成人门诊肿瘤环境中抗肿瘤输注相关反应算法的应用与实施入门指南。
A PRIMER for the Application and Implementation of an Antineoplastic Infusion-Related Reaction Algorithm in Adult Ambulatory Oncology Settings.
作者信息
Corbett Megan A, Nesbitt Marylou
机构信息
Megan A. Corbett.
Marylou Nesbitt.
出版信息
Clin J Oncol Nurs. 2025 May 19;29(3):E79-E87. doi: 10.1188/25.CJON.E79-E87.
BACKGROUND
Although risk factors have been identified and certain treatment plans require premedications to prevent reactions, it remains uncertain which patient will have an antineoplastic infusion-related reaction (IRR), and there is no way to predict the severity of that reaction.
OBJECTIVES
This article highlights details of these risks and emphasizes interventions to identify, prevent, minimize, and manage IRRs in adult ambulatory cancer treatment settings.
METHODS
Using the mnemonic PRIMER (prevention, recognition, intervention, management, evaluation, and recommendation), this article outlines key topics for infusion centers to ensure safe, high-quality care for high-risk patients.
FINDINGS
Using a standardized, evidence-based IRR algorithm based on the PRIMER model can optimize outcomes for patients who experience antineoplastic IRRs.
背景
尽管已经确定了风险因素，并且某些治疗方案需要进行预处理以预防反应，但仍不确定哪些患者会发生抗肿瘤药物输注相关反应（IRR），并且无法预测该反应的严重程度。
目的
本文重点介绍了这些风险的细节，并强调了在成人门诊癌症治疗环境中识别、预防、最小化和管理IRR的干预措施。
方法
本文使用助记符PRIMER（预防、识别、干预、管理、评估和建议），概述了输液中心为高危患者确保安全、高质量护理的关键主题。
研究结果
使用基于PRIMER模型的标准化、循证IRR算法可以优化发生抗肿瘤药物IRR的患者的治疗结局。
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