Suppr超能文献

预测接受低剂量利妥昔单抗治疗的重症肌无力患者短期预后的列线图。

A predictive nomogram for short-term outcomes of myasthenia gravis patients treated with low-dose rituximab.

机构信息

Department of Neurology, Huashan Hospital, Fudan University, Shanghai, China.

Huashan Rare Disease Center, Huashan Hospital, Fudan University, Shanghai, China.

出版信息

CNS Neurosci Ther. 2024 May;30(5):e14761. doi: 10.1111/cns.14761.

Abstract

BACKGROUND

This study aims to establish and validate a predictive nomogram for the short-term clinical outcomes of myasthenia gravis (MG) patients treated with low-dose rituximab.

METHODS

We retrospectively reviewed 108 patients who received rituximab of 600 mg every 6 months in Huashan Hospital and Tangdu Hospital. Of them, 76 patients from Huashan Hospital were included in the derivation cohort to develop the predictive nomogram, which was externally validated using 32 patients from Tangdu Hospital. The clinical response is defined as a ≥ 3 points decrease in QMG score within 6 months. Both clinical and genetic characteristics were included to screen predictors via multivariate logistic regression. Discrimination and calibration were measured by the area under the receiver operating characteristic curve (AUC-ROC) and Hosmer-Lemeshow test, respectively.

RESULTS

Disease duration (OR = 0.987, p = 0.032), positive anti-muscle-specific tyrosine kinase antibodies (OR = 19.8, p = 0.007), and genotypes in FCGR2A rs1801274 (AG: OR = 0.131, p = 0.024;GG:OR = 0.037, p = 0.010) were independently associated with clinical response of post-rituximab patients. The nomogram identified MG patients with clinical response with an AUC-ROC (95% CI) of 0.875 (0.798-0.952) in the derivation cohort and 0.741(0.501-0.982) in the validation cohort. Hosmer-Lemeshow test showed a good calibration (derivation: Chi-square = 3.181, p = 0.923; validation: Chi-square = 8.098, p = 0.424).

CONCLUSIONS

The nomogram achieved an optimal prediction of short-term outcomes in patients treated with low-dose rituximab.

摘要

背景

本研究旨在建立和验证一个预测模型,用于预测接受低剂量利妥昔单抗治疗的重症肌无力(MG)患者的短期临床结局。

方法

我们回顾性分析了在华山医院和唐都医院接受利妥昔单抗(每 6 个月 600mg)治疗的 108 例患者。其中,华山医院的 76 例患者纳入推导队列,以开发预测模型,该模型通过唐都医院的 32 例患者进行外部验证。临床反应定义为 QMG 评分在 6 个月内下降≥3 分。通过多变量逻辑回归筛选包括临床和遗传特征在内的预测因素。通过接受者操作特征曲线(ROC)下面积(AUC-ROC)和 Hosmer-Lemeshow 检验分别测量判别能力和校准度。

结果

疾病持续时间(OR=0.987,p=0.032)、抗肌肉特异性酪氨酸激酶抗体阳性(OR=19.8,p=0.007)和 FCGR2A rs1801274 基因型(AG:OR=0.131,p=0.024;GG:OR=0.037,p=0.010)与利妥昔单抗治疗后患者的临床反应独立相关。该预测模型在推导队列中识别出具有临床反应的 MG 患者的 AUC-ROC(95%CI)为 0.875(0.798-0.952),在验证队列中为 0.741(0.501-0.982)。Hosmer-Lemeshow 检验表明校准良好(推导:卡方=3.181,p=0.923;验证:卡方=8.098,p=0.424)。

结论

该预测模型在预测接受低剂量利妥昔单抗治疗的患者的短期结局方面取得了最佳预测效果。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b97d/11090079/6f02108dcae7/CNS-30-e14761-g001.jpg

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验