基于实验室指标的系统性红斑狼疮鉴别诊断列线图的构建及评估

doi:10.3969/j.issn.1674-8115.2024.02.006

上海交通大学学报（医学版） ›› 2024, Vol. 44 ›› Issue (2): 204-211.doi: 10.3969/j.issn.1674-8115.2024.02.006

• 论著 · 临床研究 • 上一篇

基于实验室指标的系统性红斑狼疮鉴别诊断列线图的构建及评估

杨婧偊¹(), 陈留宝², 王康太², 杨兴智¹, 于海涛¹^,³()

^1.兰州大学第一临床医学院，兰州 730000
^2.兰州大学第一医院信息中心，兰州 730000
^3.兰州大学第一医院医学检验中心，兰州 730000

收稿日期:2023-07-05 接受日期:2023-11-30 出版日期:2024-02-28 发布日期:2024-03-25
通讯作者: 于海涛 E-mail:13688496031@163.com;yuhaitao7707@163.com
作者简介:杨婧偊（1992—），女，硕士生；电子信箱：13688496031@163.com。
基金资助:
国家自然科学基金(81960388);甘肃省科技计划项目(23JRRA0957);兰州市科技计划项目(2023-2-37);兰州大学医学科研创新能力提升项目(lzuyxcx-2022-165);兰州市城关区科技计划项目(2020-2-11-3)

Establishment and evaluation of nomogram for differential diagnosis of systemic lupus erythematosus based on laboratory indications

YANG Jingyu¹(), CHEN Liubao², WANG Kangtai², YANG Xingzhi¹, YU Haitao¹^,³()

^1.The First School of Clinical Medicine of Lanzhou University, Lanzhou 730000, China
^2.Information Center, The First Hospital of Lanzhou University, Lanzhou 730000, China
^3.Department of Clinical Laboratory, The First Hospital of Lanzhou University, Lanzhou 730000, China

Received:2023-07-05 Accepted:2023-11-30 Online:2024-02-28 Published:2024-03-25
Contact: YU Haitao E-mail:13688496031@163.com;yuhaitao7707@163.com
Supported by:
National Natural Science Foundation of China(81960388);Science and Technology Plan Project of Gansu Province(23JRRA0957);Science and Technology Plan Project of Lanzhou City(2023-2-37);Lanzhou University Medical Research Improvement Project(lzuyxcx-2022-165);Science and Technology Plan Project of Chengguan District of Lanzhou City(2020-2-11-3)

摘要/Abstract

摘要：

目的·基于实验室指标，建立早期系统性红斑狼疮（systemic lupus erythmatosus，SLE）与其他自身免疫性疾病鉴别诊断的列线图并评估其效能。方法·选择2017年1月—2021年12月在兰州大学第一医院就诊的535例SLE患者（SLE组）以及同时期的535例其他自身免疫性疾病患者（对照组）。收集并比较2组患者的基础信息及实验室检查指标（共116项）。将SLE组和对照组分别按7∶3的比例随机分为训练集和验证集，采用LASSO回归、多因素Logistic回归筛选SLE的主要危险因子，并建立早期SLE鉴别诊断列线图（简称“SLE列线图”）。使用Bootstrap法行内部重复抽样1 000次对列线图进行校准，分别利用受试者操作特征曲线（receiver operator characteristic curve，ROC曲线）、决策曲线分析（decision curve analysis，DCA）评估SLE列线图的鉴别诊断的能力以及在临床应用中的价值。采用R语言“DynNom”包将列线图转换为电子计算器，并通过3组患者数据对其与SLE列线图的一致性进行验证。结果·LASSO回归和多因素Logistic回归共筛选出6个SLE的主要危险因子，即抗核抗体（antinuclear antibody，ANA）、抗双链DNA（anti-double-stranded DNA，anti-dsDNA）抗体、抗核糖核蛋白抗体/史密斯抗体（anti-ribonucleoprotein antibody/anti-Simth antibody，anti-nRNP/Sm）、抗核糖体P蛋白（anti-ribosomal P protein，anti-P）抗体、抗核小体抗体（anti-nucleosome antibody，ANuA）、尿蛋白（urinary protein，PRO），并由该6个因子共同构建SLE列线图。该列线图的校准曲线在训练集和验证集的标准误分别为0.009和0.015，其ROC曲线下面积分别为0.889和0.869。DCA的结果显示，当SLE列线图的风险阈概率在0.15~0.95时，该列线图取得的净获益较高。电子计算器的预测结果显示，1号SLE患者的ANA（滴度1∶100）为阳性，其患病率为0.166；2号患者的ANA（滴度1∶100）、ANuA（滴度1∶100）均为阳性，其患病率为0.676；3号患者的PRO、ANA（滴度1∶100）、ANuA（滴度1∶100）、anti-P抗体（滴度1∶100）均为阳性，其患病率为0.990，这与SLE列线图鉴别诊断的结果相一致。结论·基于ANA、anti-dsDNA抗体、anti-nRNP/Sm、anti-P抗体、ANuA、PRO建立的SLE列线图以及转换成的电子计算器可较好地鉴别SLE早期和其他自身免疫性疾病，具有重要的临床应用价值。

