An integrated CSF-serum biomarker model for predicting clinical progression in Alzheimer's disease.

Background: The early and accurate identification of Alzheimer's disease (AD) remains a significant clinical challenge. Integrating novel peripheral blood-based biomarkers with established cerebrospinal fluid (CSF) measures may offer a promising strategy to enhance diagnostic accuracy and risk stratification. Methods: This study enrolled 91 participants who underwent CSF and serum testing. The cohort was randomly divided into a training set ( Results: The final predictive model incorporated CSF pTau181, A/G ratio, and PLR (using a cut-off ≥113.22). It demonstrated robust discrimination, achieving an AUC of 0.92 in the training set, 0.86 in the testing set, and 0.83 upon external validation. Calibration was excellent (MAE = 0.039). In the testing set, sensitivity was 0.83 and specificity was 0.86. A higher A/G ratio was associated with a reduced risk of AD progression, whereas a higher PLR was associated with an increased risk. Conclusion: The combined CSF-peripheral blood biomarker model demonstrates robust discrimination and calibration for predicting AD progression. By linking central tau pathology with peripheral nutritional and inflammatory status, it may aid clinical risk stratification and guide management strategies focused on nutrition and inflammation. Further large-scale, prospective validation is warranted.