基于超声评分参数及临床指标的列线图鉴别原发性干燥综合征与IgG4相关唾液腺炎

doi:10.3969/j.issn.1674-8115.2025.03.015

上海交通大学学报（医学版） ›› 2025, Vol. 45 ›› Issue (3): 373-380.doi: 10.3969/j.issn.1674-8115.2025.03.015

基于超声评分参数及临床指标的列线图鉴别原发性干燥综合征与IgG4相关唾液腺炎

刘楚萱(), 左佳鑫, 熊屏()

上海交通大学医学院附属第九人民医院超声医学科，上海 200011

收稿日期:2024-09-02 接受日期:2024-12-13 出版日期:2025-03-28 发布日期:2025-03-28
通讯作者: 熊　屏，主任医师，博士；电子信箱：xiong_ping_xp@163.com。
作者简介:刘楚萱（1999—），女，硕士生；电子信箱：lcx1999takemone@163.com。
基金资助:
上海交通大学医学院附属第九人民医院“交叉”研究基金(JYJC202132);上海交通大学医学院附属第九人民医院学科群建设项目

A nomogram based on ultrasound scoring parameters and clinical indicators for differentiating primary Sjὅgren′s syndrome from IgG4-related sialadenitis

LIU Chuxuan(), ZUO Jiaxin, XIONG Ping()

Department of Ultrasound, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200011, China

Received:2024-09-02 Accepted:2024-12-13 Online:2025-03-28 Published:2025-03-28
Contact: XIONG Ping, E-mail: xiong_ping_xp@163.com.
Supported by:
Cross-Disciplinary Research Fund Project of Shanghai Ninth People′s Hospital, Shanghai Jiao Tong University School of Medicine(JYJC202132);Discipline Cluster Construction Project of Shanghai Ninth People′s Hospital, Shanghai Jiao Tong University School of Medicine

摘要/Abstract

摘要：

目的·基于超声评分参数及临床指标，构建鉴别原发性干燥综合征（primary Sjὅgren′s syndrome，PSS）与免疫球蛋白G4相关唾液腺炎（immunoglobulin G4-related sialadenitis，IgG4-RS）列线图并评估其性能。方法·回顾性选择2018年1月—2023年12月就诊于上海交通大学医学院附属第九人民医院的PSS患者141例和IgG4-RS患者31例。收集患者的超声评分参数，包括腮腺超声（parotid gland ultrasound，PGUS）评分、下颌下腺超声（submandibular gland ultrasound，SMGUS）评分、唾液腺超声（salivary gland ultrasound，SGUS）评分，及临床指标包括性别、年龄、抗SSB/La抗体、抗SSA/Ro60抗体、抗SSA/Ro52抗体、IgG、类风湿因子（rheumatoid factor，RF）。利用最小绝对收缩和选择算子（least absolute shrinkage and selection operator，LASSO）回归筛选出最优超声评分参数和临床指标，建立PSS和IgG4-RS的鉴别诊断列线图。通过bootstrap法进行模型的内部验证。分别采用受试者操作特征（receiver operator characteristic，ROC）曲线、校准曲线及决策曲线分析（decision curve analysis，DCA）评价模型的区分度、校准度及其在临床中的应用价值。结果·通过LASSO回归算法，共筛选出性别、年龄、抗SSA/Ro60抗体、抗SSA/Ro52抗体、PGUS评分、SMGUS评分6个变量，根据该6个指标建立列线图模型。该列线图模型的ROC曲线显示曲线下面积（area under the curve，AUC）为0.976，具有较强的区分度。bootstrap法内部重复抽样1 000次进行验证，平均绝对误差0.018，校准曲线表明预测值与实测值良好吻合。DCA表明该列线图具有一定的临床实用性。结论·基于超声评分参数及临床指标建立的列线图，在鉴别PSS和IgG4-RS方面展示了良好的区分度和校准度，有望为临床鉴别诊断2种疾病及制定相应治疗方案提供参考。

