Frolich, Lutz ORCID: 0000-0003-1494-0813, Peters, Oliver, Lewczuk, Piotr, Grueber, Oliver, Teipel, Stefan J., Gertz, Hermann J., Jahn, Holger ORCID: 0000-0003-3607-7651, Jessen, Frank, Kurz, Alexander, Luckhaus, Christian, Huell, Michael, Pantel, Johannes, Reischies, Friedel M., Schroeder, Johannes, Wagner, Michael ORCID: 0000-0003-2589-6440, Rienhoff, Otto, Wolf, Stefanie, Bauer, Chris, Schuchhardt, Johannes, Heuser, Isabella, Ruether, Eckart, Henn, Fritz, Maier, Wolfgang, Wiltfang, Jens ORCID: 0000-0003-1492-5330 and Kornhuber, Johannes ORCID: 0000-0002-8096-3987 (2017). Incremental value of biomarker combinations to predict progression of mild cognitive impairment to Alzheimer's dementia. Alzheimers Res. Ther., 9. LONDON: BIOMED CENTRAL LTD. ISSN 1758-9193

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Abstract

Background: The progression of mild cognitive impairment (MCI) to Alzheimer's disease (AD) dementia can be predicted by cognitive, neuroimaging, and cerebrospinal fluid (CSF) markers. Since most biomarkers reveal complementary information, a combination of biomarkers may increase the predictive power. We investigated which combination of the Mini-Mental State Examination (MMSE), Clinical Dementia Rating (CDR)-sum-of-boxes, the word list delayed free recall from the Consortium to Establish a Registry of Dementia (CERAD) test battery, hippocampal volume (HCV), amyloid-beta(1-42) (A beta 42), amyloid-beta(1-40) (A beta 40) levels, the ratio of A beta 42/A beta 40, phosphorylated tau, and total tau (t-Tau) levels in the CSF best predicted a short-term conversion from MCI to AD dementia. Methods: We used 115 complete datasets from MCI patients of the Dementia Competence Network, a German multicenter cohort study with annual follow-up up to 3 years. MCI was broadly defined to include amnestic and nonamnestic syndromes. Variables known to predict progression in MCI patients were selected a priori. Nine individual predictors were compared by receiver operating characteristic (ROC) curve analysis. ROC curves of the five best two-, three-, and four-parameter combinations were analyzed for significant superiority by a bootstrapping wrapper around a support vector machine with linear kernel. The incremental value of combinations was tested for statistical significance by comparing the specificities of the different classifiers at a given sensitivity of 85%. Results: Out of 115 subjects, 28 (24.3%) with MCI progressed to AD dementia within a mean follow-up period of 25.5 months. At baseline, MCI-AD patients were no different from stable MCI in age and gender distribution, but had lower educational attainment. All single biomarkers were significantly different between the two groups at baseline. ROC curves of the individual predictors gave areas under the curve (AUC) between 0.66 and 0.77, and all single predictors were statistically superior to A beta 40. The AUC of the two-parameter combinations ranged from 0.77 to 0.81. The three-parameter combinations ranged from AUC 0.80-0.83, and the four-parameter combination from AUC 0.81-0.82. None of the predictor combinations was significantly superior to the two best single predictors (HCV and t-Tau). When maximizing the AUC differences by fixing sensitivity at 85%, the two-to four-parameter combinations were superior to HCV alone. Conclusion: A combination of two biomarkers of neurodegeneration (e.g., HCV and t-Tau) is not superior over the single parameters in identifying patients with MCI who are most likely to progress to AD dementia, although there is a gradual increase in the statistical measures across increasing biomarker combinations. This may have implications for clinical diagnosis and for selecting subjects for participation in clinical trials.

Item Type: Journal Article
Creators:
CreatorsEmailORCIDORCID Put Code
Frolich, LutzUNSPECIFIEDorcid.org/0000-0003-1494-0813UNSPECIFIED
Peters, OliverUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Lewczuk, PiotrUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Grueber, OliverUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Teipel, Stefan J.UNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Gertz, Hermann J.UNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Jahn, HolgerUNSPECIFIEDorcid.org/0000-0003-3607-7651UNSPECIFIED
Jessen, FrankUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Kurz, AlexanderUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Luckhaus, ChristianUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Huell, MichaelUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Pantel, JohannesUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Reischies, Friedel M.UNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Schroeder, JohannesUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Wagner, MichaelUNSPECIFIEDorcid.org/0000-0003-2589-6440UNSPECIFIED
Rienhoff, OttoUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Wolf, StefanieUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Bauer, ChrisUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Schuchhardt, JohannesUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Heuser, IsabellaUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Ruether, EckartUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Henn, FritzUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Maier, WolfgangUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Wiltfang, JensUNSPECIFIEDorcid.org/0000-0003-1492-5330UNSPECIFIED
Kornhuber, JohannesUNSPECIFIEDorcid.org/0000-0002-8096-3987UNSPECIFIED
URN: urn:nbn:de:hbz:38-214343
DOI: 10.1186/s13195-017-0301-7
Journal or Publication Title: Alzheimers Res. Ther.
Volume: 9
Date: 2017
Publisher: BIOMED CENTRAL LTD
Place of Publication: LONDON
ISSN: 1758-9193
Language: English
Faculty: Faculty of Management, Economy and Social Sciences
Divisions: Unspecified
Subjects: no entry
Uncontrolled Keywords:
KeywordsLanguage
CEREBROSPINAL-FLUID BIOMARKERS; CSF BIOMARKERS; HYPOTHETICAL MODEL; PHOSPHORYLATED-TAU; DYNAMIC BIOMARKERS; CLINICAL-CHANGE; MRI BIOMARKERS; MEMORY DEFICIT; BRAIN ATROPHY; MCI PATIENTSMultiple languages
Clinical Neurology; NeurosciencesMultiple languages
Refereed: Yes
URI: http://kups.ub.uni-koeln.de/id/eprint/21434

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