原发性膜性肾病血栓栓塞临床预测模型的建立与验证
Establishment and Validation of a Predictive Model for Thromboembolism in Primary Membranous Nephropathy
摘要: 目的:建立原发性膜性肾病血栓栓塞预测模型并验证。方法:收集2018年8月1日~2020年12月31日于青岛大学附属医院测定抗磷脂酶A2受体抗体滴度的原发性膜性肾病病人119例,以D二聚体是否发生异常为分组依据分为血栓栓塞组(n = 39人),非血栓栓塞组(n = 80人)。利用差异性分析与单因素逻辑回归筛选患者合并血栓栓塞并发证的危险因素。根据多因素逻辑回归分析建立血栓栓塞并发症的临床预测模型,并对临床预测模型进行评价以及验证。结果:差异性分析后,血栓栓塞组与非血栓栓塞组患者在性别、血清白蛋白、血清PLA2R抗体、24小时尿蛋白定量这4项指标有显著性差异(P < 0.05)。在单因素逻辑回归分析中上述5项均有意义是血栓栓塞的危险因素(P < 0.05),其中经过多因素逻辑回归分析血清白蛋白与24小时尿蛋白定量可以认为是原发性膜性肾病血栓栓塞的独立危险因素(P < 0.05)。随后我们以这4项指标构建临床诊断模型并以列线图呈现。其有较好的评价性能。结论:基于性别、血清白蛋白、血清PLA2R抗体、24小时尿蛋白定量这4项指标,构建的原发性膜性肾病并发血栓栓塞的临床预测模型,对发生血栓栓塞并发症的区分度较高,有利于血栓栓塞并发症早期的防治。
Abstract: Objective: To establish and verify the prediction model of thromboembolism in primary membra-nous nephropathy. Methods: A total of 119 patients with primary membranous nephropathy, whose anti-phospholipase A2 receptor antibody titers were measured in The Affiliated Hospital of Qingdao University from August 1st, 2018 to December 31st, 2020, were divided into the thromboembolic group (n = 39) and the non-thromboembolic group (n = 80) according to the abnormality of D-dimer. Differential analysis and univariate logistic regression were used to screen the risk factors for patients with thromboembolism. The clinical prediction model of thromboembolic complications was established based on multivariate logistic regression analysis, and the clinical prediction model was evaluated and verified. Results: After difference analysis, there were significant differences in gender, serum albumin, serum PLA2R antibody and 24-hour urine protein quantification between thromboembolic group and non-thromboembolic group (P < 0.05). In univariate logistic regression analysis, all the above 4 items were significant risk factors for thromboembolism (P < 0.05), and serum albumin and 24-hour urine protein quantification could be considered as independent risk factors for thromboembolism of primary membranous nephropathy after multivariate logistic re-gression analysis (P < 0.05). Subsequently, we constructed a clinical diagnostic model based on these 4 indicators and presented it as a column chart. It has good evaluation performance. Conclu-sion: Based on the four indexes of gender, serum albumin, serum PLA2R antibody and 24-hour urine protein quantification, the clinical prediction model of primary membranous nephropathy complicated with thromboembolism was established, which has a high degree of differentiation in the occurrence of thromboembolism complications, and is conducive to the early prevention and treatment of thromboembolism complications.
文章引用:陈怿鹏, 何颖, 高鹏丽, 张嘉倩, 邢广群. 原发性膜性肾病血栓栓塞临床预测模型的建立与验证[J]. 临床医学进展, 2022, 12(7): 6621-6628. https://doi.org/10.12677/ACM.2022.127956

