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抗癌药物诱导的动脉损伤:风险分层、预防和治疗。

Anti-cancer drugs-induced arterial injury: risk stratification, prevention, and treatment.

机构信息

Heart and Vascular Centre, Semmelweis University, 68 Városmajor str., Budapest, 1122, Hungary.

出版信息

Med Oncol. 2019 Jul 10;36(8):72. doi: 10.1007/s12032-019-1295-8.

DOI:10.1007/s12032-019-1295-8
PMID:31292791
Abstract

Vascular side effects of standard chemotherapeutic drugs and novel anti-tumor agents complicate treatment cycles, increase non-cancer-related mortality rates, and decrease the quality of life in cancer survivors. Arterial thromboembolic events (ATEE) are associated with most anti-cancer medications. Previous articles have reported a variety of vascular events including ST-segment elevation myocardial infarction as one of the most severe acute arterial attacks. Cardiologists should play an early role in identifying those at high risk for vascular complications and tailor anti-thrombotic therapies in keeping with thromboembolic and bleeding risks. Early preventive steps and individualized chemotherapy may decrease anti-tumor treatment-related vascular events. Here, we aim to provide an extensive review of anti-tumor drug-induced vascular injury (DIVI), pathomechanisms, and risk stratification underlining arterial events. We give a summary of clinical manifestations, treatment options, and possible preventive measures of DIVI. Additionally, the treatment of modifiable risk factors and tailored choice of chemotherapy must be considered in all oncology patients to prevent DIVI. We propose a complex tool for ATEE risk stratification which is warranted for early prediction leading to less frequent complications in cancer patients.

摘要

标准化疗药物和新型抗肿瘤药物的血管副作用使治疗周期复杂化,增加了非癌症相关死亡率,并降低了癌症幸存者的生活质量。动脉血栓栓塞事件(ATEE)与大多数抗癌药物有关。先前的文章报道了多种血管事件,包括 ST 段抬高型心肌梗死,这是最严重的急性动脉攻击之一。心脏病专家应在早期识别出那些有发生血管并发症高风险的患者,并根据血栓栓塞和出血风险制定抗血栓治疗方案。早期预防措施和个体化化疗可能会降低抗肿瘤治疗相关的血管事件。在这里,我们旨在提供广泛的抗肿瘤药物引起的血管损伤(DIVI)、发病机制和动脉事件的风险分层综述。我们总结了 DIVI 的临床表现、治疗选择和可能的预防措施。此外,在所有肿瘤患者中,必须考虑可改变的危险因素的治疗和化疗的个体化选择,以预防 DIVI。我们提出了一种用于 ATEE 风险分层的复杂工具,这对于早期预测是必要的,可减少癌症患者并发症的发生频率。

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