Diagnostic Accuracy of Combined Plasma NfL and Aβ₄₂/Aβ₄₀ Ratio for Differentiating Alzheimer's Disease from Frontotemporal Dementia: A Bivariate Meta-analysis
Neel Parikh1, Anagha Shree3, Mohit Desai2, Suchita Mylavarapu4, Sara S5, Anis Shaikh6, Meet Kachhadia7, Sannidhya Singh8
1Department of Neurology, 2Department of Internal Medicine, Zydus Medical College and Hospital, 3SGT Medical College Hospital and Research Institute, 4Malla Reddy Medical College for Women, 5Fatima Institute of Medical Sciences, 6Zydus Medical College and Hospital India, 7Department of Neurology, Florida Atlantic University Charles E. Schmidt College Of Medicine, Florida, USA, 8RNT Medical College, Udaipur
Objective:
We conducted a systematic review and bivariate meta-analysis to determine the pooled diagnostic accuracy of combined plasma biomarkers (NfL and the A
β42/A
β40 ratio) for the critical differential diagnosis between Alzheimer’s disease (AD) and frontotemporal dementia (FTD).
Background:
Alzheimer’s disease (AD) and frontotemporal dementia (FTD) share early clinical overlap, creating diagnostic uncertainty. Current definitive diagnosis relies on costly, invasive CSF or PET imaging. While individual plasma markers (e.g., Aβ42/Aβ40 ratio or NfL) show promise, their reliability for AD/FTD differentiation is inconsistent. Validating a practical, non-invasive panel requires aggregating data on the combined evaluation of both amyloid pathology and neurodegeneration.
Design/Methods:
We searched for diagnostic accuracy studies that compared AD (biologically confirmed A
β+status) against FTD (FTLD, bivariate FTD). Eligible studies measured plasma NfL and/or the A
β42/A
β40 ratio via high-sensitivity platforms (SIMOA/MS). From 6 reports covering 7 cohorts (over 680 participants), 2×2 contingency data were extracted. Analysis used a hierarchical summary ROC (HSROC) framework via a bivariate random-effects model, with sensitivity analysis probing heterogeneity by FTD subtype.
Results:
The HSROC model converged successfully despite sparse data and zero cell events, demonstrating strong overall discriminative power for the combined plasma biomarker panels. Heterogeneity across the studies was low (I² <50%). The pooled Summary Area Under the Curve (AUC) was 0.942 (95% CI: 0.852-0.981). This strong accuracy was confirmed by the pooled Summary Operating Point (SOP) showing, a sensitivity was 76.4% (95% CI: 59.3%-87.8%) and specificity of 86.1% (95% CI: 67.8%-95.7%). Individual study AUCs for the panels ranged up to 0.94, highlighting the reliability of these biomarker combinations.
Conclusions:
These findings indicate that combined plasma biomarker panels may provide high diagnostic accuracy for the differential diagnosis between AD and FTD. Supported by an AUC exceeding 0.94, the test's reliability demonstrates its utility as a powerful, accessible screening tool in cognitive clinics to effectively triage patients.
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