Advancing Precision Medicine for Hypertensive Nephropathy: A Novel Prognostic Model Incorporating Pathological Indicators.

IF 2.3 4区医学 Q2 PERIPHERAL VASCULAR DISEASE

Kidney & blood pressure research Pub Date : 2025-01-01 Epub Date: 2025-03-29 DOI:10.1159/000545524

Yunlong Qin, Jin Zhao, Yan Xing, Zixian Yu, Panpan Liu, Yuwei Wang, Anjing Wang, Yueqing Hui, Wei Zhao, Mei Han, Meng Liu, Xiaoxuan Ning, Shiren Sun

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引用次数: 0

Abstract

Introduction: This study aimed to assess the long-term renal prognosis of patients with hypertensive nephropathy (HN) diagnosed through renal biopsy, utilizing the random survival forest (RSF) algorithm.

Methods: From December 2010 to December 2022, HN patients diagnosed by renal biopsy in Xijing Hospital were enrolled and randomly divided into training set and testing set at a ratio of 7∶3. The study's composite endpoint was defined as a ≥50% decline in estimated glomerular filtration rate (eGFR), end-stage renal disease, or death. RSF and Cox regression were used to establish a renal prognosis prediction model based on the factors screened by the RSF algorithm. The Concordance index (C-index), integrated Brier score, net reclassification improvement (NRI), and integrated discrimination improvement (IDI) were used to evaluate discrimination, calibration, and risk classification, respectively.

Results: A total of 225 patients were included in this study, with 72 (32.0%) patients experiencing combined events after a median follow-up of 29.9 (16.6, 52.1) months. Six eligible variables (overall chronicity grade of renal pathology, eGFR, high-density lipoprotein cholesterol, hematocrit, monocyte, and stroke volume) were selected from clinical data and introduced into the RSF model. The RSF model had a higher C-index in both the training set (0.904 [95% CI: 0.842-0.938] vs. 0.831 [95% CI: 0.768-0.894], p < 0.001) and the testing set (0.893 [95% CI: 0.770-0.944] vs. 0.841 [95% CI: 0.751-0.931], p = 0.021) compared to the Cox model. NRI and IDI indicated that the RSF model outperformed the Cox model regarding risk classification.

Conclusion: In this study, the RSF algorithm was employed to identify the risk factors affecting the prognosis of HN patients, and a clinical prognostic RSF model was constructed to predict the adverse outcomes of HN patients based on renal pathology. Compared to the traditional Cox regression model, the RSF model offers superior performance and can provide valuable new insights for clinical diagnosis and treatment strategies.

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推进高血压肾病的精准医学：结合病理指标的新型预后模型。

摘要：本研究旨在利用随机生存森林（RSF）算法评估肾活检诊断的高血压肾病（HN）患者的长期肾脏预后。方法：选取2010年12月~ 2022年12月在西京医院经肾活检确诊的HN患者，按7∶3的比例随机分为训练集和测试集。该研究的综合终点定义为肾小球滤过率（eGFR）、ESRD或死亡率下降≥50%。基于RSF算法筛选的因素，采用RSF和Cox回归建立肾脏预后预测模型。采用一致性指数（C-index）、综合brier评分（IBS）、净重分类指数（NRI）和综合判别改进（IDI）分别评价辨别性、校准性和风险分类。结果：本研究共纳入225例患者，其中72例（32.0%）患者在中位随访29.9（16.6,52.1）个月后出现合并事件。从临床数据中选择6个符合条件的变量（肾脏病理总体慢性分级、eGFR、高密度脂蛋白胆固醇、红细胞压积、单核细胞和脑卒中体积）并引入RSF模型。与Cox模型相比，RSF模型在训练集[0.904 (95%CI 0.842 - 0.938) vs 0.831 (95%CI 0.768 - 0.894), P < 0.001]和检验集[0.893 (95%CI 0.770 - 0.944) vs 0.841 (95%CI 0.751 - 0.931), P = 0.021]的c -指数均较高。NRI和IDI表明，RSF模型在风险分类和区分方面优于Cox模型。结论：本研究采用RSF算法识别影响HN患者预后的危险因素，并基于肾脏病理构建临床预后RSF模型，预测HN患者的不良结局。与传统的Cox回归模型相比，RSF模型具有优越的性能，可以为临床诊断和治疗策略提供有价值的新见解。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Kidney & blood pressure research 医学-泌尿学与肾脏学

CiteScore

4.80

自引率

3.60%

发文量

审稿时长

6-12 weeks

期刊介绍： This journal comprises both clinical and basic studies at the interface of nephrology, hypertension and cardiovascular research. The topics to be covered include the structural organization and biochemistry of the normal and diseased kidney, the molecular biology of transporters, the physiology and pathophysiology of glomerular filtration and tubular transport, endothelial and vascular smooth muscle cell function and blood pressure control, as well as water, electrolyte and mineral metabolism. Also discussed are the (patho)physiology and (patho) biochemistry of renal hormones, the molecular biology, genetics and clinical course of renal disease and hypertension, the renal elimination, action and clinical use of drugs, as well as dialysis and transplantation. Featuring peer-reviewed original papers, editorials translating basic science into patient-oriented research and disease, in depth reviews, and regular special topic sections, ''Kidney & Blood Pressure Research'' is an important source of information for researchers in nephrology and cardiovascular medicine.