- Email: [email protected]
A multidomain prediction model for mild cognitive impairment to Alzheimer's disease conversion
Poster Presentations: P1 Background: Although hyperglycemia can affect cognitive function, the potential influence of episodes of severe hyperglycemia on future risk of dementia has not been evaluated at a population level in the elderly. Our aim was to examine the longitudinal association between severe hyperglycemic episodes and risk of dementia in a cohort of patients with type 2 diabetes (T2DM). Results: 2314 (14%) were diagnosed with dementia and 233 patients had > 1 hyperglycemic episode. Those with a history of hyperglycemia had an increased dementia incidence rate (369.4 events, 95% confidence interval (CI) 348,390 versus 541.4 events, 95% CI 158,695). Results from Cox proportional hazards models showed those with a hyperglycemic episode had a 40% greater risk of dementia versus those without hyperglycemia (Table 1) and there was suggestion of a trend in dose effect for those with > 1 hyperglycemic episode (Table 1). Sensitivity analyses revealed that those with diabetes ketoacidosis had a 150% greater risk of dementia versus those without a hyperglycemic episode (Table 1). Conclusions: Among patients with type 2 diabetes, those with a history of severe hyperglycemic episodes have a 30-40% increased risk of dementia compared to diabetic patients without these episodes. Since this population is at a greater risk of dementia, future studies should evaluate the association of severe glycemic dysregulation on markers of neurodegeneration.
P149
deciles of predicted risk. Results: The final prediction model included 9 factors from 5 domains: age, Functional Assessment Questionnaire (FAQ) score, American National Adult Reading Test score, Alzheimer’s Disease Assessment Scale-cognitive score, clock draw score, Trails A, ApoE status, left hippocampal volume and right inferior parietal cortical thickness (c-statistic 0.84, c-statistic accounting for overfitting 0.80). Left hippocampal volume was the most stable predictor and was present in 100% of bootstrap samples; conversely, right inferior parietal cortical thickness was present in only 51% of bootstrap samples. Our prediction model showed excellent calibration across MCI to AD conversion risk (see Figure). Conclusions: A multi-domain model that included age, function, neuropsychological assessments, ApoE status and imaging factors predicted conversion from MCI to AD with excellent accuracy. This model may be useful for enrolling subjects in clinical trials and targeting treatments currently under development to those individuals most likely to develop AD.
Table 1 Cox Proportional Hazards Models of Hyperglycemic Episodes and Risk of Dementia
Hyperglycemic Episode ( yes vs. no) Number of Episodes 0 1 2+ Diabetes Ketoacidosis only, (yes vs no)
Model 1*
Model 2**
HR
95% CI
HR
95% CI
1.41
1.07,1.86
1.28
1.1, 1.7
1.03, 1.91 1.03, 4.15 1.55,3.90
1.0 1.27 1.79 2.32
1.0 1.37 2.07 2.50
Figure 1. Predicted versus Actual Probability of Mild Cognitive Impairment Conversion to Alzheimer’s Disease 0.99, 1.7 0.89, 2.1 1.44,3.74
* ¼ adjusted for age ( as the time scale), education, gender and race, ** ¼ adjusted for model 1+ diabetes pharmacotherapy, glycosylated hemoglobin
P1-125
USE OF ANGIOTENSIN RECEPTOR BLOCKERS IS ASSOCIATED WITH DECREASED RISK OF DEMENTIA IN OLDER ADULTS: SECONDARY ANALYSIS OF THE GINKGO EVALUATION OF MEMORY STUDY
Sei Lee1, John Boscardin2, Irena Stijacic Cenzer2, Deborah Barnes3, UCSF/San Francisco VA, San Francisco, California, United States; 2 UCSF, San Francisco, California, United States; 3University of California, San Francisco, San Francisco, California, United States.
Jin Xia1, Sevil Yasar1, Qian-Li Xue1, Carla Mercado2, Annette Fitzpatrick2, Linda Fried3, Claudia Kawas4, Kaycee Sink5, Jeff Williamson5, Curt Furberg5, Michelle Carlson1, Steven DeKosky6, 1Johns Hopkins University, Baltimore, Maryland, United States; 2University of Washington, Seattle, Washington, United States; 3Columbia University, New York, New York, United States; 4University of California Irvine, Irvine, California, United States; 5Wake Forest University, Winston-Salem, North Carolina, United States; 6University of Virginia School of Medicine, Charlottesville, Virginia, United States.
