Kassubek Rebecca, Winter Marc-Andre G R, Dreyhaupt Jens, Laible Mona, Kassubek Jan, Ludolph Albert C, Lewerenz Jan
Department of Neurology, University of Ulm, Oberer Eselsberg 45, Ulm 89081, Germany.
Department of Neurology, University of Ulm, Ulm, Germany.
Ther Adv Neurol Disord. 2024 Apr 8;17:17562864241239123. doi: 10.1177/17562864241239123. eCollection 2024.
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.
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.
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.
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%.
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.
副肿瘤性缺血性卒中预后较差。我们最近报告了一种基于缺血区域数量、C反应蛋白（CRP）、乳酸脱氢酶（LDH）和粒细胞增多来预测病例对照研究中潜在活动性癌症的算法。然而，癌症与卒中的同时发生也可能仅仅是偶然的。
通过对与特定癌症亚型相关的缺血性卒中进行详细分析，并与感染性心内膜炎患者进行比较，在一个大型、未经选择的连续卒中患者队列中检测与癌症相关的缺血性卒中。
对1612例连续缺血性卒中患者进行回顾性单中心队列研究，收集磁共振成像、CRP、LDH和相对粒细胞增多数据，包括识别活动性癌症、既往非活动性癌症病史以及心内膜炎诊断。应用先前开发的检测副肿瘤性癌症的算法。与副肿瘤性卒中相关的肿瘤类型用于优化诊断算法。
与活动性癌症以及感染性心内膜炎相关的缺血性卒中，其缺血区域更多，CRP和LDH水平更高。我们之前的算法识别出与活动性癌症相关的卒中，特异性为83%，敏感性为52%。与肺癌、胰腺癌和结直肠癌（LPC）相关而非与乳腺癌和前列腺癌相关的缺血性卒中，表现出更频繁和显著的副肿瘤性卒中特征。为识别LPC癌症而优化的多元逻辑回归模型检测活动性癌症的敏感性为77.8%，特异性为81.4%。所有活动性癌症的阳性预测值（PPV）为13.1%。
当考虑到在易患卒中的老年人群中缺血性卒中与乳腺癌和前列腺癌的关联可能在很大程度上是偶然的时，标准临床检查可用于以足够的敏感性、特异性和PPV识别可疑的副肿瘤性卒中。
