SLESIS-R:基于 RELESSER 前瞻性队列的系统性红斑狼疮患者严重感染预测评分改进版

IF 3.7 2区 医学 Q1 RHEUMATOLOGY Lupus Science & Medicine Pub Date : 2024-04-01 DOI:10.1136/lupus-2023-001096
Iñigo Rua-Figueroa, M Jesus García de Yébenes, Julia Martinez-Barrio, Maria Galindo Izquierdo, Jaime Calvo Alén, Antonio Fernandez-Nebro, Raúl Menor-Almagro, Loreto Carmona, Beatriz Tejera Segura, Eva Tomero, Mercedes Freire-González, Clara Sangüesa, Loreto Horcada, Ricardo Blanco, Esther Uriarte Itzazelaia, Javier Narváez, José Carlos Rosas Gómez de Salazar, Silvia Gómez-Sabater, Claudia Moriano Morales, Jose L Andreu, Vicente Torrente Segarra, Elena Aurrecoechea, Ana Perez, Javier Nóvoa Medina, Eva Salgado, Nuria Lozano-Rivas, Carlos Montilla, Esther Ruiz-Lucea, Marta Arevalo, Carlota Iñiguez, María Jesús García-Villanueva, Lorena Exposito, Mónica Ibáñez-Barceló, Gema Bonilla, Irene Carrión-Barberà, Celia Erausquin, Jorge Juan Fragio Gil, Angela Pecondón, Francisco J Toyos, Tatiana Cobo, Alejandro Muñoz-Jiménez, Jose Oller, Joan M Nolla, J M Pego-Reigosa
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Methods We used data from the prospective phase of RELESSER (RELESSER-PROS), the SLE register of the Spanish Society of Rheumatology. A multivariable logistic model was constructed taking into account the variables already forming the SLESIS score, plus all other potential predictors identified in a literature review. Performance was analysed using the C-statistic and the area under the receiver operating characteristic curve (AUROC). Internal validation was carried out using a 100-sample bootstrapping procedure. ORs were transformed into score items, and the AUROC was used to determine performance. Results A total of 1459 patients who had completed 1 year of follow-up were included in the development cohort (mean age, 49±13 years; 90% women). Twenty-five (1.7%) had experienced ≥1 severe infection. 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引用次数: 0

摘要

目的 开发一种用于预测系统性红斑狼疮(SLE)患者严重感染的改良评分,即系统性红斑狼疮严重感染评分-修订版(SLE Severe Infection Score-Revised,SLESIS-R),并在大型多中心狼疮队列中进行验证。方法 我们使用了西班牙风湿病学会系统性红斑狼疮登记册 RELESSER(RELESSER-PROS)前瞻性阶段的数据。考虑到已形成 SLESIS 评分的变量,以及文献综述中确定的所有其他潜在预测因素,我们构建了一个多变量逻辑模型。使用 C 统计量和接收者工作特征曲线下面积 (AUROC) 分析其性能。采用 100 个样本的引导程序进行内部验证。将 ORs 转化为评分项目,并使用 AUROC 来确定性能。结果 共有 1459 名完成 1 年随访的患者被纳入开发队列(平均年龄为 49±13 岁;90% 为女性)。25人(1.7%)经历过≥1次严重感染。根据调整后的多变量模型,严重感染可由四个变量预测:年龄(岁)≥60、既往系统性红斑狼疮相关住院、既往严重感染和糖皮质激素剂量。根据最佳模型建立一个分值,分值从 0 到 17。AUROC为0.861(0.777-0.946)。选择的临界值为≥6,准确率为 85.9%,阳性似然比为 5.48。结论 SLESIS-R 是预测系统性红斑狼疮患者感染的准确可行的工具。SLESIS-R有助于就免疫抑制剂的使用和预防措施的实施做出明智的决定。如有合理要求,可提供相关数据。
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SLESIS-R: an improved score for prediction of serious infection in patients with systemic lupus erythematosus based on the RELESSER prospective cohort
Objective To develop an improved score for prediction of severe infection in patients with systemic lupus erythematosus (SLE), namely, the SLE Severe Infection Score-Revised (SLESIS-R) and to validate it in a large multicentre lupus cohort. Methods We used data from the prospective phase of RELESSER (RELESSER-PROS), the SLE register of the Spanish Society of Rheumatology. A multivariable logistic model was constructed taking into account the variables already forming the SLESIS score, plus all other potential predictors identified in a literature review. Performance was analysed using the C-statistic and the area under the receiver operating characteristic curve (AUROC). Internal validation was carried out using a 100-sample bootstrapping procedure. ORs were transformed into score items, and the AUROC was used to determine performance. Results A total of 1459 patients who had completed 1 year of follow-up were included in the development cohort (mean age, 49±13 years; 90% women). Twenty-five (1.7%) had experienced ≥1 severe infection. According to the adjusted multivariate model, severe infection could be predicted from four variables: age (years) ≥60, previous SLE-related hospitalisation, previous serious infection and glucocorticoid dose. A score was built from the best model, taking values from 0 to 17. The AUROC was 0.861 (0.777–0.946). The cut-off chosen was ≥6, which exhibited an accuracy of 85.9% and a positive likelihood ratio of 5.48. Conclusions SLESIS-R is an accurate and feasible instrument for predicting infections in patients with SLE. SLESIS-R could help to make informed decisions on the use of immunosuppressants and the implementation of preventive measures. Data are available upon reasonable request.
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来源期刊
Lupus Science & Medicine
Lupus Science & Medicine RHEUMATOLOGY-
CiteScore
5.30
自引率
7.70%
发文量
88
审稿时长
15 weeks
期刊介绍: Lupus Science & Medicine is a global, peer reviewed, open access online journal that provides a central point for publication of basic, clinical, translational, and epidemiological studies of all aspects of lupus and related diseases. It is the first lupus-specific open access journal in the world and was developed in response to the need for a barrier-free forum for publication of groundbreaking studies in lupus. The journal publishes research on lupus from fields including, but not limited to: rheumatology, dermatology, nephrology, immunology, pediatrics, cardiology, hepatology, pulmonology, obstetrics and gynecology, and psychiatry.
期刊最新文献
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