Developing a Dementia Platform Databank Using Multiple Existing Cohorts
0
조회
0
다운로드
0
인용
0
참고문헌
키워드
초록
This study was conducted as a pilot project to evaluate the feasibility of building an integrate dementia platform converging preexisting dementia cohorts from several variable levels. The following four cohorts were used to develop this pilot platform: 1) Clinical Research Center for Dementia of South Korea (CREDOS), 2) Korean Brain Aging Study for Early Diagnosis and Prediction of Alzheimer’s disease (K-BASE), 3) Environmental Pollution-induced Neurological Effects (EPINEF) study, and 4) a prospective registry in Dementia Platform Korea project (DPKR). A total of 29916 patients were included in the platform with 348 integrated variables. Among participants, 13.9%, 31.5%, and 44.2% of patients had normal cognition, mild cognitive impairment, and dementia, respectively. The mean age was 72.4 years. Females accounted for 65.7% of all patients. Those with college or higher education and those without problems in reading or writing accounted for 12.3% and 46.8%, respectively. Marital status, cohabitation, family history of Parkinson’s disease, smoking and drinking status, physical activity, sleep status, and nutrition status had rates of missing information of 50% or more. Although individual cohorts were of the same domain and of high quality, we found there were several barriers to integrating individual cohorts, including variability in study variables and measurements. Although many researchers are trying to combine pre-existing cohorts, the process of integrating past data has not been easy. Therefore, it is necessary to establish a protocol with considerations for data integration at the cohort establishment stage.
Abstract
This study was conducted as a pilot project to evaluate the feasibility of building an integrate dementia platform converging preexisting dementia cohorts from several variable levels. The following four cohorts were used to develop this pilot platform: 1) Clinical Research Center for Dementia of South Korea (CREDOS), 2) Korean Brain Aging Study for Early Diagnosis and Prediction of Alzheimer’s disease (K-BASE), 3) Environmental Pollution-induced Neurological Effects (EPINEF) study, and 4) a prospective registry in Dementia Platform Korea project (DPKR). A total of 29916 patients were included in the platform with 348 integrated variables. Among participants, 13.9%, 31.5%, and 44.2% of patients had normal cognition, mild cognitive impairment, and dementia, respectively. The mean age was 72.4 years. Females accounted for 65.7% of all patients. Those with college or higher education and those without problems in reading or writing accounted for 12.3% and 46.8%, respectively. Marital status, cohabitation, family history of Parkinson’s disease, smoking and drinking status, physical activity, sleep status, and nutrition status had rates of missing information of 50% or more. Although individual cohorts were of the same domain and of high quality, we found there were several barriers to integrating individual cohorts, including variability in study variables and measurements. Although many researchers are trying to combine pre-existing cohorts, the process of integrating past data has not been easy. Therefore, it is necessary to establish a protocol with considerations for data integration at the cohort establishment stage.
참고문헌 (38)
- World Alzheimer report 2016: improving healthcare for people living with dementia: coverage, quality and costs now and in the future, "Prince M", Alzheimer’s Disease International, 110~115 (2016)
- Cummings J, "Alzheimer’s disease drug development pipeline: 2019", Alzheimer’s Dement (NY), 5, pp.272~293 (2019)
- "Dementia: the R&D landscape" (2015)[URL]
- Husain M, "Big data: could it ever cure Alzheimer’s disease?", Brain, 137, pp.2623~2624 (2014)
- Saykin AJ, "Genetic studies of quantitative MCI and AD phenotypes in ADNI : progress, opportunities, and plans", Alzheimers Dement, 11, pp.792~814 (2015)
- Ferguson AR, "Big data from small data : data-sharing in the ‘long tail’ of neuroscience", Nat Neurosci, 17, pp.1442~1447 (2014)
- Poldrack RA, "Making big data open : data sharing in neuroimaging", Nat Neurosci, 17, pp.1510~1517 (2014)
- Krysinska K, "Dementia registries around the globe and their applications : a systematic review", Alzheimers Dement, 13, pp.1031~1047 (2017)
