Identification of prognostic factors to predict cognitive decline of patients with early Alzheimer's disease in the Japanese Alzheimer's Disease Neuroimaging Initiative study
Abstract Introduction The objective of this study was to determine the factors including neuropsychological test performances and cerebrospinal fluid (CSF) biomarkers which can predict disease progression of early Alzheimer's disease (AD) in a Japanese population. Methods The group classificati...
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Wiley
2019-01-01
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| Series: | Alzheimer’s & Dementia: Translational Research & Clinical Interventions |
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| Online Access: | https://doi.org/10.1016/j.trci.2019.06.004 |
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| author | Takuya Yagi Michio Kanekiyo Junichi Ito Ryoko Ihara Kazushi Suzuki Atsushi Iwata Takeshi Iwatsubo Ken Aoshima Alzheimer's Disease Neuroimaging Initiative Japanese Alzheimer's Disease Neuroimaging Initiative |
| author_facet | Takuya Yagi Michio Kanekiyo Junichi Ito Ryoko Ihara Kazushi Suzuki Atsushi Iwata Takeshi Iwatsubo Ken Aoshima Alzheimer's Disease Neuroimaging Initiative Japanese Alzheimer's Disease Neuroimaging Initiative |
| author_sort | Takuya Yagi |
| collection | DOAJ |
| description | Abstract Introduction The objective of this study was to determine the factors including neuropsychological test performances and cerebrospinal fluid (CSF) biomarkers which can predict disease progression of early Alzheimer's disease (AD) in a Japanese population. Methods The group classification on early AD population in both Japanese Alzheimer's Disease Neuroimaging Initiative (J‐ADNI) and North American ADNI (NA‐ADNI) was performed using the inclusion criteria including brain amyloid positivity on positron emission tomography or CSF. Participants with early AD from each cohort were stratified into two groups based on a cutoff 1.0 of Clinical Dementia Rating Scale Sum of Boxes (CDR‐SB) change at month 24 (m24): participants in “progress group” have CDR‐SB change ≥ 1.0 and participants in “stable group” have CDR‐SB change < 1.0. Then, we performed identification of prognostic factors from baseline items including neuropsychological scores (Assessment Scale‐Cognitive Subscale[ADAS‐cog 13], Mini‐Mental State Examination (MMSE), CDR, FAQ, and Geriatric Depression Scale), CSF markers (t‐tau, p‐tau, and beta‐amyloid 1‐42), vital signs (body weight, pulse rate, etc.,), by using two statistical approaches, Welch's t‐test and simple linear regression by ordinary least squares. Comparisons between participants with J‐ADNI and participants with NA‐ADNI were also performed. Results Trends of CDR‐SB changes were very similar between J‐ADNI and NA‐ADNI early AD population enrolled in this study. Baseline levels of CSF t‐tau, p‐tau, Mini‐Mental State Examination, FAQ, and ADAS‐cog13 were identified as prognostic factors in both J‐ADNI and NA‐ADNI. Based on a detailed subscale analysis on ADAS‐cog13, four subscales (Q1: word recall, Q3: construction, Q4: delayed word recall, and Q8: word recognition) were identified as prognostic factors in both J‐ADNI and NA‐ADNI. Discussion Characterizing population with early AD can provide benefits for promoting efficiency in conducting AD clinical trials for disease‐modifying treatments. Thus, implementing these prognostic factors into clinical trials may be potentially a good method to enrich participants with early AD who are suitable for evaluating treatment effects. |
| format | Article |
| id | doaj-art-db970f6ea5354e73a66f008471e163cb |
| institution | Kabale University |
| issn | 2352-8737 |
| language | English |
| publishDate | 2019-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Alzheimer’s & Dementia: Translational Research & Clinical Interventions |
| spelling | doaj-art-db970f6ea5354e73a66f008471e163cb2025-08-20T03:30:39ZengWileyAlzheimer’s & Dementia: Translational Research & Clinical Interventions2352-87372019-01-015136437310.1016/j.trci.2019.06.004Identification of prognostic factors to predict cognitive decline of patients with early Alzheimer's disease in the Japanese Alzheimer's Disease Neuroimaging Initiative studyTakuya Yagi0Michio Kanekiyo1Junichi Ito2Ryoko Ihara3Kazushi Suzuki4Atsushi Iwata5Takeshi Iwatsubo6Ken Aoshima7Alzheimer's Disease Neuroimaging Initiative8Japanese Alzheimer's Disease Neuroimaging Initiative9Eisai Co., Ltd.KoishikawaBunkyo‐kuTokyoJapanEisai Inc.Woodcliff LakeNJUSAEisai Co., Ltd.TokodaiTsukuba‐shiIbarakiJapanUnit for Early and Exploratory Clinical DevelopmentThe University of Tokyo HospitalTokyoJapanUnit for Early and Exploratory