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CSF Cytokine Panel and Machine Learning for Neurosyphilis Progression Prediction

CSF Cytokine Panel and Machine Learning for Neurosyphilis Progression Prediction
Photo by Cht Gsml / Unsplash
Key Takeaway
Consider that CSF cytokine panels show potential for neurosyphilis risk stratification, but findings require prospective validation before clinical use.

In this observational cohort study, researchers analyzed 48 cytokines and chemokines in the cerebrospinal fluid of 129 patients with syphilis and 15 controls. The cohort included 19 patients with common syphilis, 77 with asymptomatic neurosyphilis, and 33 with symptomatic neurosyphilis. The analysis combined cytokine measurement with machine learning to distinguish syphilis patients from controls and to predict progression from asymptomatic to symptomatic neurosyphilis.

A three-cytokine panel (RANTES, MIP-1β, IL-3) discriminated syphilis patients from controls with an AUC of 0.869 (95% CI: 0.821–0.917). For predicting symptomatic neurosyphilis, IL-2Rα as a standalone biomarker achieved an AUROC of 0.843 (95% CI: 0.784–0.902). Multivariable analysis adjusting for age yielded an AUC of 0.876 (95% CI: 0.827–0.925) for IL-2Rα.

Age-stratified performance for IL-2Rα showed an AUC of 0.939 in patients aged 35–45 years (cut-off 21.82 U/mL; sensitivity 100.0%, specificity 85.7%), an AUC of 0.889 in those aged 45–55 years (cut-off 25.48 U/mL; sensitivity 83.3%, specificity 88.9%), and an AUC of 0.789 in patients older than 55 years (cut-off 24.54 U/mL; sensitivity 73.7%, specificity 84.6%). Combining IL-2Rα and IP-10 improved performance in some age groups, with an AUC of 0.949 for ages 35–45, an AUC of 1.000 for ages 45–55, and an AUC of 0.814 for ages >55.

Safety and tolerability were not reported. Key limitations include the small control group (n=15), the small common syphilis group (n=19), a cross-sectional design without longitudinal follow-up, lack of an external validation cohort, and uncertain generalizability. The practice relevance is that CSF cytokine-guided risk stratification may help distinguish asymptomatic from symptomatic neurosyphilis and predict disease progression, but these biomarkers are not validated for clinical use.

Study Details

Study typeCohort
EvidenceLevel 3
PublishedApr 2026
View Original Abstract ↓
BackgroundSyphilis is a sexually transmitted disease (STD) caused by Treponema pallidum (TP) which could progress to neurosyphilis affecting the nervous system. However, the pathogenesis of neurosyphilis remain unknown. In addition, current diagnosis of neurosyphilis is mainly based on serological tests and cerebrospinal fluid (CSF) analysis, with limitations in terms of sensitivity and specificity.MethodsFrom April 2021 to April 2023, 129 patients with syphilis were enrolled and divided into the non-neurosyphilis group (common syphilis, CS, n=19), asymptomatic neurosyphilis group (AN, n=77), symptomatic neurosyphilis group (NS, n=33) and a control group (n=15). Forty-eight cytokines/chemokines in the CSF samples were measured and analysed in combination with clinical indices. Feature selections were further analysed for the using different machine learning model for the diagnosis and progression predicting of neurosyphilis.ResultsMachine learning-based feature selection identified a three-cytokine panel (RANTES, MIP-1β, and IL-3) that effectively distinguished syphilis patients from controls (AUC = 0.869, 95% CI: 0.821–0.917). For prediction of symptomatic neurosyphilis progression, IL-2Rα emerged as the optimal standalone biomarker, achieving an AUROC of 0.843 (95% CI: 0.784–0.902) for discriminating asymptomatic from symptomatic disease. Multivariable analysis confirmed IL-2Rα retained independent discriminatory power after adjusting for age (multivariable AUC = 0.876, 95% CI: 0.827–0.925). Age-stratified ROC analysis revealed IL-2Rα maintains robust diagnostic utility across all adult age groups, with optimal Youden-derived cut-offs of 21.82 U/mL (sensitivity 100.0%, specificity 85.7%, AUC 0.939) for 35–45 years; 25.48 U/mL (sensitivity 83.3%, specificity 88.9%, AUC 0.889) for 45–55 years; and 24.54 U/mL (sensitivity 73.7%, specificity 84.6%, AUC 0.789) for >55 years. The combination of IL-2Rα and IP-10 significantly improved predictive accuracy within specific age strata, achieving AUCs of 0.949 (35–45 years), 1.000 (45–55 years), and 0.814 (>55 years) when distinguishing symptomatic from asymptomatic neurosyphilis.ConclusionIn conclusion, IL-2Rα and IP-10 represent promising predictive biomarkers for neurosyphilis progression, with their combined application achieving high diagnostic accuracy for distinguishing symptomatic from asymptomatic disease. These findings establish a foundation for CSF cytokine-guided risk stratification in syphilis patients, although prospective validation in larger, age-matched cohorts is warranted to optimize clinical cut-offs and confirm generalizability across diverse populations.
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