|Title||Using dynamic microsimulation to project cognitive function in the elderly population.|
|Publication Type||Journal Article|
|Year of Publication||2022|
|Authors||Wei, Y, Heun-Johnson, H, Tysinger, B|
|Keywords||Alzheimer disease, Cognition, Cognitive Dysfunction, Neuropsychological tests, ROC Curve|
BACKGROUND: A long-term projection model based on nationally representative data and tracking disease progression across Alzheimer's disease continuum is important for economics evaluation of Alzheimer's disease and other dementias (ADOD) therapy.
METHODS: The Health and Retirement Study (HRS) includes an adapted version of the Telephone Interview for Cognitive Status (TICS27) to evaluate respondents' cognitive function. We developed an ordered probit transition model to predict future TICS27 score. This transition model is utilized in the Future Elderly Model (FEM), a dynamic microsimulation model of health and health-related economic outcomes for the US population. We validated the FEM TICS27 model using a five-fold cross validation approach, by comparing 10-year (2006-2016) simulated outcomes against observed HRS data.
RESULTS: In aggregate, the distribution of TICS27 scores after ten years of FEM simulation matches the HRS. FEM's assignment of cognitive/mortality status also matches those observed in HRS on the population level. At the individual level, the area under the receiver operating characteristic (AUROC) curve is 0.904 for prediction of dementia or dead with dementia in 10 years, the AUROC for predicting significant cognitive decline in two years for mild cognitive impairment patients is 0.722.
CONCLUSIONS: The FEM TICS27 model demonstrates its predictive accuracy for both two- and ten-year cognitive outcomes. Our cognition projection model is unique in its validation with an unbiased approach, resulting in a high-quality platform for assessing the burden of cognitive decline and translating the benefit of innovative therapies into long-term value to society.
|PubMed Central ID||PMC9477290|
|Grant List||R01 AG062277 / AG / NIA NIH HHS / United States |
P30 AG024968 / AG / NIA NIH HHS / United States