关键词: 超声评分系统, 原发性干燥综合征, 免疫球蛋白G4相关唾液腺炎, 鉴别诊断, 列线图

Abstract:

Objective ·To construct and validate a nomogram for distinguishing primary Sjὅgren′s syndrome (PSS) from immunoglobulin G4-related sialadenitis (IgG4-RS) based on ultrasound scoring parameters and clinical indicators. Methods ·A total of 141 patients with PSS and 31 patients with IgG4-RS were retrospectively recruited from Shanghai Ninth People′s Hospital, Shanghai Jiao Tong University School of Medicine from January 2018 to December 2023. The ultrasound scoring parameters, including parotid gland ultrasound (PGUS) score, submandibular gland ultrasound (SMGUS) score, and salivary gland ultrasound (SGUS) score, along with clinical indicators such as gender, age, anti-SSB/La antibody, anti-SSA/Ro60 antibody, anti-SSA/Ro52 antibody, IgG, and rheumatoid factor (RF), were collected. The optimal US scoring parameters and clinical indicators were screened by least absolute shrinkage and selection operator (LASSO) regression, and a nomogram model was constructed to distinguish PSS from IgG4-RS. The internal validation of the model was carried out through bootstrap method. Receiver operator characteristic (ROC) curve, calibration curve and decision curve analysis (DCA) were used to estimate the discrimination, calibration, and clinical utility of the nomogram model, respectively. Results ·LASSO regression identified six major variables: gender, age, anti-SSA/Ro60 antibody, anti-SSA/Ro52 antibody, PGUS score, and SMGUS score. These variables were used to construct the nomogram. ROC curve of the nomogram showed that the area under the curve (AUC) was 0.976, indicating the nomogram had strong discrimination ability. The bootstrap method was used for internal validation with 1 000 resampling iterations, and the average absolute error was 0.018. Calibration curve demonstrated good agreement between predicted and observed values. DCA indicated that the nomogram had certain clinical utility. Conclusion ·The nomogram based on ultrasound scoring parameters and clinical indicators demonstrates excellent discrimination and calibration in differentiating PSS from IgG4-RS. It has the potential to assist in clinical diagnosis and decision-making.

Key words: ultrasound scoring system, primary sj?gren′s syndrome, IgG4-related sialadenitis, differential diagnosis, nomogram

中图分类号:

R445.1

刘楚萱, 左佳鑫, 熊屏. 基于超声评分参数及临床指标的列线图鉴别原发性干燥综合征与IgG4相关唾液腺炎[J]. 上海交通大学学报（医学版）, 2025, 45(3): 373-380.

LIU Chuxuan, ZUO Jiaxin, XIONG Ping. A nomogram based on ultrasound scoring parameters and clinical indicators for differentiating primary Sjὅgren′s syndrome from IgG4-related sialadenitis[J]. Journal of Shanghai Jiao Tong University (Medical Science), 2025, 45(3): 373-380.

图/表 7

表1 PSS和IgG4-RS患者的临床特征和超声评分参数

Tab 1 Clinical indicators and ultrasound scoring parameters of PSS and IgG4-RS patients

Characteristic	PSS (n=141)	IgG4-RS (n=31)	P value
Gender/n (%)			<0.001
Male	9(6.4)	15(48.4)
Female	132(93.6)	16(51.6)
Age/year	49.28±13.19	59.71±11.40	<0.001
Anti-SSB/La antibody/n (%)			<0.001
Negative	91(64.5)	31(100.0)
Positive	50(35.5)	0(0)
Anti-SSA/Ro60 antibody/n (%)			<0.001
Negative	29(20.6)	31(100.0)
Positive	112(79.4)	0(0)
Anti-SSA/Ro52 antibody/n (%)			<0.001
Negative	24(17.0)	30(96.8)
Positive	117(83.0)	1(3.2)
IgG/g·L^-1	18.55±5.12	21.55±10.86	0.142
RF/n (%)			0.003
Negative	63(44.7)	23(74.2)
Positive	78(55.3)	8(25.8)
PGUS/score	13.40±4.17	7.32±3.49	<0.001
SMGUS/score	11.67±3.74	16.32±4.11	<0.001
SGUS/score	25.07±6.54	23.65±5.08	0.256

