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Development and validation of a priori risk model for extensive white matter lesions in people age 65 years or older: the Dijon MRI study
  1. Phillip J Tully1,
  2. Sarah Qchiqach1,
  3. Edwige Pereira1,
  4. Stephanie Debette1,
  5. Bernard Mazoyer2,
  6. Christophe Tzourio1
  1. 1 Univ. Bordeaux, Inserm, Bordeaux Population Health Research Center, UMR 1219, CHU Bordeaux, F-33000 Bordeaux, France
  2. 2 UMR5293, Groupe d’Imagerie Neurofonctionnelle, University Bordeaux, Institut des Maladies Neurodégénératives, Bordeaux, France
  1. Correspondence to Professor Christophe Tzourio; christophe.tzourio{at}


Objectives The objective was to develop and validate a risk model for the likelihood of extensive white matter lesions (extWML) to inform clinicians on whether to proceed with or forgo diagnostic MRI.

Design Population-based cohort study and multivariable prediction model.

Setting Two representative samples from France.

Participants Persons aged 60–80 years without dementia or stroke. Derivation sample n=1714; validation sample n=789.

Primary and secondary outcome measures Volume of extWML (log cm3) was obtained from T2-weighted images in a 1.5 T scanner. 20 candidate risk factors for extWML were evaluated with the C-statistic. Secondary outcomes in validation included incident stroke over 12 years follow-up.

Results The multivariable prediction model included six clinical risk factors (C-statistic=0.61). A cut-off of 7 points on the multivariable prediction model yielded the optimum balance in sensitivity 63.7% and specificity 54.0% and the negative predictive value was high (81.8%), but the positive predictive value was low (31.5%). In further validation, incident stroke risk was associated with continuous scores on the multivariable prediction model (HR 1.02; 95% CI 1.01 to 1.04, P=0.02) and dichotomised scores from the multivariable prediction model (HR 1.28; 95% CI 1.02 to 1.60, P=0.03).

Conclusions A simple clinical risk equation for WML constituted by six variables can inform decisions whether to proceed with or forgo brain MRI. The high-negative predictive value demonstrates potential to reduce unnecessary MRI in the population aged 60–80 years.

  • white matter hyperintensities
  • leukoaraiosis
  • magnetic resonance imaging
  • receiver operating characteristics
  • predictive risk

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  • Contributors PJT wrote the statistical analysis plan, drafted and revised the paper. SQ wrote the statistical analysis plan, cleaned and analysed the data, and drafted and revised the paper. She is guarantor. EP wrote the statistical analysis plan and revised the draft paper. SD revised the draft paper. BM monitored data collection for the entire study and revised the draft paper. CT designed the study, monitored data collection for the entire study and revised the draft paper.

  • Funding The Fondation pour la Recherche Medicale funded the preparation and initiation of the study. The Fondation Plan Alzheimer partly funded the follow-up of the study. The 3C study is also supported by the Caisse Nationale Maladie des Travailleurs Salaries, Direction Generale de la Sante, MGEN, Institut de la Longevite, Conseils Regionaux of Aquitaine and Bourgogne, Fondation de France, and the Ministry of Research-INSERM Programme “Cohortes et collections de donnees biologiques.” The 3C study supports are listed on the study website (

  • Disclaimer The funding organisations played no role in the design and conduct of the study and were not involved in collection, management, analysis and interpretation of the data or in preparation, review or approval of the manuscript.

  • Competing interests None declared.

  • Ethics approval University Hospital of Kremlin-Bicêtre.

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Data sharing statement The 3C Dijon MRI study data are not on open access but are accessible through a process described on the study website (

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