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. 2025 Jan 21;15(1):2689.
doi: 10.1038/s41598-025-87456-z.

Renal anemia and hyporesponsiveness to ESA for preservation of residual kidney function in patients undergoing peritoneal dialysis

Takahiro Imaizumi  1   2 , Takeshi Hasegawa  3   4   5   6   7 , Takaaki Kosugi  8 , Hiroki Nishiwaki  9 , Masanori Abe  10   11 , Norio Hanafusa  11   12 , Hirokazu Honda  5 , Kazuhiko Tsuruya  8 , Yasuhiko Ito  13 , Takahiro Kuragano  14
Affiliations

Renal anemia and hyporesponsiveness to ESA for preservation of residual kidney function in patients undergoing peritoneal dialysis

Takahiro Imaizumi et al. Sci Rep. .

Abstract

Preservation of residual kidney function (RKF) is important in patients undergoing peritoneal dialysis (PD). We aimed to examine the association between anemia management and residual urine output using data from a nationwide survey of dialysis patients. After excluding patients with anuria at baseline from the Total cohort of 2,712, 659 of 1,640 patients developed anuria during a median follow-up of 2.5 (interquartile range: 1.5-4.2) years. Urine volume decreased more rapidly as hemoglobin decreased or as the erythropoiesis-stimulating agent (ESA) resistance index (ERI) increased. The hazard ratios with 95% confidence intervals for the development of anuria, defined as residual urine volume ≤ 100 mL/day, were 1.65 (1.20-2.27), 1.39 (1.08-1.77), and 1.32 (1.07-1.63) for hemoglobin levels of < 9.0, 9.0-9.9, and 10.0-10.9 g/dL compared with 11.0-11.9 g/dL, and 1.35 (1.10-1.66) and 1.41 (1.14-1.73) for the second and third tertiles of ERI compared with the first tertile. In conclusion, patients with a low hemoglobin level or a high ERI were more likely to experience a decline in residual urine output and to develop anuria. Further studies are needed to investigate the effects of interventions that could improve renal anemia and/or ESA hyporesponsiveness on RKF preservation.

Keywords: Anuria; Erythropoiesis-stimulating agent resistance index; Hyporesponsiveness to erythropoiesis-stimulating agent; Peritoneal dialysis; Residual kidney function.

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Conflict of interest statement

Declarations. Competing interests: TI received a research grant from Kyowa Kirin Co., Ltd. and a consultation fee from GlaxoSmithKline. TH received a research grant from JSPS KAKENHI (Grant Number 19K03092 and 24K06239), and honoraria from Kyowa Kirin, Baxter, Terumo, and Torii Pharmaceutical. TKo received honoraria from Kowa, Torii, Sanwa Kagaku Kenkyusyo, and AstraZeneca. HN received speaker honoraria from Kyowa Kirin, Baxter, Terumo, Ono Pharmaceutical Co. Ltd., Daiichi-Sankyo, and Kissei Pharmaceutical Co. Ltd. MA received honoraria from Kyowa Kirin, Baxter, Terumo, Mitsubishi Tanabe, Torii, Bayer Yakuhin, and Astellas. HH is a scientific advisor for Astellas Pharma, Bayer Yakuhin, Kyowa Kirin, Mitsubishi Tanabe Pharma, and Torii Pharmaceutical and has obtained research funds from Chugai Pharmaceutical, Kyowa Kirin, Otsuka Pharmaceutical, and Torii Pharmaceutical and lecture fees from Astellas Pharma, Bayer Yakuhin, Chugai Pharmaceutical, Kissei Pharmaceutical, Kyowa Kirin, Mitsubishi Tanabe Pharma, and Torii Pharmaceutical. KT received honoraria from Kyowa Kirin, Mitsubishi-Tanabe, Astellas, Torii, Bayer, Baxter, Kissei, and Chugai and endorsements from Kyowa Kirin, Baxter, Terumo, Torii, Chugai, and Bayer. YI received research grants and speaker honoraria from Chugai Pharmaceutical, Kyowa Kirin, Astellas Pharma, Mitsubishi Tanabe Pharma, Bayer, and Torii Pharmaceuticals. TKu received research grants from Ono Pharmaceutical Co., Ltd., Kissei Pharmaceutical Co., Ltd., speaker bureaus from Kyowa Kirin, Fuso Pharmaceutical Industries, Ltd., Mitsubishi Tanabe Pharma Corporation, Astellas Pharma Inc., AstraZeneca Plc., and Bayer Yakuhin Ltd. All the remaining authors have nothing to disclose.

Figures

Fig. 1
Fig. 1
Flow diagram of patient selection. In the Total cohort, patients undergoing PD with available data on ESA dose and residual urine were included to examine the association between urine output and ERI. In the Analytic cohort, after excluding those with a urine volume ≤ 100 mL/day at baseline and those with only one urine data available, we examined the longitudinal association of ERI with urine output. PD, peritoneal dialysis; ESA, erythropoiesis-stimulating agent; ERI, ESA resistance index; UV, urine volume.
Fig. 2
Fig. 2
Longitudinal trajectories of residual urine output across levels of hemoglobin and ESA resistance index at baseline. Longitudinal trajectories of residual urine output across levels of hemoglobin (A) and ERI tertiles (B) were estimated using mixed-effects models. The residual urine output decreased more rapidly over time in patients with lower hemoglobin levels or higher ERI. Models were adjusted for age, sex, time since dialysis initiation, and log-transformed urine volume at baseline. ESA, erythropoiesis-stimulating agent; ERI, ESA resistance index.
Fig. 3
Fig. 3
Association between hemoglobin levels and anuria. Covariates in multivariable adjustment models were as follows: age, sex, time since starting PD, hypertension, urine output at baseline, weekly ESA dose; DM, BMI, history of myocardial infarction, history of stroke, total Kt/V, and smoking (Model 1, a demographic model); Model 1 + TSAT, and ferritin (Model 2, + iron indices); Model 2 + phosphorus, calcium, and intact PTH (Model 3, + CKD-MBD markers); Model 3 + CRP and history of peritonitis (Model 4, + inflammation); Model 4 + albumin and total cholesterol (Model 5, nutritional indices). HR, hazard ratio; CI, confidence interval; ESA, erythropoiesis-stimulating agent; ERI, ESA resistance index; PD, peritoneal dialysis; DM, diabetes mellitus; BMI, body mass index; TSAT, transferrin saturation; PTH, parathyroid hormone; CKD-MBD, chronic kidney disease mineral and bone disorder; CRP, C-reactive protein.
Fig. 4
Fig. 4
Non-linear association between ESA resistance index and risk of anuria. Non-linear estimation of residual urine output was demonstrated using restricted cubic spline analysis with three knots at the 10th, 50th, and 90th percentiles of ERI in all patients (A) and in those who were administered ESA (B). The reference category was placed on the median values of ERI, 2.47 (A) and 2.68 (B). A multivariable regression model was adjusted for the variables in Model 5. ESA, erythropoiesis-stimulating agent; ERI, ESA resistance index.
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