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

IF 4.7 2区 医学 Q1 CLINICAL NEUROLOGY
Therapeutic Advances in Neurological Disorders Pub Date : 2024-04-08 eCollection Date: 2024-01-01 DOI:10.1177/17562864241239123
Rebecca Kassubek, Marc-Andre G R Winter, Jens Dreyhaupt, Mona Laible, Jan Kassubek, Albert C Ludolph, Jan Lewerenz
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引用次数: 0

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.

开发一种算法,用于识别与肺癌、胰腺癌和结直肠癌相关的副肿瘤性缺血性中风。
背景:副肿瘤性缺血性卒中预后较差。我们最近报道了一种基于缺血区数量、C 反应蛋白(CRP)、乳酸脱氢酶(LDH)和粒细胞减少的算法,可在病例对照中预测潜在的活动性癌症。然而,癌症与中风同时发生也可能只是偶然现象:目的:通过详细分析与特定癌症亚型相关的缺血性卒中,并与细菌性心内膜炎患者进行比较,在一个大型、未选择的连续卒中患者队列中检测癌症相关的缺血性卒中:方法: 对连续 1612 例缺血性脑卒中患者进行了回顾性单中心队列研究,这些患者均有磁共振成像、CRP、LDH 和相对粒细胞增多数据,包括活动性癌症、目前非活动性癌症病史和心内膜炎诊断。采用了之前开发的副肿瘤性癌症检测算法。与副肿瘤性中风相关的肿瘤类型被用于优化诊断算法:结果:与活动性癌症和心内膜炎相关的缺血性脑卒中缺血区域更多,CRP 和 LDH 水平更高。我们之前的算法能识别出活动性癌症相关脑卒中,特异性为 83%,灵敏度为 52%。与肺癌、胰腺癌和结肠直肠癌(LPC)相关的缺血性脑卒中,而与乳腺癌和前列腺癌无关的缺血性脑卒中显示出更频繁和更突出的副肿瘤性脑卒中特征。为识别 LPC 癌症而优化的多元逻辑回归模型检测到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%:结论:如果考虑到易发中风的老年人群中缺血性中风与乳腺癌和前列腺癌的关联可能主要是偶然的,那么可以采用标准的临床检查来识别可疑的副肿瘤性中风,并具有足够的灵敏度、特异性和 PPV。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
8.30
自引率
1.70%
发文量
62
审稿时长
15 weeks
期刊介绍: Therapeutic Advances in Neurological Disorders is a peer-reviewed, open access journal delivering the highest quality articles, reviews, and scholarly comment on pioneering efforts and innovative studies across all areas of neurology. The journal has a strong clinical and pharmacological focus and is aimed at clinicians and researchers in neurology, providing a forum in print and online for publishing the highest quality articles in this area.
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