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Comparison of CSF markers and semi-quantitative amyloid PET in Alzheimer's disease diagnosis and in cognitive impairment prognosis using the ADNI-2 database.

Abstract

BACKGROUND

The relative performance of semi-quantitative amyloid positron emission tomography (PET) and cerebrospinal fluid (CSF) markers in diagnosing Alzheimer's disease (AD) and predicting the cognitive evolution of patients with mild cognitive impairment (MCI) is still debated.

METHODS

Subjects from the Alzheimer's Disease Neuroimaging Initiative 2 with complete baseline cognitive assessment (Mini Mental State Examination, Clinical Dementia Rating [CDR] and Alzheimer's Disease Assessment Scale-Cognitive Subscale [ADAS-cog] scores), CSF collection (amyloid-β1-42 [Aβ], tau and phosphorylated tau) and 18F-florbetapir scans were included in our cross-sectional cohort. Among these, patients with MCI or substantial memory complaints constituted our longitudinal cohort and were followed for 30 ± 16 months. PET amyloid deposition was quantified using relative retention indices (standardised uptake value ratio [SUVr]) with respect to pontine, cerebellar and composite reference regions. Diagnostic and prognostic performance based on PET and CSF was evaluated using ROC analysis, multivariate linear regression and survival analysis with the Cox proportional hazards model.

RESULTS

The cross-sectional study included 677 participants and revealed that pontine and composite SUVr values were better classifiers (AUC 0.88, diagnostic accuracy 85%) than CSF markers (AUC 0.83 and 0.85, accuracy 80% and 75%, for Aβ and tau, respectively). SUVr was a strong independent determinant of cognition in multivariate regression, whereas Aβ was not; tau was also a determinant, but to a lesser degree. Among the 396 patients from the longitudinal study, 82 (21%) converted to AD within 22 ± 13 months. Optimal SUVr thresholds to differentiate AD converters were quite similar to those of the cross-sectional study. Composite SUVr was the best AD classifier (AUC 0.86, sensitivity 88%, specificity 81%). In multivariate regression, baseline cognition (CDR and ADAS-cog) was the main predictor of subsequent cognitive decline. Pontine and composite SUVr were moderate but independent predictors of final status and CDR/ADAS-cog progression rate, whereas baseline CSF markers had a marginal influence. The adjusted HRs for AD conversion were 3.8 (p = 0.01) for PET profile, 1.2 (p = ns) for Aβ profile and 1.8 (p = 0.03) for tau profile.

CONCLUSIONS

Semi-quantitative amyloid PET appears more powerful than CSF markers for AD grading and MCI prognosis in terms of cognitive decline and AD conversion.

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  • Authors+Show Affiliations

    ,

    Toulouse NeuroImaging Centre (ToNIC), Université de Toulouse, Inserm/UPS, Toulouse, France. faybenb@hotmail.com. Nuclear Medicine Department, Purpan University Hospital, Toulouse, France. faybenb@hotmail.com. Nuclear Medicine Department, Lapeyronie University Hospital, Montpellier, France. faybenb@hotmail.com.

    ,

    Nuclear Medicine Department, Lapeyronie University Hospital, Montpellier, France.

    ,

    Toulouse NeuroImaging Centre (ToNIC), Université de Toulouse, Inserm/UPS, Toulouse, France. Nuclear Medicine Department, Purpan University Hospital, Toulouse, France.

    Source

    Alzheimer's research & therapy 9:1 2017 Apr 26 pg 32

    MeSH

    Aged
    Aged, 80 and over
    Alzheimer Disease
    Amyloid beta-Peptides
    Biomarkers
    Cognition Disorders
    Comorbidity
    Databases, Factual
    Diagnosis, Differential
    Female
    France
    Humans
    Male
    Middle Aged
    Peptide Fragments
    Positron-Emission Tomography
    Prevalence
    Prognosis
    Radiopharmaceuticals
    Reproducibility of Results
    Risk Assessment
    Sensitivity and Specificity
    tau Proteins

    Pub Type(s)

