Development and Validation of the RxDx-Dementia Risk Index to Predict Dementia in Patients with Type 2 Diabetes and Hypertension. Mehta, H. B., Mehta, V., Tsai, C., Chen, H., Aparasu, R. R., & Johnson, M. L. Journal of Alzheimer's disease: JAD, 49(2):423–432, 2016.
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BACKGROUND: Elderly patients with type 2 diabetes mellitus and hypertension are at high risk for developing dementia. In addition to comorbid disease conditions (Dx), prescription drugs (Rx) are important risk factors for dementia. OBJECTIVE: Develop and validate the RxDx-Dementia risk index by combining diagnosis and prescription information in a single risk index to predict incident dementia, and compare its performance with diagnosis-based Charlson comorbidity score (CCS) and prescription-based chronic disease score (CDS). METHODS: Elderly patients diagnosed with type 2 diabetes mellitus and hypertension, and without prior dementia were identified from the Clinical Practice Research Datalink (2003-2012). A Cox proportional hazard model was constructed to model the time to dementia by incorporating age, gender, and 31 RxDx disease conditions as independent variables. Points were assigned to risk factors to obtain summary risk score. Discrimination and calibration of the risk index were evaluated. Different risk indices were compared against RxDx-Dementia risk index using c-statistic, net reclassification improvement (NRI) and integrated discrimination improvement (IDI). RESULTS: Of 133,176 patients with type 2 diabetes mellitus and hypertension, 3.42% patients developed dementia.The c-statistics value for RxDx-Dementia risk index was 0.806 (95% CI, 0.799-0.812). Based on the c-statistics, NRI and IDI values, the RxDx-Dementia risk index performed better compared to CCS, CDS, and their combinations. CONCLUSION: The RxDx-Dementia risk index can be a useful tool to identify hypertensive and diabetic patients who are at high risk of developing dementia. This has implications for clinical management of patients with multiple comorbid conditions as well as risk adjustment for database studies.
@article{mehta_development_2016,
	title = {Development and {Validation} of the {RxDx}-{Dementia} {Risk} {Index} to {Predict} {Dementia} in {Patients} with {Type} 2 {Diabetes} and {Hypertension}},
	volume = {49},
	issn = {1875-8908},
	doi = {10.3233/JAD-150466},
	abstract = {BACKGROUND: Elderly patients with type 2 diabetes mellitus and hypertension are at high risk for developing dementia. In addition to comorbid disease conditions (Dx), prescription drugs (Rx) are important risk factors for dementia.
OBJECTIVE: Develop and validate the RxDx-Dementia risk index by combining diagnosis and prescription information in a single risk index to predict incident dementia, and compare its performance with diagnosis-based Charlson comorbidity score (CCS) and prescription-based chronic disease score (CDS).
METHODS: Elderly patients diagnosed with type 2 diabetes mellitus and hypertension, and without prior dementia were identified from the Clinical Practice Research Datalink (2003-2012). A Cox proportional hazard model was constructed to model the time to dementia by incorporating age, gender, and 31 RxDx disease conditions as independent variables. Points were assigned to risk factors to obtain summary risk score. Discrimination and calibration of the risk index were evaluated. Different risk indices were compared against RxDx-Dementia risk index using c-statistic, net reclassification improvement (NRI) and integrated discrimination improvement (IDI).
RESULTS: Of 133,176 patients with type 2 diabetes mellitus and hypertension, 3.42\% patients developed dementia.The c-statistics value for RxDx-Dementia risk index was 0.806 (95\% CI, 0.799-0.812). Based on the c-statistics, NRI and IDI values, the RxDx-Dementia risk index performed better compared to CCS, CDS, and their combinations.
CONCLUSION: The RxDx-Dementia risk index can be a useful tool to identify hypertensive and diabetic patients who are at high risk of developing dementia. This has implications for clinical management of patients with multiple comorbid conditions as well as risk adjustment for database studies.},
	language = {eng},
	number = {2},
	journal = {Journal of Alzheimer's disease: JAD},
	author = {Mehta, Hemalkumar B. and Mehta, Vinay and Tsai, Chu-Lin and Chen, Hua and Aparasu, Rajender R. and Johnson, Michael L.},
	year = {2016},
	pmid = {26519436},
	keywords = {Aged, Aged, 80 and over, Cohort Studies, Dementia, Diabetes Mellitus, Type 2, Female, Humans, Hypertension, Male, Middle Aged, Predictive Value of Tests, Prescription Drugs, Proportional Hazards Models, Reproducibility of Results, Risk Assessment, Risk Factors, Type 2 diabetes, prediction model, risk index},
	pages = {423--432}
}
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