Construction and validation of a clinical prediction model for early renal injury in patients with immunoglobulin A vasculitis
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摘要:目的
建立过敏性紫癜患者发生早期肾损伤的临床预测模型，并验证其有效性。
方法选取165例免疫球蛋白A(IgA)血管炎患者作为研究对象，依据病情是否累及肾脏分为肾损伤组(65例)和无肾损伤组(100例); 采集患者入院时资料(如年龄、性别、身高、体质量、心率、生活环境等一般资料，中性粒细胞与淋巴细胞比值、血小板与淋巴细胞比值等实验室检查指标)。采用单因素Logistic回归分析筛选高危因素，以逐步法建立临床预测模型，通过R4.2.2软件运行rms程序包将模型可视化。模型预测性能从模型区分度、校准度、可推广性(准确性、稳定性)3个方面进行评价; 模型内部验证采用十折交叉验证及Bootstrap法; 采用时段验证的方式进行外部验证。
结果2组患者生活环境、心率、血小板与淋巴细胞比值、血小板计数、乳酸脱氢酶、白细胞介素-6、尿β2-微球蛋白、尿微量白蛋白水平比较，差异有统计学意义(P < 0.05)。单因素Logistic回归分析结果显示，生活环境、心率、血小板与淋巴细胞比值、白细胞介素-6、尿β2-微球蛋白、尿微量白蛋白是IgAV患者发生早期肾损伤的影响因素(P < 0.05)。基于影响因素构建IgAV患者发生早期肾损伤的临床预测模型，随机拆分的十折交叉验证、Bootstrap重复抽样1 000次这2种验证方式均显示，该模型具有较好的准确性和稳定性。模型受试者工作特征曲线的曲线下面积(AUC)为0.87, 决策曲线分析显示，该模型预测IgAV患者发生肾损伤的概率阈值为0.10~1.00时，患者净获益率大于0。校准曲线分析、Hosmer-Lemeshow拟合优度检验、外部验证均显示该模型预测效能良好。
结论该模型对肾损伤患者的区分度较高，对临床决策具有一定指导价值，但需要多中心数据对模型进行进一步优化。
Abstract:ObjectiveTo construct a clinical prediction model of early renal injury in patients with Henoch-SchÖnlein purpura and verify its effectiveness.
MethodsThere are 165 patients with immunoglobulin A(IgA)vasculitis were selected as research objects. Patients were divided into kidney injury group (65 cases) and no kidney injury group (100 cases) according to whether the disease involved in kidney or not. Clinical data (general data including age, sex, height, body weight, heart rate, living environment, and laboratory indicators including neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio) were collected at admission. Single-factor Logistic regression analysis was used to screen the high-risk factors, and the clinical prediction model was established with the method of step by step. The model was visualized by running the rms package with R4.2.2 software. The prediction performance of the model was evaluated from three aspects: model differentiation degree, calibration degree, and extensibility (accuracy and stability). The model was internally verified by ten-fold cross-validation and Bootstrap method, and externally verified by time period validation.
ResultsThere were statistically significant differences in living environment, heart rate, platelet-to-lymphocyte ratio, platelet count, lactate dehydrogenase, interleukin-6, urinary β2-microglobulin and urinary microalbumin between two groups (P < 0.05). Single-factor Logistic regression analysis showed that living environment, heart rate, platelet-to-lymphocyte ratio, interleukin-6, urinary β2-microglobulin and urinary microalbumin were the influencing factors of early kidney injury in IgAV patients (P < 0.05). A clinical prediction model for early kidney injury in IgAV patients was established based on the influencing factors, and random split 10-fold cross-validation and Bootstrap repeated sampling 1 000 times showed that the model had good accuracy and stability. The area under the curve (AUC) of receiver operating characteristic curve of the model was 0.87. Decision curve analysis showed that when the probability threshold of kidney injury in IgA vasculitis patients predicted by this model was 0.10 to 1.00, the net benefit rate of patients was greater than 0. Calibration curve analysis, Hosmer-Lemeshow goodness of fit test, and external validation all showed that the model had good predictive performance.
ConclusionThe model can distinguish patients with kidney injury of IgAV in a high degree of differentiation and has a certain guiding value for clinical decision-making. The model would be perfect with multi-center data in the future.
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Keywords:
- vasculitis /
- Henoch-Schönlein purpura /
- kidney injury /
- risk factors /
- prediction model
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表 1 2组临床资料比较(x±s)[M(P25, P75)][n(%)]
临床资料 无肾损伤组(n=100) 有肾损伤组(n=65) χ2/t/z P 性别 女 54(54.00) 25(38.46) 3.811 0.051 男 46(46.00) 40(61.54) 农村 56(56.00) 51(78.46) 8.719 0.003 城市 44(44.00) 14(21.54) 年龄/岁 9.04±3.76 9.23±3.35 -0.331 0.741 体质量指数/(kg/m2) 18.49±4.54 18.24±4.27 0.344 0.731 心率/(次/min) 91.46±12.14 83.65±12.40 4.007 < 0.001 NLR 2.09(1.43, 3.40) 2.34(1.59, 3.91) -1.497 0.766 PLR 118.86(93.78, 158.44) 160.03(113.04, 215.98) 1.714 0.006 血小板计数/(×109/L) 256.23±82.82 297.02±69.04 -3.294 0.001 血肌酐/(μmol/L) 39.41±16.69 39.68±14.56 -0.106 0.916 乳酸脱氢酶/(U/L) 251.41±76.33 225.95±63.38 2.234 0.027 IL-6/(pg/mL) 8.02±7.75 10.84±7.87 -2.263 0.025 尿素氮/(mmol/L) 4.20±1.25 4.08±1.14 0.666 0.506 尿β2-微球蛋白/(μg/L) 49.00(25.25, 161.75) 223.00(41.50, 627.00) 2.235 < 0.001 尿微量白蛋白/(mg/L) 12.00(5.25, 18.98) 26.00(8.00, 47.55) 2.979 < 0.001 尿微量白蛋白/肌酐 0.31(0.12, 0.50) 0.82(0.34, 1.63) 3.013 < 0.001 NLR: 中性粒细胞与淋巴细胞的比值; PLR: 血小板与淋巴细胞的比值; IL-6: 白细胞介素-6。 
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表 2 IgAV患者发生肾损伤的单因素Logistic回归分析结果
变量 β SE Wald P OR 95% CI 生活环境 1.193 0.479 6.139 0.013 3.296 1.288~8.431 心率 -0.056 0.020 7.814 0.005 0.946 0.910~0.984 PLR 0.004 0.002 4.994 0.025 1.004 1.000~1.007 血小板计数 0.005 0.003 3.745 0.053 1.005 1.000~1.010 乳酸脱氢酶 -0.001 0.003 0.013 0.749 0.999 0.992~1.005 IL-6 0.079 0.028 8.184 0.004 1.082 1.025~1.143 尿β2-微球蛋白 0.003 0.001 5.920 0.015 1.003 1.000~1.005 尿微量白蛋白 0.031 0.014 4.629 0.031 1.031 1.003~1.061
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