Nicolás Tentoni, Miriam Hwang, Gabriela Villanueva, Ryan Combs, Jennifer Lowe, Laura B. Ramsey, Zachary L. Taylor, Thais Murciano Carrillo, María Dolores Aumente, Teresa López-Viñau López, Carmelo Rizzari, Scott C. Howard
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Early levels were tagged and MTX elimination half-life (t<sub>½</sub>) were calculated from combinations of two of three different early time periods. Receiver operating characteristic (ROC) curves were synthesized for each elimination t<sub>½</sub> (biomarker) with respect to AKI and delayed methotrexate elimination (DME); the biomarker with the highest area under the ROC curve (AUC) was tested in a multiple variable logistic regression model.</p>\n </section>\n \n <section>\n \n <h3> Results</h3>\n \n <p>Data from 169 patients who received a total of 556 courses of HDMTX were analyzed. ROC analysis revealed MTX elimination t<sub>½</sub> calculated from the second and third time periods had the highest AUC for AKI at 0.62 (interquartile range [IQR] 0.56–0.69) and DME at 0.86 (IQR 0.73–1.00). 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引用次数: 0
摘要
导言 大剂量甲氨蝶呤(HDMTX)的使用可能会因急性肾损伤(AKI)的发生而受到限制。要防止进一步的肾损伤和不可逆的毒性,早期发现 AKI 至关重要。本研究旨在确定 MTX 的早期消除模式是否可作为 HDMTX 治疗中 AKI 的生物标记物。 方法 这项回顾性队列研究包括两个在 MTX 输注结束后 16 小时内采集 MTX 水平≥2 的研究机构。对早期水平进行标记,并根据三个不同早期时间段中两个时间段的组合计算 MTX 消除半衰期 (t½)。为每种消除半衰期(t½)(生物标记物)合成与 AKI 和甲氨蝶呤延迟消除(DME)相关的接收者操作特征(ROC)曲线;在多变量逻辑回归模型中测试 ROC 曲线下面积(AUC)最大的生物标记物。 结果 分析了169名患者的数据,这些患者共接受了556个疗程的HDMTX治疗。ROC分析显示,从第二和第三个时间段计算的MTX消除t/½对AKI的AUC最高,为0.62(四分位距[IQR] 0.56-0.69),对DME的AUC最高,为0.86(IQR 0.73-1.00)。在对年龄、性别、剂量(毫克/平方米)、输注时间、HDMTX疗程和基线肾小球滤过率进行调整后,其对AKI的影响仍然显著,OR值为1.29,95%置信区间为1.03-1.65。 结论 输注结束后 16 小时内测量的早期 MTX 清除率 t½ 与 AKI 的发生显著相关,它是一种早期清除生物标志物,可识别出哪些患者可从增加水合、加强白消安抢救和服用葡萄糖苷酶中获益。
Early therapeutic drug monitoring of methotrexate and its association with acute kidney injury: A retrospective cohort study
Introduction
High-dose methotrexate (HDMTX) use can be limited by the development of acute kidney injury (AKI). Early AKI detection is paramount to prevent further renal injury and irreversible toxicities. This study sought to determine whether early elimination patterns of MTX would be useful as a biomarker of AKI in HDMTX treatment.
Methods
This retrospective cohort study included two sites that collected ≥2 MTX levels within 16 h from completion of MTX infusion. Early levels were tagged and MTX elimination half-life (t½) were calculated from combinations of two of three different early time periods. Receiver operating characteristic (ROC) curves were synthesized for each elimination t½ (biomarker) with respect to AKI and delayed methotrexate elimination (DME); the biomarker with the highest area under the ROC curve (AUC) was tested in a multiple variable logistic regression model.
Results
Data from 169 patients who received a total of 556 courses of HDMTX were analyzed. ROC analysis revealed MTX elimination t½ calculated from the second and third time periods had the highest AUC for AKI at 0.62 (interquartile range [IQR] 0.56–0.69) and DME at 0.86 (IQR 0.73–1.00). After adjusting for age, sex, dose (mg/m2), infusion duration, HDMTX course, and baseline estimated glomerular filtration rate, it remained significant for AKI with an OR of 1.29 and 95% confidence interval of 1.03–1.65.
Conclusion
Early MTX elimination t½ measured within 16 h of infusion completion was significantly associated with the development of AKI and serves as an early clearance biomarker that may identify patients who benefit from increased hydration, augmented leucovorin rescue, and glucarpidase administration.
期刊介绍:
Cancer Medicine is a peer-reviewed, open access, interdisciplinary journal providing rapid publication of research from global biomedical researchers across the cancer sciences. The journal will consider submissions from all oncologic specialties, including, but not limited to, the following areas:
Clinical Cancer Research
Translational research ∙ clinical trials ∙ chemotherapy ∙ radiation therapy ∙ surgical therapy ∙ clinical observations ∙ clinical guidelines ∙ genetic consultation ∙ ethical considerations
Cancer Biology:
Molecular biology ∙ cellular biology ∙ molecular genetics ∙ genomics ∙ immunology ∙ epigenetics ∙ metabolic studies ∙ proteomics ∙ cytopathology ∙ carcinogenesis ∙ drug discovery and delivery.
Cancer Prevention:
Behavioral science ∙ psychosocial studies ∙ screening ∙ nutrition ∙ epidemiology and prevention ∙ community outreach.
Bioinformatics:
Gene expressions profiles ∙ gene regulation networks ∙ genome bioinformatics ∙ pathwayanalysis ∙ prognostic biomarkers.
Cancer Medicine publishes original research articles, systematic reviews, meta-analyses, and research methods papers, along with invited editorials and commentaries. Original research papers must report well-conducted research with conclusions supported by the data presented in the paper.