Comparative Prognostic Performance of Hippocampal Volume and Plasma Biomarkers in Amyloid-Negative Subjective...

Subjective cognitive decline (SCD) may precede mild cognitive impairment (MCI) and dementia. However, the prognosis of patients with amyloid-negative (A-) SCD remains unclear. We investigated whether baseline plasma and imaging biomarkers predict four-year clinical progression in A-SCD.

Sixty-five individuals with A-SCD were followed for four years. Baseline plasma biomarkers-phosphorylated tau 181 (pTau181), glial fibrillary acidic protein, neurofilament light chain (NfL), and pTau181/Aβ42 ratio-and MRI markers (hippocampal volume and white matter hyperintensity [WMH] grade) were assessed. Outcomes included MCI conversion and cognitive progression defined as ≥1-point (Prog-1) or ≥2-point (Prog-2) decline in Korean Mini-Mental State Examination. Predictive performance was evaluated using multivariable logistic regression and bootstrap-validated receiver operating characteristic analyses.

Fourteen participants (21.5%) converted to MCI, and 24 (36.9%) were classified as Prog-1. Plasma biomarkers did not show consistent predictive performance across predefined endpoints (all p>0.05), although NfL demonstrated modest discrimination for MCI conversion (area under the curve [AUC] 0.686, p=0.008). Hippocampal volume demonstrated significant discriminative performance for MCI conversion (AUC 0.765, p=0.016) and Prog-1 (AUC 0.933, p<0.001). For Prog-2, hippocampal volume showed high discrimination (AUC 0.952, p<0.001). WMH grade also demonstrated significant discrimination for MCI conversion (AUC 0.835, p<0.001) and Prog-1 (AUC 0.857, p<0.001). Bootstrap analyses (1,000 iterations) tended to show higher AUC estimates for imaging markers compared with plasma biomarkers.

In this A-SCD cohort, hippocampal atrophy demonstrated more consistent prognostic performance than Alzheimer's disease-focused plasma biomarkers for predicting four-year conversion to MCI and cognitive decline, suggesting a potential role for MRI-based neurodegeneration markers in clinical risk stratification.