1. 引言

原发性膜性肾病(Primary membranous nephropathy, pMN)是成人肾病综合征的主要病因之一 [1]。组织学特征为光镜下肾小球基底膜增厚,免疫荧光观察到IgG和补体C3沿毛细血管袢颗粒样沉积,电镜下可见上皮下电子致密物沉积 [2] [3] [4]。pMN的主要自身抗原被鉴定为m型磷脂酶A2受体(Phospholipase A2 receptor, PLA2R),这是一种位于足细胞上的跨膜蛋白,与IgG4在上皮下免疫沉积物中共定位。循环抗PLA2R抗体的测定迅速改变了pMN的临床实践。抗PLA2R抗体对pMN的诊断特异性约为96%~99% [5]。抗PLA2R抗体滴度水平与pMN临床活性密切相关,可以有效地预测pMN的预后和治疗反应。因此,它可以作为一种很好的生物标志物来监测疾病的活跃程度。

pMN的治疗目标主要集中在预防终末期肾病(End stage renal disease, ESRD),ESRD通常发生在数年后,而pMN的其他并发症可能在病程中更早发生 [6]。静脉血栓栓塞事件(Venous thromboembolic events, VTE)包括下肢深静脉血栓(Deep venous thrombosis, DVT)、肾静脉血栓(Renal venous thrombosis, RVT)、脑血栓形成和肺栓塞(Pulmonary embolism, PE)。VTE被认为是pMN的早期并发症,具有显著的发病率和死亡率。既往研究已明确低白蛋白血症是肾病综合征VTE风险重要的独立危险因素 [7] [8]。而动脉血栓栓塞事件(Arterial thromboembolic events, ATE)的绝对风险主要集中发生在pMN起病的前6个月,严重的蛋白尿、估算的肾小球滤过率下降和吸烟是ATES的预测因素 [7] [9]。有研究报道,36%的pMN患者有DVT,33%有RVT,17%有PE。

但同时,现在关于预测pMN血栓栓塞并发症的临床诊断模型较少。本研究回顾性分析了青岛大学附属医院进行了抗PLA2R抗体检测的pMN患者的入院临床资料。建立并验证针对pMN患者血栓栓塞并发症的临床预测模型,为pMN患者血栓栓塞的早期防治提供重要的参考依据。

2. 对象与方法

2.1. 研究对象

收集2018年8月1日~2020年12月31日于青岛大学附属医院测定抗磷脂酶A2受体抗体滴度的原发性膜性肾病病人。研究的纳入标准和排除标准如下。纳入标准:1) 肾穿刺活检明确诊断为原发性膜性肾病,同时在肾穿刺活检当天早晨抽血送检了血清抗PLA2R抗体检测的患者;2) 现有人口学信息和临床信息完整;3) 患者年龄在18岁以上。排除标准:1) 患者伴发恶性肿瘤;2) 伴有结缔组织病或继发性膜性肾病;3) 有乙型、丙型肝炎及或严重肝功能不全患者;4) 孕妇或哺乳期妇女。经过筛选共入组119名患者,其中发生血栓栓塞并发症的患者39例,未发生血栓栓塞并发症的患者80例。本研究通过青岛大学医院检索电子病历和实验室数据记录。所有研究都是在所有参与者和/或其法定监护人的知情同意下,按照相关准则/规定进行的。

2.2. 研究方法

2.2.1. 血清抗PLA2R抗体滴度测定

循环抗PLA2R抗体采用商业ELISA试剂盒(EUROIMMUN AG, EA1254-9601G),按照标准说明进行检测 [10]。

2.2.2. 临床资料的收集

收集人口统计数据和实验室检查数据。人口数据包括性别;年龄;血压(包括收缩压和舒张压);体重指数(Body mass index, BMI);吸烟史。临床实验室资料包括:血小板计数、血清白蛋白、甘油三脂、血尿酸、低密度脂蛋白、血清肌酐、24小时尿蛋白定量。

2.3. 血栓栓塞事件的界定

血栓栓塞的诊断标准如下:pMN患者易发生血栓栓塞的部位不定且隐匿,在临床容易在影像学中漏诊 [11]。所以本文在排除了D二聚体常见的升高因素后,以D二聚体异常为血栓栓塞的诊断标准。D二聚体是临床上提示血栓栓塞的敏感指标。且目前对这个检测指标的研究较为成熟,D二聚体随年龄的增加增长,年龄 < 50岁者,D二聚体 > 500 μg/L被视为有提示作用;年龄大于50岁者,D二聚体 > 年龄*10被认为有提示价值。

