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Incremental value of biomarker combinations to predict progression of mild cognitive impairment to Alzheimer's dementia.
Alzheimers Res Ther 2017; 9(1):84AR

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-beta1-42 (Aβ42), amyloid-beta1-40 (Aβ40) levels, the ratio of Aβ42/Aβ40, 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 Aβ40. 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.

Authors+Show Affiliations

Department of Geriatric Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Zentralinstitut für Seelische Gesundheit, Quadrat J5, D-68159, Mannheim, Germany. lutz.froelich@zi-mannheim.de.Department of Psychiatry and Psychotherapy, Campus Benjamin Franklin, Charité, Berlin, Germany.Department of Psychiatry and Psychotherapy, Friedrich-Alexander-University of Erlangen-Nuremberg, Nuremberg, Germany. Department of Neurodegeneration Diagnostics, Medical University of Bialystok, Bialystok, Poland.Department of Psychiatry and Psychotherapy, University Medical Center Göttingen, and German Center for Neurodegenerative Diseases (DZNE), Research Site Göttingen, Göttingen, Germany.German Center for Neurodegenerative Diseases (DZNE), Rostock, Germany. Department of Psychosomatic Medicine, University Medicine Rostock, Rostock, Germany. Department of Psychiatry and Psychotherapy, Ludwig-Maximilian-University of Munich, Munich, Germany.Department of Psychiatry, University of Leipzig, Leipzig, Germany.Department of Psychiatry and Psychotherapy, University Medical Center Hamburg, Hamburg, Germany.Department of Psychiatry and Psychotherapy, University of Bonn, Bonn, Germany. German Center for Neurodegenerative Diseases (DZNE), Cologne/Bonn, Germany. Department of Psychiatry and Psychotherapy, Medical Faculty University of Cologne, Cologne, Germany.Department of Psychiatry and Psychotherapy, Technical University of Munich, Munich, Germany.Department of Psychiatry and Psychotherapy, University of Düsseldorf, Düsseldorf, Germany.Center for Psychiatry, Clinic for Geriatric Psychiatry and Psychotherapy Emmendingen and Department of Psychiatry and Psychotherapy, University of Freiburg, Freiburg, Germany.Institute of General Medicine University of Frankfurt, Frankfurt am Main, Germany.Department of Psychiatry and Psychotherapy, Campus Benjamin Franklin, Charité, Berlin, Germany.Section for Geriatric Psychiatry Research, Department for Psychiatry, University of Heidelberg, Heidelberg, Germany.Department of Psychiatry and Psychotherapy, University of Bonn, Bonn, Germany.Department of Medical Informatics, University of Göttingen, Göttingen, Germany.Department of Psychiatry and Psychotherapy, University Medical Center Göttingen, and German Center for Neurodegenerative Diseases (DZNE), Research Site Göttingen, Göttingen, Germany.MicroDiscovery GmbH, Berlin, Germany.MicroDiscovery GmbH, Berlin, Germany.Department of Psychiatry and Psychotherapy, Campus Benjamin Franklin, Charité, Berlin, Germany.Department of Psychiatry and Psychotherapy, University Medical Center Göttingen, and German Center for Neurodegenerative Diseases (DZNE), Research Site Göttingen, Göttingen, Germany.Department of Geriatric Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Zentralinstitut für Seelische Gesundheit, Quadrat J5, D-68159, Mannheim, Germany.Department of Psychiatry and Psychotherapy, University of Bonn, Bonn, Germany.Department of Psychiatry and Psychotherapy, University Medical Center Göttingen, and German Center for Neurodegenerative Diseases (DZNE), Research Site Göttingen, Göttingen, Germany.Department of Psychiatry and Psychotherapy, Friedrich-Alexander-University of Erlangen-Nuremberg, Nuremberg, Germany. Department of Neurodegeneration Diagnostics, Medical University of Bialystok, Bialystok, Poland.

Pub Type(s)

Journal Article
Multicenter Study

Language

eng

PubMed ID

29017593

Citation

Frölich, Lutz, et al. "Incremental Value of Biomarker Combinations to Predict Progression of Mild Cognitive Impairment to Alzheimer's Dementia." Alzheimer's Research & Therapy, vol. 9, no. 1, 2017, p. 84.
Frölich L, Peters O, Lewczuk P, et al. Incremental value of biomarker combinations to predict progression of mild cognitive impairment to Alzheimer's dementia. Alzheimers Res Ther. 2017;9(1):84.
Frölich, L., Peters, O., Lewczuk, P., Gruber, O., Teipel, S. J., Gertz, H. J., ... Kornhuber, J. (2017). Incremental value of biomarker combinations to predict progression of mild cognitive impairment to Alzheimer's dementia. Alzheimer's Research & Therapy, 9(1), p. 84. doi:10.1186/s13195-017-0301-7.
Frölich L, et al. Incremental Value of Biomarker Combinations to Predict Progression of Mild Cognitive Impairment to Alzheimer's Dementia. Alzheimers Res Ther. 2017 Oct 10;9(1):84. PubMed PMID: 29017593.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Incremental value of biomarker combinations to predict progression of mild cognitive impairment to Alzheimer's dementia. AU - Frölich,Lutz, AU - Peters,Oliver, AU - Lewczuk,Piotr, AU - Gruber,Oliver, AU - Teipel,Stefan J, AU - Gertz,Hermann J, AU - Jahn,Holger, AU - Jessen,Frank, AU - Kurz,Alexander, AU - Luckhaus,Christian, AU - Hüll,Michael, AU - Pantel,Johannes, AU - Reischies,Friedel M, AU - Schröder,Johannes, AU - Wagner,Michael, AU - Rienhoff,Otto, AU - Wolf,Stefanie, AU - Bauer,Chris, AU - Schuchhardt,Johannes, AU - Heuser,Isabella, AU - Rüther,Eckart, AU - Henn,Fritz, AU - Maier,Wolfgang, AU - Wiltfang,Jens, AU - Kornhuber,Johannes, Y1 - 2017/10/10/ PY - 2016/09/07/received PY - 2017/08/30/accepted PY - 2017/10/12/entrez PY - 2017/10/12/pubmed PY - 2018/6/21/medline KW - Alzheimer’s dementia KW - Amyloid-beta 42 KW - Biomarkers KW - Hippocampal volume KW - Mild cognitive impairment KW - Phospho-tau KW - Prediction KW - Tau SP - 84 EP - 84 JF - Alzheimer's research & therapy JO - Alzheimers Res Ther VL - 9 IS - 1 N2 - 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-beta1-42 (Aβ42), amyloid-beta1-40 (Aβ40) levels, the ratio of Aβ42/Aβ40, 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 Aβ40. 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. SN - 1758-9193 UR - https://www.unboundmedicine.com/medline/citation/29017593/Incremental_value_of_biomarker_combinations_to_predict_progression_of_mild_cognitive_impairment_to_Alzheimer's_dementia_ L2 - https://alzres.biomedcentral.com/articles/10.1186/s13195-017-0301-7 DB - PRIME DP - Unbound Medicine ER -