Test-retest variability of plasma biomarkers in Alzheimer's disease and its effects on clinical prediction models

被引:36
作者
Cullen, Nicholas C. [1 ]
Janelidze, Shorena [1 ]
Mattsson-Carlgren, Niklas [1 ,2 ,3 ]
Palmqvist, Sebastian [1 ,4 ]
Bittner, Tobias [5 ]
Suridjan, Ivonne [6 ]
Jethwa, Alexander [7 ]
Kollmorgen, Gwendlyn [7 ]
Brum, Wagner S. [8 ]
Zetterberg, Henrik [9 ,10 ,11 ,12 ,13 ]
Blennow, Kaj [9 ,10 ]
Stomrud, Erik [1 ,4 ]
Hansson, Oskar [1 ,4 ]
机构
[1] Lund Univ, Fac Med, Dept Clin Sci Malmo, Clin Memory Res Unit, Lund, Sweden
[2] Skane Univ Hosp, Dept Neurol, Lund, Sweden
[3] Lund Univ, Wallenberg Ctr Mol Med, Lund, Sweden
[4] Skane Univ Hosp, Memory Clin, SE-20502 Malmo, Sweden
[5] F Hoffmann La Roche Ltd, Basel, Switzerland
[6] Roche Diagnost Int Ltd, Rotkreuz, Switzerland
[7] Roche Diagnost GmbH, Penzberg, Germany
[8] Univ Fed Rio Grande do Sul UFRGS, Grad Program Biol Sci Biochem, Porto Alegre, RS, Brazil
[9] Univ Gothenburg, Sahlgrenska Acad, Dept Psychiat & Neurochem, Molndal, Sweden
[10] Sahlgrens Univ Hosp, Clin Neurochem Lab, Molndal, Sweden
[11] UCL Inst Neurol, Dept Neurodegenerat Dis, Queen Sq, London, England
[12] UCL, UK Dementia Res Inst, London, England
[13] Hong Kong Ctr 27 Neurodegenerat Dis, Hong Kong, Peoples R China
基金
欧洲研究理事会; 美国国家卫生研究院; 瑞典研究理事会;
关键词
diagnosis; gray zones; plasma biomarkers; random error; test-retest variability; GRAY ZONE; DIAGNOSIS;
D O I
10.1002/alz.12706
中图分类号
R74 [神经病学与精神病学];
学科分类号
摘要
INTRODUCTION The effect of random error on the performance of blood-based biomarkers for Alzheimer's disease (AD) must be determined before clinical implementation. METHODS We measured test-retest variability of plasma amyloid beta (A beta)42/A beta 40, neurofilament light (NfL), glial fibrillary acidic protein (GFAP), and phosphorylated tau (p-tau)217 and simulated effects of this variability on biomarker performance when predicting either cerebrospinal fluid (CSF) A beta status or conversion to AD dementia in 399 non-demented participants with cognitive symptoms. RESULTS Clinical performance was highest when combining all biomarkers. Among single-biomarkers, p-tau217 performed best. Test-retest variability ranged from 4.1% (A beta 42/A beta 40) to 25% (GFAP). This variability reduced the performance of the biomarkers (approximate to Delta AUC [area under the curve] -1% to -4%) with the least effects on models with p-tau217. The percent of individuals with unstable predicted outcomes was lowest for the multi-biomarker combination (14%). DISCUSSION Clinical prediction models combining plasma biomarkers-particularly p-tau217-exhibit high performance and are less effected by random error. Individuals with unstable predicted outcomes ("gray zone") should be recommended for further tests.
引用
收藏
页码:797 / 806
页数:10
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