2.4. 统计学分析

采用SPSS 25.0软件进行数据的统计学处理。正态分布的计量资料用 x ¯ ± s 表示,采用t检验;非正态分布的计量资料用M(1/4, 3/4)表示,采用Mann-Whitney U检验。分类变量以例数(百分比)表示,用卡方检验或Fisher确切概率法进行两组间比较。将单因素分析结果中P < 0.05的自变量纳入多因素逻辑回归方程,并对所有自变量进行共线性诊断,排除共线性问题后,筛选出pMN并发肾损害的独立危险因素。把单因素逻辑回归的因素代入确定最终模型,应用R 3.6.0版本建立列线图。采用C指数检验评价模型的区分度及临床决策曲线对模型临床实用性进行评价。本文中*P < 0.05,**P < 0.01,***P < 0.001。

3. 结果

3.1. 原发性膜性肾病血栓栓塞组与非血栓栓塞组患者的临床资料比较

pMN患者血栓栓塞组与非血栓栓塞组患者在性别、血清白蛋白、血清PLA2R抗体、24小时尿蛋白定量这4项指标有显著性差异(P < 0.05)。其余指标没有显著性差异。

Table 1. Comparison of general clinical data of pMN patients with thromboembolism and non-thromboembolism

表1. pMN血栓栓塞组与非血栓栓塞组患者入院一般临床资料比较

3.2. 原发性膜性肾病发生血栓栓塞并发症的单因素与多因素二元逻辑回归分析

在进行了单因素逻辑回归后性别、血清白蛋白、血清PLA2R抗体、24小时尿蛋白定量这4项指标都可以认为是pMN合并血栓栓塞的危险因素(P < 0.05)。经过多因素逻辑回归的分析血清白蛋白与24小时尿蛋白定量可以认为是pMN合并血栓栓塞的独立危险因素。

Table 2. Univariate and multivariate binary logistic regression analysis of thromboembolic complications in pMN patients

表2. pMN发生血栓栓塞并发症的单因素与多因素二元逻辑回归分析

3.3. 临床模型的可视化构建与评价

在“图1”中我们基于多因素逻辑回归建立了pMN血栓栓塞临床预测模型,并且用列线图的方式对临床预测模型进行了可视化处理。在“图2”中我们评价了这个模型,经过1000次自抽样,其错误119次,正确率约为88.1%,并且其平均绝对误差为0.059,可以认为临床决策模型有较好的区分能力。在“图3”中我们运用临床决策曲线对临床预测模型进行了评价,表明临床预测模型是最具效果的。

Figure 1. Establishment of a clinical prediction model for pMN thromboembolism

图1. pMN血栓栓塞临床预测模型的列线图建立

Figure 2. C-index calibration curves of clinical prediction models for pMN thromboembolism

图2. pMN血栓栓塞临床预测模型的C指数校准曲线

Figure 3. Clinical decision curve of pMN model for predicting thromboembolism

图3. pMN血栓栓塞临床预测模型的临床决策曲线

4. 讨论

pMN的血栓栓塞事件发生率明显高于其他类型的肾病综合征,Sean J [12] 发现pMN有7.9%的患者会患有VTE,相对局灶性节段性肾小球硬化(Focal segmental glomerulosclerosis, FSGS)与IgA肾病的血栓栓塞发生概率分别是3%与0.4%。pMN合并的血栓栓塞大多数患者症状隐匿 [13]。影像学诊断会受到血栓发生的部位、大小等多种因素影响,D二聚体检测具有灵敏的提示作用,该指标经过年龄校正后对血栓栓塞有较好的敏感度 [11] [14]。所以用D二聚体的异常作为血栓栓塞的分组依据。本研究致力于分析引起pMN血栓并发症的危险因素,拟建立有效的统计模型,实现模型的可视化,从而准确指导临床。

