Analysis of conversion of Alzheimer’s disease using a multi-state Markov model
| Autor: | Yingjie Li, Alzheimer’s Disease Neuroimaging Initiative, Jongeun Choi, David C. Zhu, Liangliang Zhang, Chae Young Lim, Andrea Bozoki, Tapabrata Maiti |
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| Rok vydání: | 2018 |
| Předmět: |
Male
Statistics and Probability Oncology medicine.medical_specialty Epidemiology Neuroimaging Disease Markov model 01 natural sciences 010104 statistics & probability 03 medical and health sciences Sex Factors 0302 clinical medicine Health Information Management Survival probability Alzheimer Disease Risk Factors Internal medicine medicine Humans 030212 general & internal medicine 0101 mathematics Aged Cause of death Magnetic Resonance Imaging Scan Multi state business.industry Cancer medicine.disease Markov Chains Left truncation Disease Progression Female business |
| Zdroj: | Statistical Methods in Medical Research. 28:2801-2819 |
| ISSN: | 1477-0334 0962-2802 |
| Popis: | With rapid aging of world population, Alzheimer’s disease is becoming a leading cause of death after cardiovascular disease and cancer. Nearly 10% of people who are over 65 years old are affected by Alzheimer’s disease. The causes have been studied intensively, but no definitive answer has been found. Genetic predisposition, abnormal protein deposits in brain, and environmental factors are suspected to play a role in the development of this disease. In this paper, we model progression of Alzheimer’s disease using a multi-state Markov model to investigate the significance of known risk factors such as age, apolipoprotein E4, and some brain structural volumetric variables from magnetic resonance imaging scans (e.g., hippocampus, etc.) while predicting transitions between different clinical diagnosis states. With the Alzheimer’s Disease Neuroimaging Initiative data, we found that the model with age is not significant (p = 0.1733) according to the likelihood ratio test, but the apolipoprotein E4 is a significant risk factor, and the examination of apolipoprotein E4-by-sex interaction suggests that the apolipoprotein E4 link to Alzheimer’s disease is stronger in women. Given the estimated transition probabilities, the prediction accuracy is as high as 0.7849. |
| Databáze: | OpenAIRE |
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