表2 超声评分参数的一致性分析

Tab 2 Agreement of ultrasound scoring parameters

Ultrasound/score	Intraobserver ICC (95%CI)	Interobserver ICC (95%CI)
PGUS	0.944 (0.923‒0.959)	0.927 (0.901‒0.947)
SMGUS	0.943 (0.919‒0.959)	0.918 (0.890‒0.939)
SGUS	0.936 (0.903‒0.957)	0.914 (0.879‒0.938)

图1 通过LASSO回归算法筛选最优临床指标和超声参数Note： A. Path diagram of the LASSO coefficient. The ordinate represents the regression coefficients of different variables, while the lower abscissas shows the logarithm of the penalty coefficient (λ), and the upper abscissas shows the number of variables with non-zero coefficients corresponding to different log λ values. Different colored lines represent different variables. B. Cross-verification curve of LASSO regression. The ordinate represents binomial deviance. A smaller deviance indicates better model performance. The upper and lower abscissas are the same as in Figure A. The left dashed line in Figure B indicates the number of variables corresponding to the minimum λ (when the model fits best), and the number of variables is 7. The right dashed line indicates one standard error above the minimum λ (when the model performs relatively well), and the number of variables is 6.

Fig 1 Selection of clinical indicators and ultrasound data by LASSO regression

图2 PSS与IgG4-RS鉴别诊断列线图

Fig 2 Nomogram for differential diagnosis of PSS and IgG4-RS

图3 列线图鉴别诊断的性能评估Note： A. ROC curve of the nomogram B. Calibration curve of the nomogram. The x-axis represents the predicted probabilities from the nomogram model, while the y-axis reflects the actual probabilities. The ideal line (black dashed line) indicates perfect calibration, while predicted probabilities align exactly with actual probabilities. The apparent line (gray dashed line) illustrates the observed performance of the nomogram model, while the bias-corrected line (black solid line) shows the model′s performance after 1 000 repetitions of bootstrapping. C. DCA curve of the nomogram. The x-axis represents different probability thresholds, while the y-axis shows the net benefit. The black horizontal line indicates no intervention for any patients, the gray solid line represents intervention for all patients, and the red solid line reflects interventions guided by the nomogram.

Fig 3 Performance evaluation of the nomogram for differential diagnosis

图4 列线图诊断PSS的实际应用Note： A 60-year-old female with PSS, positive for anti-SSA/Ro60 antibody and anti-SSA/Ro52 antibody. A. The ultrasound images of bilateral parotid gland showed a PGUS score of 24. The ultrasound images of bilateral submandibular gland showed a SMGUS score of 22. B. According to the nomogram, the prediction probability of PSS was greater than 90.00%.

Fig 4 Practical application of the nomogram in PSS diagnosis

图5 列线图诊断IgG4-RS的实际应用Note： A 66-year-old male with IgG4-RS, negative for anti-SSA/Ro60 antibody and anti-SSA/Ro52 antibody. A. The ultrasound images of bilateral parotid gland showed a PGUS score of 4. The ultrasound images of bilateral submandibular gland showed a SMGUS score of 18. B. According to the nomogram, the prediction probability of PSS was less than 10.00%.

Fig 5 Practical application of the nomogram in IgG4-RS diagnosis

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基于超声评分参数及临床指标的列线图鉴别原发性干燥综合征与IgG4相关唾液腺炎

A nomogram based on ultrasound scoring parameters and clinical indicators for differentiating primary Sjὅgren′s syndrome from IgG4-related sialadenitis

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