在“表1”中我们看到血栓栓塞组与非血栓栓塞组患者在性别、血清白蛋白、血清PLA2R抗体、24小时尿蛋白定量这4项指标有显著性差异(P < 0.05)。其余指标没有显著性差异。而在“表2”中经过单因素逻辑回归分析其上4个因素均是pMN血栓栓塞并发症的危险因素,而其中血清白蛋白与24小时尿蛋白定量这两个指标可以认为是独立危险因素。

pMN中血清抗PLA2R抗体有特异性,可以作为诊断的依据 [2]。在人体肾脏中抗PLA2R抗体穿过肾小球基底膜,与足突的PLA2R结合形成免疫复合物,并沉积在肾小球基底膜上。PLA2R存在于多种哺乳动物组织中,主要是M型PLA2R [15]。在血清中的抗PLA2R抗体高滴度是否可以对血管上皮造成损伤尚不清楚。但近年来的研究表明PLA2在哺乳动物体内发挥着重要作用 [16] [17] [18]。抗PLA2R抗体水平已被临床证明与疾病的预后相关,在2021年KDIGO指南中把抗PLA2R抗体受体水平作为pMN疾病严重程度分级的重要依据。并在指南中提出,当血清白蛋白小于20 g/L时应高度警惕VTE的发生,当血清白蛋白小于30 g/L时应警惕ATE的发生。血清白蛋白水平降低是pMN血栓栓塞事件的独立危险因素 [7]。在其他研究中,低血清白蛋白已被证明是pMN发生VTE的强大的独立危险因素。Lionaki, S [19] 的研究表明,静脉血栓栓塞风险的增加与血清白蛋白水平的降低成正比。白蛋白每降低1.0 g/dL,发生静脉血栓栓塞的风险增加2.13倍,阈值为2.8 g/dL。Zou [20] 建议,当血清白蛋白低于3.2 g/dL时,应使用阿司匹林或华法林进行个体化预防治疗。而大量蛋白尿会导致血清白蛋白的减少和大量体内抗凝剂的清除,而肝功能的代偿活动导致体内促凝物质的增加 [1] [21]。本研究还观察到24小时尿蛋白定量是血栓栓塞的独立危险因素。

本研究以性别、血清白蛋白、血清PLA2R抗体、24小时尿蛋白定量这4项指标所做临床预测模型在“图1”中通过列线图的形式直观地呈现出来。将上述预测因素整合起来,采用带有刻度的线段,按照一定的比例绘制在同一平面上,根据pMN患者自身情况计算得到一个总分,总分越高,其并发血栓栓塞的风险越大。随后在“图2”中通过C指数的方式对预测模型进行评价,经评价临床预测模型有较好的区分度。在“图3”中根据临床决策曲线对患者的临床净获益进行分析。表明单因素中血清白蛋白与抗PLA2R抗体水平均是个好的指标,其单一因素的临床净获益较大,但与之相比临床预测模型的临床净收益更大可以使患者更大的获益。

同时本研究也存在一定的局限性:① 本研究是单中心、回顾性研究,患者的病史依靠病历记录和患者调查取得,可能存在一定的信息偏倚。② 本研究的样本量有限,并且缺乏多中心的外部验证,其准确性仍有待进一步证实。下一步将扩大样本量,并进行多中心、前瞻性的验证。

5. 研究结论

本研究基于性别、血清白蛋白、血清PLA2R抗体、24小时尿蛋白定量这4项指标,构建的pMN并发血栓栓塞的临床预测模型,对发生血栓栓塞并发症的区分度较高,有利于血栓栓塞并发症早期的防治。

基金项目

国家自然科学基金项目(81770699),青岛市民生科技项目(15-9-2-90-nsh),青岛市卫生健康委员会优秀学术带头人培养计划资助(3565)。

NOTES

*通讯作者Email: gqx99monash@163.com

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