基于血清补体C3与CHI3L1构建紫癜性肾炎高危患儿的预测模型及防治策略

Development of a predictive model and prevention strategy for high-risk children with Henoch-Schönlein purpura nephritis based on serum complement C3 and CHI3L1

摘要:

目的 探讨血清补体C3与人软骨糖蛋白39（CHI3L1）对儿童紫癜性肾炎（HSPN）预后的预测价值，构建联合预测模型及防治策略，为临床早期识别、治疗高危患儿提供依据。方法 按照1∶1比例纳入首都医科大学附属北京安贞医院南充医院2020年1月—2024年12月收治的100例HSPN患儿临床资料，展开回顾性分析。患儿分为预后良好组和预后不良组，每组50例。收集患儿的人口学与临床特征、肾脏病理与功能评估、实验室指标及治疗方式。采用单因素分析和多因素逐步Logistic回归分析预后的影响因素，绘制受试者工作特征（ROC）曲线、精确率-召回曲线，评估各指标及联合模型的预测效能与模型质量。结果 预后良好组与预后不良组的性别构成、发病年龄、病程、肉眼血尿率、腹痛率、关节痛率、贫血率、低血清白蛋白率、肾素-血管紧张素系统（RAS）抑制剂使用率、应用泼尼松率、甲泼尼龙冲击治疗率、应用免疫率、胆固醇水平比较，差异均无统计学意义（P >0.05）。预后不良组的肾脏受累到肾穿刺时间、国际儿童肾病学学会分级（ISKDC）、高尿酸血症率、紫癜反复次数≥3次、皮疹持续时间≥2周、血小板计数（PLT）、CHI3L1水平、白细胞计数（WBC）、红细胞分布宽度（RDW）、中性粒细胞计数（NEU）、D-二聚体（D-D）、尿蛋白量、尿N-乙酰-β-D-氨基葡萄糖苷酶与肌酐比值（NAG/Cr）、C反应蛋白（CRP）水平均高于预后良好组（P <0.05），预后不良组皮疹到肾脏受累时间和补体C3水平均低于预后良好组（P <0.05）。多因素逐步Logistic回归分析显示，ISKDC分级升高［O^R=2.339（95% CI：1.248，4.385）］、NEU升高［O^R=2.955（95% CI：1.077，4.508）］、CHI3L1升高［O^R=1.353（95% CI：1.109，1.651）］及补体C3下降［O^R=0.002（95% CI：0.000，0.338）］均是HSPN患儿预后不良的独立危险因素（P <0.05）。ROC曲线分析结果显示，ISKDC分级、NEU、补体C3、CHI3L1及联合模型预测HSPN患儿预后的曲线下面积分别为0.706、0.813、0.728、0.819、0.937。ISKDC分级、NEU、补体C3、CHI3L1及联合模型的敏感性分别为76.0%、78.0%、84.0%、78.0%和88.0%；特异性分别为56.0%、76.0%、56.0%、84.0%和94.0%。模型质量评分为0.83。内部验证显示联合模型曲线下面积为0.906，校准良好（P >0.05）。结论 ISKDC分级、NEU、补体C3、CHI3L1可作为预测HSPN患儿预后的潜在生物标志物。基于上述指标构建的联合预测模型具有良好的判别能力和临床适用性，能够有效识别HSPN高危患儿。结合模型评估结果，提出了早期激素冲击治疗、免疫调节、抗纤维化药物联合应用及动态指标监测等个体化干预策略，为优化HSPN患儿的预后管理提供了参考。

Abstract:

Objective To investigate the predictive value of complement C3 and chitinase-3-like protein 1 (CHI3L1) in the prognosis of henoch-sch?nlein purpura nephritis (HSPN) in children, and to construct a combined predictive model and prevention strategy, thereby providing a basis for the early identification and treatment of high-risk pediatric patients.Methods A total of 100 pediatric HSPN patients were enrolled at a 1:1 ratio to Beijing Anzhen Nanchong Hospital of Capital Medical University (Nanchong Central Hospital) from January 2020 to December 2024 were retrospectively analyzed. Based on follow-up outcomes, patients were divided into a good prognosis group and a poor prognosis group (n = 50 each). Data including age of onset, laboratory parameters, and clinical features were collected. Univariate and multivariate logistic regression analyses were used to identify prognostic factors. The receiver operating characteristic (ROC) curve, precision-recall (PR) curve, and model quality score were employed to evaluate the predictive performance of individual markers and the combined model.Results No significant differences were observed between the good- and poor-prognosis groups regarding sex, age at onset, disease duration, macroscopic hematuria, abdominal or joint pain, anemia, hypoalbuminemia, RAS inhibitor or immunosuppressive therapy, and cholesterol levels (P > 0.05). The poor-prognosis group showed higher ISKDC grading, neutrophil count, WBC, RDW, D-dimer, proteinuria, NAG/UCr, CRP, CHI3L1,PLT, frequency of purpura ≥ 3 times, rash duration ≥ 2 weeks, hyperuricemia rate, and longer interval from kidney involvement to biopsy, but lower complement C3, and shorter rash-to-kidney involvement interval (P < 0.05). Multivariate logistic regression identified elevated ISKDC grading [O^R = 2.339 (95% CI: 1.248,4.385) ], neutrophil count [O^R = 2.955 (95% CI: 1.077, 4.508) ], CHI3L1 [O^R = 1.353 (95% CI: 1.109, 1.651) ], and decreased complement C3 [O^R = 0.002 (95% CI: 0.000, 0.338) ] as independent risk factors for poor prognosis (P < 0.05). ROC analysis showed AUCs of 0.706 (ISKDC), 0.813 (neutrophil), 0.728 (C3), 0.819 (CHI3L1), and 0.937 for the combined model, with sensitivities of 76.0%, 78.0%, 84.0%, 78.0%, 88.0%, and specificities of 56.0%, 76.0%, 56.0%, 84.0%, 94.0%. Internal validation confirmed good calibration (AUC = 0.906, P > 0.05).Conclusion ISKDC grade, NEU, CHI3L1, and complement C3 are potential biomarkers for predicting prognosis in HSPN children. The combined predictive model based on these indicators demonstrates strong discriminatory ability and clinical applicability, enabling effective identification of high-risk patients. Based on the model assessment results, individualized intervention strategies including early corticosteroid pulse therapy, immunomodulation, combined antifibrotic therapy, and dynamic monitoring of relevant indicators are proposed to optimize the prognostic management of HSPN children.