Background: To effectively target therapies for preventing Alzheimer’s disease (AD), accurate methods are needed to identify patients at highest risk. Despite evidence that AD is a multi-factorial disease, much of the previous work on AD prediction has focused on single types of risk factors. Our goal was to develop a multi-domain prediction model incorporating many different types of risk factors to stratify patients into high and low risk groups for conversion from mild cognitive impairment (MCI) to AD. Methods: We examined 397 subjects diagnosed with MCI enrolled in the Alzheimer’s Dementia Neuroimaging Initiative (ADNI). The outcome was conversion from MCI to AD over 5 years. We developed our prediction model in stages, focusing in turn on 6 risk factor domains at baseline: demographics, symptoms/function, comorbid medical conditions, neuropsychological assessments, biomarkers and neuroimaging. For each domain, we used stepwise backward selection logistic regression to identify the predictors that were most strongly associated with conversion. We then combined these predictors into a final model to identify the factors that were independently associated with conversion. Discrimination was determined using the c-statistic; bootstrap methods were used to account for overfitting. Calibration was tested by plotting the predicted and actual probabilities of conversion across
Background: There is limited information on incidence of dementia among users of angiotensin-1 receptor blockers (ARB) or angiotensin-converting enzyme inhibitors (ACE-I). The objective of this study was to determine whether use of ARB or ACE-I is associated with reduced incidence of dementia and Alzheimer’s disease (AD) in older adults with normal cognition or mild cognitive impairment (MCI) at baseline. Methods: Secondary longitudinal data analysis of the Ginkgo Evaluation of Memory Study (GEMS) in community-dwelling adults at least 75 years of age with normal cognition (n ¼ 2587) or MCI (n ¼ 482) at baseline. The main outcome of this study was incident dementia and AD over a median 6.1-year period using Cox proportional hazard models after adjusting for confounders including hypertension. Results: 57.1% reported antihypertensive medication use at baseline of which 3.7% was ARB use and 16.7% ACE-I. There were 324 cases of dementia in participants with normal cognition and 199 cases in participants with MCI. ARB use was associated with a lower risk of incident dementia in participants with normal cognition and MCI compared with non-users of ARB. Hazard ratios (HR) and 95% Confidence Intervals (CI) for dementia in participants with normal cognition and MCI were 0.57 (0.41 - 0.78; p ¼ .001) and 0.41 (0.25 - 0.67; p ¼ 0.0003) respectively for ARBs.Results
P1-124
A MULTIDOMAIN PREDICTION MODEL FOR MILD COGNITIVE IMPAIRMENT TO ALZHEIMER’S DISEASE CONVERSION
1
P149
deciles of predicted risk. Results: The final prediction model included 9 factors from 5 domains: age, Functional Assessment Questionnaire (FAQ) score, American National Adult Reading Test score, Alzheimer’s Disease Assessment Scale-cognitive score, clock draw score, Trails A, ApoE status, left hippocampal volume and right inferior parietal cortical thickness (c-statistic 0.84, c-statistic accounting for overfitting 0.80). Left hippocampal volume was the most stable predictor and was present in 100% of bootstrap samples; conversely, right inferior parietal cortical thickness was present in only 51% of bootstrap samples. Our prediction model showed excellent calibration across MCI to AD conversion risk (see Figure). Conclusions: A multi-domain model that included age, function, neuropsychological assessments, ApoE status and imaging factors predicted conversion from MCI to AD with excellent accuracy. This model may be useful for enrolling subjects in clinical trials and targeting treatments currently under development to those individuals most likely to develop AD.
