Predictive modeling for improved anemia management in dialysis patients.
Predictive modeling for improved anemia management in dialysis patients.
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DOI：
10.1097/mnh.0b013e32834bba4e
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发表时间：
2011-11
影响因子：
3.2
通讯作者：
Gaweda AE
中科院分区：
文献类型：
--
作者：
Brier ME;Gaweda AE
本综述将探讨进行血红蛋白对红细胞生成刺激剂（ESA）反应的预测建模所需的基本假设，并总结该领域的现有文献，以便从业者可以将这些工具作为改善贫血管理过程的一部分。在过去的一年中，一些出版物已经证明了该领域的一些进展，可能会改善贫血管理。其中第一个是一个随机对照临床试验的模型预测控制在促红细胞生成素的剂量出版物。这项工作表明，血红蛋白的变异性可以减少血红蛋白反应的预测模型。从长远来看，第二篇出版物可能更有趣，因为在明确定义的患者人群中发现了促红细胞生成素反应的新标志物。血红蛋白反应的预测模型通过降低血红蛋白变异性改善贫血管理。这将使更多患者处于目标范围内。将这些工具与血红蛋白反应的新生物标志物相结合，有可能显着改善贫血管理。
This review will explore the basic assumptions needed to perform predictive modeling of hemoglobin response to erythropoiesis stimulating agents (ESAs) and summarize the current literature in the area so that the practitioner can incorporate these tools as part of an improved anemia management process. During the last year, several publications have demonstrated some advances in the field that may improve anemia management. The first of these was the publication of a randomized, controlled clinical trial of model predictive control in the dosing of erythropoietin. This work showed that hemoglobin variability can be decreased using predictive models of hemoglobin response. The second publication is potentially more interesting in the long run, as new markers of erythropoietin response were identified in a well-defined population of patients. Predictive models of hemoglobin response improve anemia management by decreasing hemoglobin variability. This will result in more patients within the target range. Coupling these tools with new biomarkers of hemoglobin response has the potential to dramatically improve anemia management.