Analysis of conversion of Alzheimer’s disease using a multi-state Markov model
العنوان: | Analysis of conversion of Alzheimer’s disease using a multi-state Markov model |
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المؤلفون: | Yingjie Li, Alzheimer’s Disease Neuroimaging Initiative, Jongeun Choi, David C. Zhu, Liangliang Zhang, Chae Young Lim, Andrea Bozoki, Tapabrata Maiti |
المصدر: | Statistical Methods in Medical Research. 28:2801-2819 |
بيانات النشر: | SAGE Publications, 2018. |
سنة النشر: | 2018 |
مصطلحات موضوعية: | 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 |
الوصف: | 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. |
تدمد: | 1477-0334 0962-2802 |
URL الوصول: | https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6688e47216bc292720668a1061085dfa https://doi.org/10.1177/0962280218786525 |
حقوق: | CLOSED |
رقم الأكسشن: | edsair.doi.dedup.....6688e47216bc292720668a1061085dfa |
قاعدة البيانات: | OpenAIRE |
تدمد: | 14770334 09622802 |
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