- Bauermeister S, "The dementias platform UK(DPUK)data portal", Eur J Epidemiol, 35, pp.601~611 (2020)
- Lerche S, "Methods in neuroepidemiology characterization of European longitudinal cohort studies in Parkinson’s disease--report of the JPND working group BioLoC-PD", Neuroepidemiology, 45, pp.282~297 (2015)
- Kaye J, "Integrative analysis of longitudinal studies on aging and dementia(IALSA)", Innov Aging, 1, pp.1275~ (2017)
- Toga AW, "The global Alzheimer’s association interactive network", Alzheimers Dement, 12, pp.49~54 (2016)
- Neu SC, "Sharing data in the global Alzheimer’s association interactive network", Neuroimage, 124, pp.1168~1174 (2016)
- Doan A, "Principles of data integration" (2012), Morgan Kaufmann
- Hwang J, "Clinical and biomarker characteristics according to clinical spectrum of Alzheimer’s disease(AD)in the validation cohort of Korean brain aging study for the early diagnosis and prediction of AD", J Clin Med, 8, pp.341~ (2019)
- Cho J, "Association between exposure to polycyclic aromatic hydrocarbons and brain cortical thinning : the environmental pollution-induced neurological effects(EPINEF)study", Sci Total Environ, 737, pp.140097~ (2020)
- "KNHANES VI" (2015)[URL]
- Kang SJ, "Caregiver-administered neuropsychiatric inventory(CGA-NPI)", J Geriatr Psychiatry Neurol, 17, pp.32~35 (2004)
- 양동원, "Korean Dementia Screeing Questionnaire (KDSQ)의 개발과 타당도 및 신뢰도의 평가", 대한신경과학회지, 20(2), pp.135~141 (2002), 대한신경과학회
- Kang Y, "Seoul neuropsychological screening battery" (2003), Human Brain Research & Consulting Co
- 오지연, "한국어판 단문형 국제신처활동설문(IPAQ)의 신뢰도와 타당도", Korean Journal of Family Medicine, 28(7), pp.532~541 (2007), 대한가정의학회
- Yesavage JA, "Development and validation of a geriatric depression screening scale : a preliminary report", J Psychiatr Res, 17, pp.37~49 (1982)
- Lee JH, "Development of the Korean version of the consortium to establish a registry for Alzheimer’s disease assessment packet(CERAD-K) : clinical and neuropsychological assessment batteries", J Gerontol B Psychol Sci Soc Sci, 57, pp.47~53 (2002)
- Park HK, "Verification of the appropriateness when a shortened version of the mini nutritional assessment(MNA)is applied for determining the malnutrition state of elderly patients", J Korean Soc Parenter Enter Nutr, 2, pp.13~18 (2009)
- Kwon SM, "Differential roles of dysfunctional attitudes and automatic thoughts in depression : an integrated cognitive model of depression", Cognit Ther Res, 16, pp.309~328 (1992)
- "Development of the stress questionnaire for KNHANES: report of scientific study service" (2010)[URL]
- Sohn SI, "The reliability and validity of the Korean version of the Pittsburgh Sleep Quality Index", Sleep Breath, 16, pp.803~812 (2012)
- Han CW, "Development of the Korean version of short-form 36-item health survey : health related QOL of healthy elderly people and elderly patients in Korea", Tohoku J Exp Med, 203, pp.189~194 (2004)
- Ryu HJ, "Validity and reliability of the Korean version of the AD8 informant interview(K-AD8)in dementia", Alzheimer Dis Assoc Disord, 23, pp.371~376 (2009)
- Kim HJ, "Assessment of extent and role of tau in subcortical vascular cognitive impairment using 18F-AV1451 positron emission tomography imaging", JAMA Neurol, 75, pp.999~1007 (2018)
- Bos I, "The EMIF-AD multimodal biomarker discovery study : design, methods and cohort characteristics", Alzheimers Res Ther, 10, pp.64~ (2018)
- Gallacher J, "Challenges for optimizing real-world evidence in Alzheimer’s disease : the ROADMAP project", J Alzheimers Dis, 67, pp.495~501 (2019)
- Zanon C, "An application of item response theory to psychological test development", Psicol Reflex Crit, 29, pp.18~ (2016)
- Barnes SA, "Missing data assumptions and methods in a smoking cessation study", Addiction, 105, pp.431~437 (2010)
- Stockton MC, "Gender and smoking behavior in a worksite smoking cessation program", Addict Behav, 25, pp.347~360 (2000)
- Joenssen DW, "Hot deck methods for imputing missing data", International workshop on machine learning and data mining in pattern recognition, pp.63~75 (2012), Springer
- Rosenbaum PR, "The central role of the propensity score in observational studies for causal effects", Biometrika, 70, pp.41~55 (1983)
- Rubin DB, "Multiple imputation for nonresponse in surveys" (2004), Wiley-Interscience
