France University of Bordeaux, College of Health Sciences, F-33000 Bordeaux, France.
authors.forename: Christophe
authors.initials: C
authors.lastname: Tzourio
authors.affiliation: University Hospital, Department of Neurology, Memory Consultation, CMRR, F-33000 Bordeaux, France.
authors.forename: Sophie
authors.initials: S
authors.lastname: Auriacombe
authors.affiliation: Inserm Research Centre for Epidemiology and Biostatistics (U897), Team Epidemiology and Neuropsychology of Brain Aging, F-33000 Bordeaux, France.
authors.forename: Hélène
authors.initials: H
authors.lastname: Amieva
authors.affiliation: Inserm Research Centre for Epidemiology and Biostatistics (U897), Team Neuroepidemiology, F-33000 Bordeaux, France University of Bordeaux, College of Health Sciences, F-33000 Bordeaux, France.
authors.forename: Carole
authors.initials: C
authors.lastname: Dufouil
authors.affiliation: Inserm Research Centre for Epidemiology and Biostatistics (U897), Team Neuroepidemiology, F-33000 Bordeaux, France.
authors.forename: Annick
authors.initials: A
authors.lastname: Alpérovitch
authors.affiliation: Inserm Research Centre for Epidemiology and Biostatistics (U897), Team Neuroepidemiology, F-33000 Bordeaux, France University of Bordeaux, College of Health Sciences, F-33000 Bordeaux, France tobias.kurth@u-bordeaux.fr.
authors.forename: Tobias
authors.initials: T
authors.lastname: Kurth
mesh_terms: D000368:Aged; D015897:Comorbidity; D003704:Dementia / Q000453:epidemiology / Q000473:pathology* / Q000503:physiopathology; D018450:Disease Progression; D005500:Follow-Up Studies; D005602:France; D006801:Humans; D008279:Magnetic Resonance Imaging; D009483:Neuropsychological Tests; D011237:Predictive Value of Tests; D015995:Prevalence; D011379:Prognosis; D011446:Prospective Studies; D015203:Reproducibility of Results; D012307:Risk Factors