Clinical DevelopmentThe University of Tokyo HospitalTokyoJapanDepartment of NeurologyThe University of Tokyo HospitalTokyoJapanDepartment of NeuropathologyGraduate School of Medicine, The University of TokyoTokyoJapanEisai Co., Ltd.KoishikawaBunkyo‐kuTokyoJapanEisai Co., Ltd.KoishikawaBunkyo‐kuTokyoJapanEisai Co., Ltd.KoishikawaBunkyo‐kuTokyoJapanAbstract Introduction The objective of this study was to determine the factors including neuropsychological test performances and cerebrospinal fluid (CSF) biomarkers which can predict disease progression of early Alzheimer's disease (AD) in a Japanese population. Methods The group classification on early AD population in both Japanese Alzheimer's Disease Neuroimaging Initiative (J‐ADNI) and North American ADNI (NA‐ADNI) was performed using the inclusion criteria including brain amyloid positivity on positron emission tomography or CSF. Participants with early AD from each cohort were stratified into two groups based on a cutoff 1.0 of Clinical Dementia Rating Scale Sum of Boxes (CDR‐SB) change at month 24 (m24): participants in “progress group” have CDR‐SB change ≥ 1.0 and participants in “stable group” have CDR‐SB change < 1.0. Then, we performed identification of prognostic factors from baseline items including neuropsychological scores (Assessment Scale‐Cognitive Subscale[ADAS‐cog 13], Mini‐Mental State Examination (MMSE), CDR, FAQ, and Geriatric Depression Scale), CSF markers (t‐tau, p‐tau, and beta‐amyloid 1‐42), vital signs (body weight, pulse rate, etc.,), by using two statistical approaches, Welch's t‐test and simple linear regression by ordinary least squares. Comparisons between participants with J‐ADNI and participants with NA‐ADNI were also performed. Results Trends of CDR‐SB changes were very similar between J‐ADNI and NA‐ADNI early AD population enrolled in this study. Baseline levels of CSF t‐tau, p‐tau, Mini‐Mental State Examination, FAQ, and ADAS‐cog13 were identified as prognostic factors in both J‐ADNI and NA‐ADNI. Based on a detailed subscale analysis on ADAS‐cog13, four subscales (Q1: word recall, Q3: construction, Q4: delayed word recall, and Q8: word recognition) were identified as prognostic factors in both J‐ADNI and NA‐ADNI. Discussion Characterizing population with early AD can provide benefits for promoting efficiency in conducting AD clinical trials for disease‐modifying treatments. Thus, implementing these prognostic factors into clinical trials may be potentially a good method to enrich participants with early AD who are suitable for evaluating treatment effects.https://doi.org/10.1016/j.trci.2019.06.004J‐ADNIADNIAlzheimer's disease assessment scaleMini‐Mental State ExaminationThe clinical dementia ratingBiomarker |
| spellingShingle | Takuya Yagi Michio Kanekiyo Junichi Ito Ryoko Ihara Kazushi Suzuki Atsushi Iwata Takeshi Iwatsubo Ken Aoshima Alzheimer's Disease Neuroimaging Initiative Japanese Alzheimer's Disease Neuroimaging Initiative Identification of prognostic factors to predict cognitive decline of patients with early Alzheimer's disease in the Japanese Alzheimer's Disease Neuroimaging Initiative study Alzheimer’s & Dementia: Translational Research & Clinical Interventions J‐ADNI ADNI Alzheimer's disease assessment scale Mini‐Mental State Examination The clinical dementia rating Biomarker |
| title | Identification of prognostic factors to predict cognitive decline of patients with early Alzheimer's disease in the Japanese Alzheimer's Disease Neuroimaging Initiative study |
| title_full | Identification of prognostic factors to predict cognitive decline of patients with early Alzheimer's disease in the Japanese Alzheimer's Disease Neuroimaging Initiative study |
| title_fullStr | Identification of prognostic factors to predict cognitive decline of patients with early Alzheimer's disease in the Japanese Alzheimer's Disease Neuroimaging Initiative study |
| title_full_unstemmed | Identification of prognostic factors to predict cognitive decline of patients with early Alzheimer's disease in the Japanese Alzheimer's Disease Neuroimaging Initiative study |
| title_short | Identification of prognostic factors to predict cognitive decline of patients with early Alzheimer's disease in the Japanese Alzheimer's Disease Neuroimaging Initiative study |
| title_sort | identification of prognostic factors to predict cognitive decline of patients with early alzheimer s disease in the japanese alzheimer s disease neuroimaging initiative study |
| topic | J‐ADNI ADNI Alzheimer's disease assessment scale Mini‐Mental State Examination The clinical dementia rating Biomarker |
| url | https://doi.org/10.1016/j.trci.2019.06.004 |
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