Assessing the Predictive Validity of Simple Dementia Risk Models in Harmonized Stroke Cohorts.,Stroke

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Assessing the Predictive Validity of Simple Dementia Risk Models in Harmonized Stroke Cohorts.
Stroke ( IF 8.3 ) Pub Date : 2020-06-17 , DOI: 10.1161/strokeaha.120.027473
Eugene Y H Tang ₁ , Christopher I Price ₁ , Louise Robinson ₁ , Catherine Exley ₁ , David W Desmond , Sebastian Köhler ₂ , Julie Staals ₃ , Bonnie Yin Ka Lam ₄ , Adrian Wong ₄ , Vincent Mok ₄ , Regis Bordet ₅ , Anne-Marie Bordet ₅ , Thibaut Dondaine ₅ , Jessica W Lo ₆ , Perminder S Sachdev _{6,

7} , Blossom C M Stephan ₈ ,

Affiliation

Population Health Sciences Institute, Newcastle University, Campus for Ageing and Vitality, Newcastle Upon Tyne, United Kingdom (E.Y.H.T., C.I.P., L.R., C.E.).
School for Mental Health and Neuroscience, Maastricht University, the Netherlands (S.K.).
Department of Neurology, Cardiovascular Research Institute Maastricht, Maastricht University Medical Center, the Netherlands (J.S.).
Division of Neurology, Department of Medicine and Therapeutics, Faculty of Medicine, Gerald Choa Neuroscience Centre, Therese Pei Fong Chow Research Centre for Prevention of Dementia, Lui Che Woo Institute of Innovative Medicine, The Chinese University of Hong Kong SAR (B.Y.K.L., A.W., V.M.).
University Lille, Inserm, CHU Lille, U1171-Degenerative and Vascular Cognitive Disorders, France (R.B., A.-M.B., T.D.).
Centre for Healthy Brain Ageing, School of Psychiatry, University of New South Wales, Sydney, Australia (J.W.L., P.S.S.).
Neuropsychiatric Institute, Prince of Wales Hospital, Sydney (P.S.S.).
Institute of Mental Health, Division of Psychiatry and Applied Psychology, School of Medicine, Nottingham University, UK (B.C.M.S.).

Background and Purpose:Stroke is associated with an increased risk of dementia. To assist in the early identification of individuals at high risk of future dementia, numerous prediction models have been developed for use in the general population. However, it is not known whether such models also provide accurate predictions among stroke patients. Therefore, the aim of this study was to determine whether existing dementia risk prediction models that were developed for use in the general population can also be applied to individuals with a history of stroke to predict poststroke dementia with equivalent predictive validity.Methods:Data were harmonized from 4 stroke studies (follow-up range, ≈12–18 months poststroke) from Hong Kong, the United States, the Netherlands, and France. Regression analysis was used to test 3 risk prediction models: the Cardiovascular Risk Factors, Aging and Dementia score, the Australian National University Alzheimer Disease Risk Index, and the Brief Dementia Screening Indicator. Model performance or discrimination accuracy was assessed using the C statistic or area under the curve. Calibration was tested using the Grønnesby and Borgan and the goodness-of-fit tests.Results:The predictive accuracy of the models varied but was generally low compared with the original development cohorts, with the Australian National University Alzheimer Disease Risk Index (C-statistic, 0.66) and the Brief Dementia Screening Indicator (C-statistic, 0.61) both performing better than the Cardiovascular Risk Factors, Aging and Dementia score (area under the curve, 0.53).Conclusions:Dementia risk prediction models developed for the general population do not perform well in individuals with stroke. Their poor performance could have been due to the need for additional or different predictors related to stroke and vascular risk factors or methodological differences across studies (eg, length of follow-up, age distribution). Future work is needed to develop simple and cost-effective risk prediction models specific to poststroke dementia.

更新日期：2020-06-23

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