Browse > Article
http://dx.doi.org/10.22857/kjbp.2020.27.2.007

Development of Cerebral Amyloid Positivity Predicting Models Using Clinical Indicators  

Chun, Young Jae (Department of Psychiatry, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea)
Joo, Soo Hyun (Department of Psychiatry, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea)
Publication Information
Korean Journal of Biological Psychiatry / v.27, no.2, 2020 , pp. 94-100 More about this Journal
Abstract
Objectives Amyloid β positron emission tomography (Aβ PET) is widely used as a diagnostic tool in patients who have symptoms of cognitive impairment, however, this diagnostic examination is too expensive. Thus, predicting the positivity of Aβ PET before patients undergo the examination is essential. We aimed to analyze clinical predictors of patients who underwent Aβ PET retrospectively, and to develop a predicting model of Aβ PET positivity. Methods 468 patients who underwent Aβ PET with cognitive impairment were recruited and their clinical indicators were analyzed retrospectively. We specified the primary outcome as Aβ PET positivity, and included variables such as age, sex, body mass index, diastolic blood pressure, systolic blood pressure, education, dementia family history, Mini Mental Status Examination (MMSE), Clinical Dementia Rating (CDR), Clinical Dementia Rating-Sum of Box (CDR-SB), hypertension (HTN), diabetes mellitus (DM) and presence of apolipoprotein E (ApoE) E4 as potential predictors. We developed three final models of amyloid positivity prediction for total subjects, mild cognitive impairment (MCI) and Alzheimer's disease (AD) dementia using a multivariate stepwise logistic regression analysis. Receiver operating characteristic (ROC) curve analysis was performed and the area under curve (AUC) value was calculated for the ROC curve. Results Aβ PET negative patients were 49.6% (n = 232), and Aβ PET positive patients were 50.4% (n = 236). In the final model of all subjects, older age, female sex, presence of ApoE E4 and lower MMSE are associated with Aβ PET positivity. The AUC value was 0.296. In the final model of MCI subjects (n = 244), older age and presence of ApoE E4 are associated with Aβ PET positivity. The AUC value was 0.725. In the final model of AD subjects (n = 173), lower MMSE scores, the presence of ApoE E4 and history of HTN are associated with Aβ PET positivity. The AUC value was 0.681. Conclusions The cerebral amyloid positivity model, which was based on commonly available clinical indicators, can be useful for prediction of amyloid PET positivity in MCI or AD patients.
Keywords
Amyloid; Alzheimer's disease; Mild cognitive impairment; Apolipoprotein E.;
Citations & Related Records
연도 인용수 순위
  • Reference
1 Lee JH, Byun MS, Yi D, Sohn BK, Jeon SY, Lee Y, et al. Prediction of cerebral amyloid with common information obtained from memory clinic practice. Front Aging Neurosci 2018;10:309.   DOI
2 Mielke MM, Wiste HJ, Weigand SD, Knopman DS, Lowe VJ, Roberts RO, et al. Indicators of amyloid burden in a population-based study of cognitively normal elderly. Neurology 2012;79:1570-1577.   DOI
3 Chetelat G, La Joie R, Villain N, Perrotin A, de La Sayette V, Eustache F, et al. Amyloid imaging in cognitively normal individuals, at-risk populations and preclinical Alzheimer's disease. Neuroimage Clin 2013;2:356-365.   DOI
4 Bischof GN, Rodrigue KM, Kennedy KM, Devous MD, Park DC. Amyloid deposition in younger adults is linked to episodic memory performance. Neurology 2016;87:2562-2566.   DOI
5 Tomadesso C, de La Sayette V, de Flores R, Bourgeat P, Villemagne VL, Egret S, et al. Neuropsychology and neuroimaging profiles of amyloid-positive versus amyloid-negative amnestic mild cognitive impairment patients. Alzheimers Dement (Amst) 2018;10:269-277.   DOI
6 Wolk DA, Price JC, Saxton JA, Snitz BE, James JA, Lopez OL, et al. Amyloid imaging in mild cognitive impairment subtypes. Ann Neurol 2009;65:557-568.   DOI
7 Wiseman RM, Saxby BK, Burton EJ, Barber R, Ford GA, O'Brien JT. Hippocampal atrophy, whole brain volume, and white matter lesions in older hypertensive subjects. Neurology 2004;63:1892-1897.   DOI
8 Farrar G. Regional visual read inspection of [18F] flutemetamol brain images from end-of-life and amnestic MCI subjects. J Nucl Med 2017;58 Suppl 1:1250.
9 Jeon SY, Byun MS, Yi D, Lee JH, Choe YM, Kim HJ, et al. Distinct clinical characteristics depending on cerebral amyloid positivity in patients with Alzheimer disease dementia. J Korean Geriatr Psychiatry 2016;20:68-74.
10 Risacher SL, Kim S, Shen L, Nho K, Foroud T, Green RC, et al. The role of apolipoprotein E (APOE) genotype in early mild cognitive impairment (E-MCI). Front Aging Neurosci 2013;5:11.
11 Choi SH, Na DL, Lee BH, Hahm DS, Jeong JH, Yoon SJ, et al. Estimating the Validity of the Korean Version of Expanded Clinical Dementia Rating (CDR) Scale. J Korean Neurol Assoc 2001;19:585-591.
