Introduction Several blood‐based biomarkers are associated with neuronal injury, but their utility in interventional clinical trials is unclear. This study retrospectively evaluated the utility of plasma neurofilament light (NfL) and total tau (t‐tau) in an 18‐month trial in mild Alzheimer's disease (AD). Methods Correlation and conditional independence analyses and Gaussian graphical models were used to investigate cross‐sectional and longitudinal relations between NfL, t‐tau, and clinical scales. Results NfL had a stronger association than t‐tau with clinical scales; t‐tau did not hold additional information to that given by NfL ( P > 0.05 at all time points). NfL held independent information about shorter‐term (3‐ to 6‐month) progression beyond patient age and clinical scores. However, no meaningful gain in power was found when adjusting a longitudinal analysis of cognitive scores for baseline NfL. Discussion Plasma NfL is superior to t‐tau in mild AD. The ability of NfL to detect changes before clinical manifestations makes it a promising biomarker of drug response in trials of disease‐modifying drugs.

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Analyzing the progression of Alzheimer's disease (AD) is challenging due to lacking sensitivity in currently available measures. AD stages are typically defined based on cognitive cut‐offs, but this results in heterogeneous patient groups. More accurate modeling of the continuous progression of the disease would enable more accurate patient prognosis. To address these issues, we propose a new multivariate continuous‐time disease progression (MCDP) model. The model is formulated as a nonlinear mixed‐effects model that aligns patients based on their predicted disease progression along a continuous latent disease timeline. The model is evaluated using long‐term follow‐up data from 2152 participants in the Alzheimer's Disease Neuroimaging Initiative. The MCDP model was used to simultaneously model three cognitive scales; the Alzheimer's Disease Assessment Scale‐cognitive subscale, the Mini‐Mental State Examination, and the Clinical Dementia Rating scale—sum of boxes. Compared with univariate modeling and previously proposed multivariate disease progression models, the MCDP model showed superior ability to predict future patient trajectories. Finally, based on the multivariate disease timeline estimated using the MCDP model, the sensitivity of the individual items of the cognitive scales along the different stages of disease was analyzed. The analysis showed that delayed memory recall items had the highest sensitivity in the early stages of disease, whereas language and attention items were sensitive later in disease.