Abstract TP142: Risk Factors and Biomarkers of Ischemic Stroke in Pancreatic Cancer Patients: Insights from a Single-Center Registry

Introduction: Cancer patients face an elevated risk of ischemic stroke, yet predictors remain poorly defined. Cancer-associated stroke (CAS) may arise from mechanisms distinct from traditional stroke risk factors, including cancer-related hypercoagulability related to neutrophil extracellular traps (NETs). The neutrophil-to-lymphocyte ratio (NLR), a potential surrogate of NET activity, has been proposed as a thrombotic biomarker, but its predictive value for ischemic stroke in cancer patients is not established. Methods: We conducted a retrospective cohort study of adults diagnosed with pancreatic cancer at our institution between February 2019 and February 2024 and with at least 1 follow-up visit. Clinical variables, past medical history, laboratory values within one month of cancer diagnosis and prior to treatment, and cancer characteristics were collected. CAS was determined by a vascular neurologist assessment and confirmatory imaging. Stepwise Cox regression was used to identify independent factors associated with stroke within 1 year of cancer diagnosis. Results: Of 551 eligible patients (median age 69, 43% female, 86% White), 23 (4.2%) experienced CAS within a year of cancer diagnosis (median time of 42 days, interquartile range 12-199 days). Of the 23 patients with ischemic stroke, 18 (78%) patients had an embolic stroke of undetermined source, and nine patients had preceding or concomitant venous thromboembolism. Compared to patients without CAS, those with CAS had a greater prevalence of hyperlipidemia (65% vs 38%, p=0.04), metastasis at time of cancer diagnosis (78% vs 35%, p<0.001), and higher median NLR (6.1 vs 3.3 , p<0.001). Multivariable analysis identified the following independent stroke predictors: history of prior stroke (HR 4.9, 95% CI 1.41-17.06; p=0.01), metastatic disease at diagnosis (HR 6.05, 95% CI 2.1-17.3; p<0.001), and NLR (HR 1.11 per unit, 95% CI 1.05-1.17). Conclusion: Pancreatic cancer patients face high early stroke risk, with NLR at diagnosis emerging as an independent predictor of incident stroke. NLR may reflect NET-mediated hypercoagulability, and further mechanistic studies are needed to investigate the utility of NLR in CAS risk stratification and prevention.

Authors

Institutions

Publication Details

Journal
Stroke
Published
2026-01-29
DOI
https://doi.org/10.1161/str.57.suppl_1.tp142
Primary Topic
Inflammatory Biomarkers in Disease Prognosis
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Abstract TP142: Risk Factors and Biomarkers of Ischemic Stroke in Pancreatic Cancer Patients: Insights from a Single-Center Registry

Jennifer J. Majersik, Aaron Shoskes, Conan G. Kinsey, Frederik Denorme et al.
Stroke
Inflammatory Biomarkers in Disease Prognosis
article

Abstract TP142: Risk Factors and Biomarkers of Ischemic Stroke in Pancreatic Cancer Patients: Insights from a Single-Center Registry

Jennifer J. Majersik, Aaron Shoskes, Conan G. Kinsey, Frederik Denorme, Anna L. Parks
article en

Abstract

Introduction: Cancer patients face an elevated risk of ischemic stroke, yet predictors remain poorly defined. Cancer-associated stroke (CAS) may arise from mechanisms distinct from traditional stroke risk factors, including cancer-related hypercoagulability related to neutrophil extracellular traps (NETs). The neutrophil-to-lymphocyte ratio (NLR), a potential surrogate of NET activity, has been proposed as a thrombotic biomarker, but its predictive value for ischemic stroke in cancer patients is not established. Methods: We conducted a retrospective cohort study of adults diagnosed with pancreatic cancer at our institution between February 2019 and February 2024 and with at least 1 follow-up visit. Clinical variables, past medical history, laboratory values within one month of cancer diagnosis and prior to treatment, and cancer characteristics were collected. CAS was determined by a vascular neurologist assessment and confirmatory imaging. Stepwise Cox regression was used to identify independent factors associated with stroke within 1 year of cancer diagnosis. Results: Of 551 eligible patients (median age 69, 43% female, 86% White), 23 (4.2%) experienced CAS within a year of cancer diagnosis (median time of 42 days, interquartile range 12-199 days). Of the 23 patients with ischemic stroke, 18 (78%) patients had an embolic stroke of undetermined source, and nine patients had preceding or concomitant venous thromboembolism. Compared to patients without CAS, those with CAS had a greater prevalence of hyperlipidemia (65% vs 38%, p=0.04), metastasis at time of cancer diagnosis (78% vs 35%, p<0.001), and higher median NLR (6.1 vs 3.3 , p<0.001). Multivariable analysis identified the following independent stroke predictors: history of prior stroke (HR 4.9, 95% CI 1.41-17.06; p=0.01), metastatic disease at diagnosis (HR 6.05, 95% CI 2.1-17.3; p<0.001), and NLR (HR 1.11 per unit, 95% CI 1.05-1.17). Conclusion: Pancreatic cancer patients face high early stroke risk, with NLR at diagnosis emerging as an independent predictor of incident stroke. NLR may reflect NET-mediated hypercoagulability, and further mechanistic studies are needed to investigate the utility of NLR in CAS risk stratification and prevention.

StrokeVol. 57(Suppl_1)
Beth Israel Deaconess Medical Center (US), Harvard University (US), Washington University in St. Louis (US), University of Utah (US)
Good health and well-being
Openalex Percentile: Top 74%
Inflammatory Biomarkers in Disease Prognosis
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.