Mase Kaori, Yamagata Kunihiro, Yamamoto Hiroyasu, Tsuruya Kazuhiko, Hase Hiroki, Nishi Shinichi, Nangaku Masaomi, Wada Takashi, Hayashi Terumasa, Uemura Yukari, Hirakata Hideki
Department of Nephrology, Institute of Medicine, University of Tsukuba, Tsukuba, Japan,
Department of Nephrology, Institute of Medicine, University of Tsukuba, Tsukuba, Japan.
Am J Nephrol. 2023;54(11-12):471-478. doi: 10.1159/000534438. Epub 2023 Oct 4.
Hyporesponsiveness to erythropoiesis-stimulating agents (ESAs) has been associated with increased mortality and cardiovascular events in patients with chronic kidney disease. We hypothesized that the prediction of ESA resistance during ESA administration would be very useful in deciding on a treatment plan.
Patients enrolled in a randomized controlled trial to evaluate renal prognosis in anemic patients with non-dialysis-dependent chronic kidney disease with hyporesponsiveness to ESA were included; the patients had different target hemoglobin levels. A landmark analysis was performed at 3 months into the study. To construct a predictive model for the severe ESA hypo-responder group, in which there was no increase in hemoglobin even with active treatment, background factors and serum test items that affect anemia at study entry were included in a logistic regression model, the area under the curve (AUC) and 95% confidence intervals (CI) were estimated, and sensitivity and specificity were calculated. This study was a post hoc sub-analysis of a randomized controlled trial.
The AUC for the 19 existing risk factors as predictors was 0.783 (95% CI: 0.711-0.855). Among the 19 risk factors, the combination of six factors (hemoglobin level, systolic blood pressure, weight, gender, smoking status, and hypertensive retinopathy) with the largest χ2 statistics were selected by multiple logistics regression. The AUC for these 6 predictors was 0.716 (95% CI: 0.634-0.799). To the six existing risk factors, five serum test items that affect anemia (vitamin B12, vitamin B6, folic acid, parathyroid hormone, and 25-hydroxyvitamin D) were added, for a total of 11 risk factors, with a similar AUC of 0.736 (95% CI: 0.655-0.817), sufficient to predict ESA resistance.
Our results suggest that existing risk factors and serum test items can be used to predict ESA resistance in patients with non-dialysis-dependent chronic kidney disease on ESA.
对促红细胞生成素(ESA)反应低下与慢性肾脏病患者死亡率增加及心血管事件相关。我们推测,在ESA治疗期间预测ESA抵抗对于制定治疗方案非常有用。
纳入一项随机对照试验的患者,该试验旨在评估对ESA反应低下的非透析依赖性慢性肾脏病贫血患者的肾脏预后;这些患者有不同的目标血红蛋白水平。在研究第3个月进行了一项标志性分析。为构建严重ESA低反应组(即即便积极治疗血红蛋白仍未升高的患者)的预测模型,将研究入组时影响贫血的背景因素和血清检测项目纳入逻辑回归模型,估计曲线下面积(AUC)和95%置信区间(CI),并计算敏感性和特异性。本研究是一项随机对照试验的事后亚分析。
作为预测指标的19个现有危险因素的AUC为0.783(95%CI:0.711 - 0.855)。在这19个危险因素中,通过多元逻辑回归选择了χ²统计量最大的6个因素(血红蛋白水平、收缩压、体重、性别、吸烟状况和高血压视网膜病变)的组合。这6个预测指标的AUC为0.716(95%CI:0.634 - 0.799)。在这6个现有危险因素基础上,增加了5个影响贫血的血清检测项目(维生素B12、维生素B6、叶酸、甲状旁腺激素和25 - 羟基维生素D),共11个危险因素,AUC相似,为0.736(95%CI:0.655 - 0.817),足以预测ESA抵抗。
我们的结果表明,现有危险因素和血清检测项目可用于预测接受ESA治疗的非透析依赖性慢性肾脏病患者的ESA抵抗。