Abstract Number: Esoc2026a408 Population-Based Study of Blood Biomarkers in the Prediction of Long-Term Recurrent Stroke

Background and aims Some blood biomarkers have been shown to predict early recurrent stroke but long-term predictive value is uncertain, particularly if samples are taken during the acute phase. We assessed whether blood biomarkers improve 10-year risk prediction in intensively treated patients after TIA/stroke. Methods We studied 12 blood biomarkers related to inflammation, neuronal injury, and thrombosis after TIA/stroke in a population-based study (OXVASC; 2002-2011) with follow-up until 2025. We used cox and negative binomial regressions to assess associations between each log-transformed biomarker (per SD increase) and recurrent stroke (first event and total number), adjusted for age, sex, and vascular risk factors. Results Among 1,292 patients (mean age 73.1 ± 13.2 years; 47.8% male), 365 recurrent strokes occurred in 280 patients over 11,336 patient-years. Several inflammatory biomarkers were associated with 10-year risk of recurrence (adjusted IRR: IL6 = 1.21, 95%CI 1.04-1.42; C-reactive protein = 1.20, 1.05–1.37; TNF receptor-1 = 1.24, 1.05-1.46). Moreover, clustering of elevated inflammatory markers was associated with higher recurrence risk (HR per marker in top quartile = 1.21, 1.08–1.36; P < 0.001), higher burden of recurrence (IRR = 1.31, 1.15-1.50, P < 0.001), which also remained up to 10 years (90 days: 1.24; 90 days–1 year: 1.24; 1–5 years: 1.22; 5–10 years: 1.34). Associations were similar in TIA and minor stroke and across aetiological subtypes. Conclusions In this large population-based cohort, individual inflammatory biomarkers showed some value for long-term prediction of recurrent stroke. However, clustering of elevated inflammatory markers was more strongly associated with long-term recurrence, supporting ongoing trials of anti-inflammatory strategies for secondary prevention. Conflict of interest All authors have nothing to disclose.