12 McKhann GM, Knopman DS, Chertkow H, Hyman BT, Jack CR Jr, Kawas CH, et al. The diagnosis of dementia due to Alzheimer's disease: recommendations from the National Institute on AgingAlzheimer's Association workgroups on diagnostic guidelines for Alzheimer's disease. Alzheimers Dement 2011;7:263-269.   DOI
13 Kim HJ, Cho H, Werring DJ, Jang YK, Kim YJ, Lee JS, et al. 18FAV-1451 PET imaging in three patients with probable cerebral amyloid angiopathy. J Alzheimers Dis 2017;57:711-716.   DOI
14 Kang Y, Na DL, Hahn S. A validity study on the Korean MiniMental State Examination (K-MMSE) in dementia patients. J Korean Neurol Assoc 1997;15:300-308.
15 Haghighi M, Smith A, Morgan D, Small B, Huang S. Identifying cost-effective predictive rules of amyloid-β level by integrating neuropsychological tests and plasma-based markers. J Alzheimers Dis 2015;43:1261-1270.
16 Kim SE, Woo S, Kim SW, Chin J, Kim HJ, Lee BI, et al. A nomogram for predicting amyloid PET positivity in amnestic mild cognitive impairment. J Alzheimers Dis 2018;66:681-691.   DOI
17 Alzheimer's Association. 2013 Alzheimer's disease facts and figures. Alzheimers Dement 2013;9:208-245.   DOI
18 Lee JS, Kang MJ, Nam HJ, Kim YJ, Lee OJ, Kim KW. Korean Dementia Observatory 2019. Seoul: National Institute of Dementia; 2020.
19 Kang DW, Lim HK. Current knowledge and clinical application of brain imaging in Alzheimer's disease. J Korean Neuropsychiatr Assoc 2018;57:12-22.   DOI
20 Beach TG, Monsell SE, Phillips LE, Kukull W. Accuracy of the clinical diagnosis of Alzheimer disease at National Institute on Aging Alzheimer Disease Centers, 2005-2010. J Neuropathol Exp Neurol 2012;71:266-273.   DOI
21 Landau SM, Horng A, Fero A, Jagust WJ; Alzheimer's Disease Neuroimaging Initiative. Amyloid negativity in patients with clinically diagnosed Alzheimer disease and MCI. Neurology 2016;86:1377-1385.   DOI
22 Martinez G, Vernooij RW, Fuentes Padilla P, Zamora J, Bonfill Cosp X, Flicker L. 18F PET with florbetapir for the early diagnosis of Alzheimer's disease dementia and other dementias in people with mild cognitive impairment (MCI). Cochrane Database Syst Rev 2017;11:CD012216.
23 Ossenkoppele R, Jansen WJ, Rabinovici GD, Knol DL, van der Flier WM, van Berckel BNM, et al. Prevalence of amyloid PET positivity in dementia syndromes: a meta-analysis. JAMA 2015;313:1939-1949.   DOI
24 Bateman RJ, Xiong C, Benzinger TLS, Fagan AM, Goate A, Fox NC, et al. Clinical and biomarker changes in dominantly inherited Alzheimer's disease. N Engl J Med 2012;367:795-804.   DOI
25 American Psychiatric Association. Diagnostic and statistical manual of mental disorders: DSM-5. 5th ed. Arlington, VA: American Psychaitric Association;2013. p.585-589.
26 Barthel H, Gertz HJ, Dresel S, Peters O, Bartenstein P, Buerger K, et al. Cerebral amyloid-β PET with florbetaben (18F) in patients with Alzheimer's disease and healthy controls: a multicentre phase 2 diagnostic study. Lancet Neurol 2011;10:424-435.   DOI
27 Beauchet O, Celle S, Roche F, Bartha R, Montero-Odasso M, Allali G, et al. Blood pressure levels and brain volume reduction: a systematic review and meta-analysis. J Hypertens 2013;31:1502-1516.   DOI
28 Power MC, Schneider AL, Wruck L, Griswold M, Coker LH, Alonso A, et al. Life-course blood pressure in relation to brain volumes. Alzheimers Dement 2016;12:890-899.   DOI
29 Glodzik L, Mosconi L, Tsui W, de Santi S, Zinkowski R, Pirraglia E, et al. Alzheimer's disease markers, hypertension, and gray matter damage in normal elderly. Neurobiol Aging 2012;33:1215-1227.   DOI
30 Ossenkoppele R, Prins ND, Pijnenburg YAL, Lemstra AW, van der Flier WM, Adriaanse SF, et al. Impact of molecular imaging on the diagnostic process in a memory clinic. Alzheimers Dement 2013;9:414-421.   DOI
31 Schneider JA. High blood pressure and microinfarcts: a link between vascular risk factors, dementia, and clinical Alzheimer's disease. J Am Geriatr Soc 2009;57:2146-2147.   DOI
32 Vemuri P, Knopman DS, Lesnick TG, Przybelski SA, Mielke MM, Graff-Radford J, et al. Evaluation of amyloid protective factors and Alzheimer disease neurodegeneration protective factors in elderly individuals. JAMA Neurol 2017;74:718-726.   DOI