Table 1 Cox Proportional Hazards Models of Hyperglycemic Episodes and Risk of Dementia
Hyperglycemic Episode ( yes vs. no) Number of Episodes 0 1 2+ Diabetes Ketoacidosis only, (yes vs no)
Model 1*
Model 2**
HR
95% CI
HR
95% CI
1.41
1.07,1.86
1.28
1.1, 1.7
1.03, 1.91 1.03, 4.15 1.55,3.90
1.0 1.27 1.79 2.32
1.0 1.37 2.07 2.50
Figure 1. Predicted versus Actual Probability of Mild Cognitive Impairment Conversion to Alzheimer’s Disease 0.99, 1.7 0.89, 2.1 1.44,3.74
* ¼ adjusted for age ( as the time scale), education, gender and race, ** ¼ adjusted for model 1+ diabetes pharmacotherapy, glycosylated hemoglobin
P1-125
USE OF ANGIOTENSIN RECEPTOR BLOCKERS IS ASSOCIATED WITH DECREASED RISK OF DEMENTIA IN OLDER ADULTS: SECONDARY ANALYSIS OF THE GINKGO EVALUATION OF MEMORY STUDY
Sei Lee1, John Boscardin2, Irena Stijacic Cenzer2, Deborah Barnes3, UCSF/San Francisco VA, San Francisco, California, United States; 2 UCSF, San Francisco, California, United States; 3University of California, San Francisco, San Francisco, California, United States.
Jin Xia1, Sevil Yasar1, Qian-Li Xue1, Carla Mercado2, Annette Fitzpatrick2, Linda Fried3, Claudia Kawas4, Kaycee Sink5, Jeff Williamson5, Curt Furberg5, Michelle Carlson1, Steven DeKosky6, 1Johns Hopkins University, Baltimore, Maryland, United States; 2University of Washington, Seattle, Washington, United States; 3Columbia University, New York, New York, United States; 4University of California Irvine, Irvine, California, United States; 5Wake Forest University, Winston-Salem, North Carolina, United States; 6University of Virginia School of Medicine, Charlottesville, Virginia, United States.
Background: To effectively target therapies for preventing Alzheimer’s disease (AD), accurate methods are needed to identify patients at highest risk. Despite evidence that AD is a multi-factorial disease, much of the previous work on AD prediction has focused on single types of risk factors. Our goal was to develop a multi-domain prediction model incorporating many different types of risk factors to stratify patients into high and low risk groups for conversion from mild cognitive impairment (MCI) to AD. Methods: We examined 397 subjects diagnosed with MCI enrolled in the Alzheimer’s Dementia Neuroimaging Initiative (ADNI). The outcome was conversion from MCI to AD over 5 years. We developed our prediction model in stages, focusing in turn on 6 risk factor domains at baseline: demographics, symptoms/function, comorbid medical conditions, neuropsychological assessments, biomarkers and neuroimaging. For each domain, we used stepwise backward selection logistic regression to identify the predictors that were most strongly associated with conversion. We then combined these predictors into a final model to identify the factors that were independently associated with conversion. Discrimination was determined using the c-statistic; bootstrap methods were used to account for overfitting. Calibration was tested by plotting the predicted and actual probabilities of conversion across
Background: There is limited information on incidence of dementia among users of angiotensin-1 receptor blockers (ARB) or angiotensin-converting enzyme inhibitors (ACE-I). The objective of this study was to determine whether use of ARB or ACE-I is associated with reduced incidence of dementia and Alzheimer’s disease (AD) in older adults with normal cognition or mild cognitive impairment (MCI) at baseline. Methods: Secondary longitudinal data analysis of the Ginkgo Evaluation of Memory Study (GEMS) in community-dwelling adults at least 75 years of age with normal cognition (n ¼ 2587) or MCI (n ¼ 482) at baseline. The main outcome of this study was incident dementia and AD over a median 6.1-year period using Cox proportional hazard models after adjusting for confounders including hypertension. Results: 57.1% reported antihypertensive medication use at baseline of which 3.7% was ARB use and 16.7% ACE-I. There were 324 cases of dementia in participants with normal cognition and 199 cases in participants with MCI. ARB use was associated with a lower risk of incident dementia in participants with normal cognition and MCI compared with non-users of ARB. Hazard ratios (HR) and 95% Confidence Intervals (CI) for dementia in participants with normal cognition and MCI were 0.57 (0.41 - 0.78; p ¼ .001) and 0.41 (0.25 - 0.67; p ¼ 0.0003) respectively for ARBs.Results
P1-124
A MULTIDOMAIN PREDICTION MODEL FOR MILD COGNITIVE IMPAIRMENT TO ALZHEIMER’S DISEASE CONVERSION
1