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通过红细胞生成的数学模型预测个体血液透析患者的血红蛋白水平。

Prediction of hemoglobin levels in individual hemodialysis patients by means of a mathematical model of erythropoiesis.

机构信息

Renal Research Institute, New York, New York, United States of America.

Institute for Mathematics and Scientific Computing, Karl-Franzens University, Graz, Austria.

出版信息

PLoS One. 2018 Apr 18;13(4):e0195918. doi: 10.1371/journal.pone.0195918. eCollection 2018.

Abstract

Anemia commonly occurs in people with chronic kidney disease (CKD) and is associated with poor clinical outcomes. The management of patients with anemia in CKD is challenging, due to its severity, frequent hypo-responsiveness to treatment with erythropoiesis stimulating agents (ESA) and common hemoglobin cycling. Nonlinear dose-response curves and long delays in the effect of treatment on red blood cell population size complicate predictions of hemoglobin (Hgb) levels in individual patients. A comprehensive physiology based mathematical model for erythropoiesis was adapted individually to 60 hemodialysis patients treated with ESAs by identifying physiologically meaningful key model parameters from temporal Hgb data. Crit-Line® III monitors provided non-invasive Hgb measurements for every hemodialysis treatment. We used Hgb data during a 150-day baseline period together to estimate a patient's individual red blood cell lifespan, effects of the ESA on proliferation of red cell progenitor cells, endogenous erythropoietin production and ESA half-life. Estimated patient specific parameters showed excellent alignment with previously conducted clinical studies in hemodialysis patients. Further, the model qualitatively and quantitatively reflected empirical hemoglobin dynamics in demographically, anthropometrically and clinically diverse patients and accurately predicted the Hgb response to ESA therapy in individual patients for up to 21 weeks. The findings suggest that estimated model parameters can be used as a proxy for parameters that are clinically very difficult to quantify. The presented method has the potential to provide new insights into the individual pathophysiology of renal anemia and its association with clinical outcomes and can potentially be used to guide personalized anemia treatment.

摘要

贫血在慢性肾脏病(CKD)患者中很常见,与不良临床结局相关。CKD 患者贫血的管理具有挑战性,这是由于其严重程度、对红细胞生成刺激剂(ESA)治疗的频繁低反应性以及常见的血红蛋白循环所致。非线性剂量反应曲线和治疗对红细胞群体大小的影响的延迟很长,使得个体患者的血红蛋白(Hgb)水平预测变得复杂。我们通过从时间性 Hgb 数据中确定生理上有意义的关键模型参数,将基于生理学的红细胞生成综合数学模型个体化地适应于 60 名接受 ESA 治疗的血液透析患者。Crit-Line® III 监测仪为每次血液透析治疗提供非侵入性 Hgb 测量值。我们在 150 天的基线期内使用 Hgb 数据一起估计患者的个体红细胞寿命、ESA 对红细胞祖细胞增殖、内源性促红细胞生成素产生和 ESA 半衰期的影响。估计的患者特异性参数与血液透析患者先前进行的临床研究非常吻合。此外,该模型在人口统计学、人体测量学和临床方面具有异质性的患者中定性和定量地反映了经验性血红蛋白动力学,并准确预测了个体患者对 ESA 治疗的 Hgb 反应长达 21 周。研究结果表明,估计的模型参数可用作临床难以量化的参数的替代物。该方法有可能为肾脏贫血的个体病理生理学及其与临床结局的关联提供新的见解,并有可能用于指导个体化贫血治疗。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ab10/5905967/b94904d1f392/pone.0195918.g001.jpg

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