NEWS & VIEWS DEMENTIA
Risk prediction models in dementia prevention Alina Solomon and Hilkka Soininen Refers to Pankratz, V. S. et al. Predicting the risk of mild cognitive impairment in the Mayo Clinic Study of Aging. Neurology 84, 1433–1442 (2015)
The list of vascular, lifestyle-related and other risk factors and biomarkers associated with dementia development has constantly grown over the past few years. A recent study emphasizes the importance of risk prediction models for identification of individuals with increased risk of future cognitive impairment who could benefit from preventive interventions. On 16–17th March 2015, the WHO hosted its first Ministerial Conference on Global Action Against Dementia, placing demen tia prevention high on the global public health agenda. The main focus of dementia research has shifted towards presympto matic or pre-dementia disease stages and at-risk states, which are thought to be more likely to be amenable to intervention than is dementia itself. The need for early identi fication of at-risk individuals who could benefit from preventive interventions has led to a growing interest in dementia risk prediction.
‘‘
…performance requirements should consider the purpose of a prediction model
’’
A recent study 1 published in Neurology presented a risk score for mild cogni tive impairment (MCI) formulated in the population-b ased Mayo Clinic Study of Aging. The purpose of the study was to predict the risk of developing of MCI in the short term (median follow-up: 5 years) in cognitively normal individuals aged 70–89 years. Basic and augmented versions of the risk score were formulated, with sexspecific predictors. The basic risk score included education, self-reported memory concerns, diabetes in relation to age, history of alcohol problems, stroke, and atrial fibrillation, all of which were risk factors in both men and women; smoking, midlife dyslipidaemia, diabetes and hypertension, which were specific to women; and obesity
and marital status, which were specific to men. The basic score had lower predictive ability than the augmented version (C statis tic: 0.60 and 0.7, respectively), which addi tionally included agitation, apathy, anxiety, the Clinical Dementia Rating Scale and the Short Test of Mental Status (both men and women); the Unified Parkinson’s Disease Rating Scale and the Functional Activities Questionnaire (women only); and slow gait, anxiety, and depression (men only). This MCI risk score is a valuable addi tion to the existing literature on prognostic models in dementia prevention, because it illustrates several key issues. The first key issue in developing prognostic risk scores is that the performance requirements should consider the purpose of a prediction model. The performance of the new risk score falls within the range previously reported for dementia risk scores (C statistic 0.65–0.81, Supplementary Table 1 online). A cut-off of
Risk prediction models in dementia prevention Alina Solomon and Hilkka Soininen Refers to Pankratz, V. S. et al. Predicting the risk of mild cognitive impairment in the Mayo Clinic Study of Aging. Neurology 84, 1433–1442 (2015)
The list of vascular, lifestyle-related and other risk factors and biomarkers associated with dementia development has constantly grown over the past few years. A recent study emphasizes the importance of risk prediction models for identification of individuals with increased risk of future cognitive impairment who could benefit from preventive interventions. On 16–17th March 2015, the WHO hosted its first Ministerial Conference on Global Action Against Dementia, placing demen tia prevention high on the global public health agenda. The main focus of dementia research has shifted towards presympto matic or pre-dementia disease stages and at-risk states, which are thought to be more likely to be amenable to intervention than is dementia itself. The need for early identi fication of at-risk individuals who could benefit from preventive interventions has led to a growing interest in dementia risk prediction.
‘‘
…performance requirements should consider the purpose of a prediction model
’’
A recent study 1 published in Neurology presented a risk score for mild cogni tive impairment (MCI) formulated in the population-b ased Mayo Clinic Study of Aging. The purpose of the study was to predict the risk of developing of MCI in the short term (median follow-up: 5 years) in cognitively normal individuals aged 70–89 years. Basic and augmented versions of the risk score were formulated, with sexspecific predictors. The basic risk score included education, self-reported memory concerns, diabetes in relation to age, history of alcohol problems, stroke, and atrial fibrillation, all of which were risk factors in both men and women; smoking, midlife dyslipidaemia, diabetes and hypertension, which were specific to women; and obesity
and marital status, which were specific to men. The basic score had lower predictive ability than the augmented version (C statis tic: 0.60 and 0.7, respectively), which addi tionally included agitation, apathy, anxiety, the Clinical Dementia Rating Scale and the Short Test of Mental Status (both men and women); the Unified Parkinson’s Disease Rating Scale and the Functional Activities Questionnaire (women only); and slow gait, anxiety, and depression (men only). This MCI risk score is a valuable addi tion to the existing literature on prognostic models in dementia prevention, because it illustrates several key issues. The first key issue in developing prognostic risk scores is that the performance requirements should consider the purpose of a prediction model. The performance of the new risk score falls within the range previously reported for dementia risk scores (C statistic 0.65–0.81, Supplementary Table 1 online). A cut-off of
