Development and validation of a priori risk model for extensive white matter lesions in people age 65 years or older: the Dijon MRI study. Issue 12 (29th December 2017)

• Record Type: Journal Article
• Authors: Tully, Phillip J; Qchiqach, Sarah; Pereira, Edwige; Debette, Stephanie; Mazoyer, Bernard; Tzourio, Christophe
• Is Part Of: BMJ open. Volume 7:Issue 12(2017)
• Publication Date: 2017-12-29
• Subjects: white matter hyperintensities -- leukoaraiosis -- magnetic resonance imaging -- receiver operating characteristics -- predictive risk; Medicine -- Research -- Periodicals; 610.72
• DOI: 10.1136/bmjopen-2017-018328
• Languages: English
• ISSNs: 2044-6055

Abstract

Abstract : 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 cm 3 ) 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.