关键词: 列线图, 系统性红斑狼疮, 自身免疫性疾病, 鉴别诊断, 电子计算器

Abstract:

Objective ·To establish a nomogram for the differential diagnosis of early systemic lupus erythematosus (SLE) and other autoimmune diseases based on laboratory indications, and to evaluate its efficacy. Methods ·A total of 535 SLE patients admitted to the First Hospital of Lanzhou University from January 2017 to December 2021 were selected as SLE group, and 535 patients with other autoimmune diseases during the same period were selected as control group. Basic information and laboratory test indicators of the SLE group and control group were collected and compared. The SLE group and control group were randomly assigned to the training set and the validation set at a ratio of 7∶3, respectively. LASSO regression method and multivariate Logistic regression were used to select the main risk factors of SLE. The nomogram for differential diagnosis of early SLE (SLE nomogram) was established according to the selected main risk factors. Bootstrap method was used to conduct internal repeated sampling for 1 000 times to calibrate the nomogram. The receiver operator characteristic curve (ROC curve) and decision curve analysis (DCA) were performed to evaluate the differential diagnosis ability and the value in clinical application of SLE nomogram, respectively. The "DynNom" package of R language was used to convert the nomogram into an electronic calculator, and its consistency with SLE nomogram was verified by data from 3 groups of patients. Results ·LASSO regression and multivariate Logistic regression identified six major risk factors for SLE, including antinuclear antibody (ANA), anti-double-stranded DNA (anti-dsDNA) antibody, anti-ribonucleoprotein antibody/anti-Simth antibody (anti-nRNP/Sm), anti-ribosomal P protein (anti-P) antibody, anti-nucleosome antibody (ANuA) and urinary protein (PRO), which were used to construct the SLE nomogram. The calibration curve of the SLE nomogram had standard errors of 0.009 and 0.015 in the training set and validation set, respectively, and its area under the curve (AUC) was 0.889 and 0.869, respectively. The results of DCA showed that when the risk threshold of SLE nomogram was 0.15?0.95, the model achieved more net benefit. The prediction results of the electronic calculator showed that when ANA (titer 1∶100) was positive in SLE patient No.1, the prevalence was 0.166; when both ANA (titer 1∶100) and ANuA (titer 1∶100) were positive in patient No.2, the prevalence was 0.676; when all of PRO, ANA (titer 1∶100), ANuA (titer 1∶100) and anti-P antibody (titer 1∶100) were positive in patient No.3, the prevalence was 0.990, which was consistent with the differential diagnosis results of the SLE nomogram. Conclusion ·The established SLE nomogram based on ANA, anti-dsDNA antibody, anti-nRNP/Sm, anti-P antibody, ANuA and PRO and its conversion into an electronic calculator can effectively distinguish early SLE from other autoimmune diseases, and have important clinical application value.

