Development of an algorithm for identifying paraneoplastic ischemic stroke in association with lung, pancreatic, and colorectal cancer

Rebecca Kassubek; Marc-Andre G R Winter; Jens Dreyhaupt; Mona Laible; Jan Kassubek; Albert C Ludolph; Jan Lewerenz

doi:10.1177/17562864241239123

Development of an algorithm for identifying paraneoplastic ischemic stroke in association with lung, pancreatic, and colorectal cancer

Ther Adv Neurol Disord. 2024 Apr 8:17:17562864241239123. doi: 10.1177/17562864241239123. eCollection 2024.

Authors

Rebecca Kassubek¹, Marc-Andre G R Winter², Jens Dreyhaupt³, Mona Laible², Jan Kassubek^{2

4}, Albert C Ludolph^{2

4}, Jan Lewerenz²

Affiliations

¹ Department of Neurology, University of Ulm, Oberer Eselsberg 45, Ulm 89081, Germany.
² Department of Neurology, University of Ulm, Ulm, Germany.
³ Institute of Epidemiology and Medical Biometry, University of Ulm, Ulm, Germany.
⁴ German Center for Neurodegenerative Diseases (DZNE) Ulm, Ulm, Germany.

Abstract

Background: Paraneoplastic ischemic stroke has a poor prognosis. We have recently reported an algorithm based on the number of ischemic territories, C-reactive protein (CRP), lactate dehydrogenase (LDH), and granulocytosis to predict the underlying active cancer in a case-control setting. However, co-occurrence of cancer and stroke might also be merely incidental.

Objective: To detect cancer-associated ischemic stroke in a large, unselected cohort of consecutive stroke patients by detailed analysis of ischemic stroke associated with specific cancer subtypes and comparison to patients with bacterial endocarditis.

Methods: Retrospective single-center cohort study of consecutive 1612 ischemic strokes with magnetic resonance imaging, CRP, LDH, and relative granulocytosis data was performed, including identification of active cancers, history of now inactive cancers, and the diagnosis of endocarditis. The previously developed algorithm to detect paraneoplastic cancer was applied. Tumor types associated with paraneoplastic stroke were used to optimize the diagnostic algorithm.

Results: Ischemic strokes associated with active cancer, but also endocarditis, were associated with more ischemic territories as well as higher CRP and LDH levels. Our previous algorithm identified active cancer-associated strokes with a specificity of 83% and sensitivity of 52%. Ischemic strokes associated with lung, pancreatic, and colorectal (LPC) cancers but not with breast and prostate cancers showed more frequent and prominent characteristics of paraneoplastic stroke. A multiple logistic regression model optimized to identify LPC cancers detected active cancer with a sensitivity of 77.8% and specificity of 81.4%. The positive predictive value (PPV) for all active cancers was 13.1%.

Conclusion: Standard clinical examinations can be employed to identify suspect paraneoplastic stroke with an adequate sensitivity, specificity, and PPV when it is considered that the association of ischemic stroke with breast and prostate cancers in the stroke-prone elderly population might be largely incidental.

Keywords: C-reactive protein; cancer; granulocytes; ischemic stroke; lactate dehydrogenase; magnetic resonance imaging; paraneoplastic; receiver operating characteristics.