Abstract：
BACKGROUND: Chronic kidney disease-associated pruritus (CKD-aP) frequently occurs in patients with end-stage renal disease (ESRD) undergoing peritoneal dialysis (PD) and presents a therapeutic challenge to physicians owing to the diversity of its pathogenesis. Herein, we developed and validated a nomogram model for individualized risk estimation of CKD-aP and investigated the possible causes of CKD-aP in PD patients.
METHODS: We retrospectively screened patients with CKD-aP who underwent PD between 2021 and 2023 at the First Affiliated Hospital of Xi\'an Jiaotong University Peritoneal Dialysis Center. Nomograms for each outcome were computed from multivariate logistic regression models with the least absolute shrinkage and selection operator regression and univariate logistic regression for variable selection. The discriminative ability was estimated by Harrell\'s C-index, and the accuracy was assessed graphically with a calibration curve plot. Models were validated internally using bootstrapping and externally by calculating their performance on a validation cohort. Decision curve analysis was used to assess the model\'s clinical usefulness.
RESULTS: In all, a total of 487 patients were entered in the analysis, including 325 in the development cohort and 162 in the validation cohort. The final nomogram incorporated five variables: age, interleukin-6, hemoglobin, residual urine volume, and renal Kt/V. The C-index of the model was 0.733 (95% CI: 0.679-0.787), and the calibration curve was a straight line with a slope close to 1. Both internal and external validations confirmed the model\'s good performance, with C-index of 0.725 (95% CI: 0.662-0.774) and 0.706 (95% CI: 0.623-0.789), respectively. Decision curve analysis showed that the nomogram had good clinical benefits.
CONCLUSIONS: Our study proposes a nomogram model for CKD-aP risk assessment in ESRD patients with PD. This nomogram might help in clinical decision-making and evidence-based selection of therapy.
METHODS: We retrospectively screened patients with CKD-aP who underwent PD between 2021 and 2023 at the First Affiliated Hospital of Xi\'an Jiaotong University Peritoneal Dialysis Center. Nomograms for each outcome were computed from multivariate logistic regression models with the least absolute shrinkage and selection operator regression and univariate logistic regression for variable selection. The discriminative ability was estimated by Harrell\'s C-index, and the accuracy was assessed graphically with a calibration curve plot. Models were validated internally using bootstrapping and externally by calculating their performance on a validation cohort. Decision curve analysis was used to assess the model\'s clinical usefulness.
RESULTS: In all, a total of 487 patients were entered in the analysis, including 325 in the development cohort and 162 in the validation cohort. The final nomogram incorporated five variables: age, interleukin-6, hemoglobin, residual urine volume, and renal Kt/V. The C-index of the model was 0.733 (95% CI: 0.679-0.787), and the calibration curve was a straight line with a slope close to 1. Both internal and external validations confirmed the model\'s good performance, with C-index of 0.725 (95% CI: 0.662-0.774) and 0.706 (95% CI: 0.623-0.789), respectively. Decision curve analysis showed that the nomogram had good clinical benefits.
CONCLUSIONS: Our study proposes a nomogram model for CKD-aP risk assessment in ESRD patients with PD. This nomogram might help in clinical decision-making and evidence-based selection of therapy.
摘要：
背景：慢性肾脏病相关瘙痒（CKD-aP）常发生在接受腹膜透析（PD）的终末期肾脏病（ESRD）患者中，由于其发病机制的多样性，对医师提出了治疗挑战。在这里，我们建立并验证了CKD-aP个体化风险评估的列线图模型,并研究了PD患者CKD-aP的可能原因.
方法：我们回顾性筛查了在西安交通大学第一附属医院腹膜透析中心于2021年至2023年接受PD的CKD-aP患者。从具有最小绝对收缩率的多变量逻辑回归模型和用于变量选择的选择算子回归和单变量逻辑回归计算每个结果的列线图。判别能力由Harrell的C指数估计，并用校准曲线图对准确性进行了图形评估。模型使用自举进行内部验证，并通过在验证队列上计算其性能进行外部验证。决策曲线分析用于评估模型的临床有用性。
结果：总而言之，共有487名患者进入分析，其中325人在开发队列中，162人在验证队列中。最终的列线图包含四个变量：年龄，白细胞介素-6，血红蛋白，残余尿量,和肾Kt/V模型的C指数为0.733（95%CI0.679-0.787），校准曲线为斜率接近1的直线。内部和外部验证都证实了模型的良好性能，C指数为0.725（95%CI0.662-0.774）和0.706（95%CI0.323-0.789），分别。决策曲线分析表明，列线图具有良好的临床效益。
结论：我们的研究提出了ESRD伴PD患者CKD-aP风险评估的列线图模型。此列线图可能有助于临床决策和基于证据的治疗选择。
方法：我们回顾性筛查了在西安交通大学第一附属医院腹膜透析中心于2021年至2023年接受PD的CKD-aP患者。从具有最小绝对收缩率的多变量逻辑回归模型和用于变量选择的选择算子回归和单变量逻辑回归计算每个结果的列线图。判别能力由Harrell的C指数估计，并用校准曲线图对准确性进行了图形评估。模型使用自举进行内部验证，并通过在验证队列上计算其性能进行外部验证。决策曲线分析用于评估模型的临床有用性。
结果：总而言之，共有487名患者进入分析，其中325人在开发队列中，162人在验证队列中。最终的列线图包含四个变量：年龄，白细胞介素-6，血红蛋白，残余尿量,和肾Kt/V模型的C指数为0.733（95%CI0.679-0.787），校准曲线为斜率接近1的直线。内部和外部验证都证实了模型的良好性能，C指数为0.725（95%CI0.662-0.774）和0.706（95%CI0.323-0.789），分别。决策曲线分析表明，列线图具有良好的临床效益。
结论：我们的研究提出了ESRD伴PD患者CKD-aP风险评估的列线图模型。此列线图可能有助于临床决策和基于证据的治疗选择。
