Department of Medical Imaging, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China,
Department of Nephrology, Kidney Hospital, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China,
Blood Purif. 2024;53(9):755-767. doi: 10.1159/000539786. Epub 2024 Jun 20.
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.
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.
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.
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.
慢性肾脏病相关性瘙痒（CKD-aP）常发生于接受腹膜透析（PD）的终末期肾病（ESRD）患者，由于其发病机制多样，给医生的治疗带来了挑战。在此，我们开发并验证了一种用于个体化评估 CKD-aP 风险的列线图模型，并探讨了 PD 患者 CKD-aP 的可能原因。
我们回顾性筛选了 2021 年至 2023 年期间在西安交通大学第一附属医院腹膜透析中心接受 PD 的 CKD-aP 患者。使用最小绝对收缩和选择算子（LASSO）回归和单变量逻辑回归进行变量选择的多变量逻辑回归模型计算每种结局的列线图。通过 Harrell 的 C 指数评估判别能力，并通过校准曲线图评估准确性。模型通过 bootstrap 进行内部验证，并通过计算验证队列的性能进行外部验证。决策曲线分析用于评估模型的临床实用性。
共有 487 例患者纳入分析，其中 325 例患者纳入开发队列，162 例患者纳入验证队列。最终的列线图纳入了 5 个变量：年龄、白细胞介素-6、血红蛋白、残余尿量和肾脏 Kt/V。模型的 C 指数为 0.733（95%CI：0.679-0.787），校准曲线为斜率接近 1 的直线。内部和外部验证均证实了该模型的良好性能，C 指数分别为 0.725（95%CI：0.662-0.774）和 0.706（95%CI：0.623-0.789）。决策曲线分析表明，该列线图具有良好的临床获益。
本研究提出了一种用于 ESRD 患者 PD 后 CKD-aP 风险评估的列线图模型。该列线图可能有助于临床决策和基于证据的治疗选择。
