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Prediction of fast decline in amyloid positive mild cognitive impairment patients using multimodal..
  • 작성일2020-02-07
  • 최종수정일2020-02-10
  • 담당부서연구기획과
  • 연락처043-719-8033
  • 898

NeuroImage: Clinical, 2019. 01, 1-9, DOI: https://doi.org/10.1016/j.nicl.2019.101941


Prediction of fast decline in amyloid positive mild cognitive impairment patients using multimodal biomarkers

Hyemin Jang, Jongyun Park; Sookyoung Woo; Seonwoo Kim; Hee Jin Kim; Duk L. Na; Samuel N. Lockhart; Yeshin Kim; Ko Woon Kim; Soo Hyun Cho; Seung Joo Kim; Joon-Kyung Seong; Sang Won Seo


Abstract

    It may be possible to classify patients with Aβ positive (+) mild cognitive impairment (MCI) into fast and slowdecliners according to their biomarker status. In this study, we aimed to develop a risk prediction model topredict fast decline in the Aβ+ MCI population using multimodal biomarkers. We included 186 Aβ+ MCI patientswho underwent florbetapir PET, brain MRI, cerebrospinal fluid (CSF) analyses, and FDG PET at baseline.We defined conversion to dementia within 3 years (= fast decline) as the outcome. The associations of potentialcovariates (MCI stage, APOE4 genotype, corrected hippocampal volume (HV), FDG PET SUVR, AV45 PET SUVR,CSF Aβ, total tau (t-tau), and phosphorylated tau (p-tau)) with the outcome were tested and nomograms wereconstructed using logistic regression models in the training dataset (n=124, n of fast decliners=52). The modelwas internally validated with the testing dataset (n=62, n of fast decliners=22). The multivariable analysis(including CSF t-tau) showed that MCI stage (late MCI vs. early MCI; OR 15.88, 95% CI 4.59, 54.88), APOE4 (OR5.65, 95% CI 1.52, 20.98), corrected HV*1000 (OR 0.22, 95% CI 0.09, 0.57), FDG SUVR*10 (OR 0.43, 95% CI0.27, 0.71), and loge CSF t-tau (OR 6.20, 95% CI 1.48, 25.96) were associated with being fast decliners. In thesecond model including CSF p-tau instead of t-tau, the above associations remained the same, with a significantassociation between loge CSF p-tau (OR 4.53, 95% CI 1.26, 16.31) and fast decline. The constructed nomogramsshowed excellent predictive performance (90%) on validation with the testing dataset. Among Aβ+ MCI patients,our findings suggested that multimodal AD biomarkers are significantly associated with being classified asfast decliners. A nomogram incorporating these biomarkers might be useful in early treatment decisions orstratified enrollment of this population into clinical trials.



  • 본 연구는 질병관리본부 연구개발과제연구비를 지원받아 수행되었습니다.
  • This research was supported by a fund by Research of Korea Centers for Disease Control and Prevention.


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