Logistic regression identifies improved predictive ability of bvFTD using NfL and atrophy in patients, indicating a need for additional markers.
INTRODUCTION Distinguishing behavioral variant frontotemporal dementia (bvFTD) from primary psychiatric disorders (PPDs) remains challenging due to overlapping clinical presentation. Neurofilament light chain (NfL) is a biomarker of neuronal damage that is elevated in neurodegenerative diseases. This study assessed the effectiveness of NfL and atrophy in differentiating bvFTD from PPDs. METHODS Atrophy maps from frontotemporal regions were generated for 55 patients with autopsy‐confirmed frontotemporal lobar degeneration (bvFTD‐FTLD), 24 mood disorder patients, and eight bvFTD patients later determined to be non‐neurodegenerative (bvFTD‐nonND). Logistic regression was employed to assess the discriminatory abilities of atrophy and NfL levels between bvFTD‐FTLD and PPD (Mood Disorders + bvFTD‐nonND). RESULTS Both atrophy (AUC = 0.87, 95% confidence interval [95% CI: 0.79 to 0.94]) and NfL (AUC = 0.89, 95% CI: 0.81 to 0.96) showed significant predictive ability, which improved when combined (AUC = 0.93, 95% CI: 0.87 to 0.99). Misclassification occurred mostly in low atrophy pathological subtypes and PPD with borderline NfL and frontotemporal volume. CONCLUSION Combining NfL with atrophy enhances differentiation, but additional markers are needed. Highlights Atrophy and NfL had comparable effectiveness in differentiating bvFTD from PPD. Combining NfL and frontotemporal atrophy significantly improved predictive accuracy. NfL, in addition to atrophy, may be beneficial in screening for neurodegeneration in ambiguous cases.
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Coulborn et al. (2025) studied this question.
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