Key words: nomogram, systemic lupus erythematosus (SLE), autoimmune disease, differential diagnosis, electronic calculator

中图分类号:

R593.24⁺1

杨婧偊, 陈留宝, 王康太, 杨兴智, 于海涛. 基于实验室指标的系统性红斑狼疮鉴别诊断列线图的构建及评估[J]. 上海交通大学学报（医学版）, 2024, 44(2): 204-211.

YANG Jingyu, CHEN Liubao, WANG Kangtai, YANG Xingzhi, YU Haitao. Establishment and evaluation of nomogram for differential diagnosis of systemic lupus erythematosus based on laboratory indications[J]. Journal of Shanghai Jiao Tong University (Medical Science), 2024, 44(2): 204-211.

图/表 5

图1 与SLE相关的主要危险因子筛选Note： A. LASSO coefficient curves for 79 indicators according to log(λ). The colored lines represent the influence of λ value in the model on the weight coefficients of different indicators. The dashed line represents the best λ value and its number of indicators. B. Selection of the indicators by LASSO at the optimal parameter (λ). C. Multivariate Logistic regression analysis of major risk indicators. TP—total protein; Pos—positive; Neg—negative.

Fig 1 Selection of major risk indicators related to SLE

表1 训练集和验证集患者的6项SLE主要危险因子比较

Tab 1 Comparison of six major risk factors for SLE in patients between training set and validation set

Risk factor	Training set (n=758)		Validation set (n=312)		P value
Risk factor	SLE group	Control group	SLE group	Control group	P value
PRO
Pos	227 (29.95)	81 (10.69)	87 (27.88)	30 (9.62)	0.999
Neg	152 (20.05)	298 (39.31)	69 (22.12)	126 (40.38)
Anti-dsDNA antibody (titer 1∶10)
Pos	157 (20.71)	10 (1.32)	61 (19.55)	5 (1.60)	1.000
Neg	222 (29.29)	369 (48.68)	95 (30.45)	151 (48.40)
Anti-nRNP/Sm (titer 1∶100)
Pos	179 (23.61)	20 (2.64)	51 (16.35)	10 (3.21)	0.274
Neg	200 (26.39)	359 (47.36)	105 (33.65)	146 (46.79)
ANA (titer 1∶100)
Pos	342 (45.12)	252(33.25)	143 (45.83)	108 (34.62)	1.000
Neg	37 (4.88)	127 (16.75)	13 (4.17)	48 (15.38)
ANuA (titer 1∶100)
Pos	128 (16.89)	4 (0.53)	52 (16.67)	0 (0)	1.000
Neg	251 (33.11)	375 (49.47)	104 (33.33)	156 (50.00)
Anti-P antibody (titer 1∶100)
Pos	102 (13.46)	6 (0.79)	35 (11.22)	2 (0.64)	0.999
Neg	277 (36.54)	373 (49.21)	121 (38.78)	154 (49.36)

图2 SLE列线图

Fig 2 Nomogram of SLE

图3 SLE列线图鉴别诊断的性能验证Note： A. Calibration curve of the training set. B. Calibration curve of the validation set. C. ROC curve of the training set and validation set. D. DCA curve of the training set.

Fig 3 Performance verification of nomogram for differential diagnosis of SLE

图4 SLE鉴别诊断的电子计算器Note： A. Patient data input interface. B. Patient risk output interface.

Fig 4 Electronic calculator for differential diagnosis of SLE

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基于实验室指标的系统性红斑狼疮鉴别诊断列线图的构建及评估

Establishment and evaluation of nomogram for differential diagnosis of systemic lupus erythematosus based on laboratory indications

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