    Comparative Study
    Evaluation Studies
    Journal Article

    Language

    eng

    PubMed ID

    28441967

    Citation

    Ben Bouallègue, Fayçal, et al. "Comparison of CSF Markers and Semi-quantitative Amyloid PET in Alzheimer's Disease Diagnosis and in Cognitive Impairment Prognosis Using the ADNI-2 Database." Alzheimer's Research & Therapy, vol. 9, no. 1, 2017, p. 32.
    Ben Bouallègue F, Mariano-Goulart D, Payoux P, et al. Comparison of CSF markers and semi-quantitative amyloid PET in Alzheimer's disease diagnosis and in cognitive impairment prognosis using the ADNI-2 database. Alzheimers Res Ther. 2017;9(1):32.
    Ben Bouallègue, F., Mariano-Goulart, D., & Payoux, P. (2017). Comparison of CSF markers and semi-quantitative amyloid PET in Alzheimer's disease diagnosis and in cognitive impairment prognosis using the ADNI-2 database. Alzheimer's Research & Therapy, 9(1), p. 32. doi:10.1186/s13195-017-0260-z.
    Ben Bouallègue F, et al. Comparison of CSF Markers and Semi-quantitative Amyloid PET in Alzheimer's Disease Diagnosis and in Cognitive Impairment Prognosis Using the ADNI-2 Database. Alzheimers Res Ther. 2017 Apr 26;9(1):32. PubMed PMID: 28441967.
    * Article titles in AMA citation format should be in sentence-case
    TY - JOUR T1 - Comparison of CSF markers and semi-quantitative amyloid PET in Alzheimer's disease diagnosis and in cognitive impairment prognosis using the ADNI-2 database. AU - Ben Bouallègue,Fayçal, AU - Mariano-Goulart,Denis, AU - Payoux,Pierre, AU - ,, Y1 - 2017/04/26/ PY - 2017/02/10/received PY - 2017/03/24/accepted PY - 2017/4/27/entrez PY - 2017/4/27/pubmed PY - 2018/1/30/medline KW - ADNI KW - Alzheimer’s disease KW - Amyloid PET KW - CSF markers KW - MCI SP - 32 EP - 32 JF - Alzheimer's research & therapy JO - Alzheimers Res Ther VL - 9 IS - 1 N2 - BACKGROUND: The relative performance of semi-quantitative amyloid positron emission tomography (PET) and cerebrospinal fluid (CSF) markers in diagnosing Alzheimer's disease (AD) and predicting the cognitive evolution of patients with mild cognitive impairment (MCI) is still debated. METHODS: Subjects from the Alzheimer's Disease Neuroimaging Initiative 2 with complete baseline cognitive assessment (Mini Mental State Examination, Clinical Dementia Rating [CDR] and Alzheimer's Disease Assessment Scale-Cognitive Subscale [ADAS-cog] scores), CSF collection (amyloid-β1-42 [Aβ], tau and phosphorylated tau) and 18F-florbetapir scans were included in our cross-sectional cohort. Among these, patients with MCI or substantial memory complaints constituted our longitudinal cohort and were followed for 30 ± 16 months. PET amyloid deposition was quantified using relative retention indices (standardised uptake value ratio [SUVr]) with respect to pontine, cerebellar and composite reference regions. Diagnostic and prognostic performance based on PET and CSF was evaluated using ROC analysis, multivariate linear regression and survival analysis with the Cox proportional hazards model. RESULTS: The cross-sectional study included 677 participants and revealed that pontine and composite SUVr values were better classifiers (AUC 0.88, diagnostic accuracy 85%) than CSF markers (AUC 0.83 and 0.85, accuracy 80% and 75%, for Aβ and tau, respectively). SUVr was a strong independent determinant of cognition in multivariate regression, whereas Aβ was not; tau was also a determinant, but to a lesser degree. Among the 396 patients from the longitudinal study, 82 (21%) converted to AD within 22 ± 13 months. Optimal SUVr thresholds to differentiate AD converters were quite similar to those of the cross-sectional study. Composite SUVr was the best AD classifier (AUC 0.86, sensitivity 88%, specificity 81%). In multivariate regression, baseline cognition (CDR and ADAS-cog) was the main predictor of subsequent cognitive decline. Pontine and composite SUVr were moderate but independent predictors of final status and CDR/ADAS-cog progression rate, whereas baseline CSF markers had a marginal influence. The adjusted HRs for AD conversion were 3.8 (p = 0.01) for PET profile, 1.2 (p = ns) for Aβ profile and 1.8 (p = 0.03) for tau profile. CONCLUSIONS: Semi-quantitative amyloid PET appears more powerful than CSF markers for AD grading and MCI prognosis in terms of cognitive decline and AD conversion. SN - 1758-9193 UR - https://www.unboundmedicine.com/medline/citation/28441967/Comparison_of_CSF_markers_and_semi_quantitative_amyloid_PET_in_Alzheimer's_disease_diagnosis_and_in_cognitive_impairment_prognosis_using_the_ADNI_2_database_ L2 - https://alzres.biomedcentral.com/articles/10.1186/s13195-017-0260-z DB - PRIME DP - Unbound Medicine ER -