抗黑色素瘤分化相关蛋白5阳性皮肌炎患者严重间质性肺病风险预测:STRAD-Ro52模型

Annals of medicine Pub Date : 2025-12-01 Epub Date: 2024-12-19 DOI:10.1080/07853890.2024.2440621
Fei Xiao, Feilong Chen, DongSheng Li, Songyuan Zheng, Xiao Liang, Juan Wu, JunYuan Zhong, Xiangliang Tan, Rui Chen, Junqing Zhu, Shixian Chen, Juan Li
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引用次数: 0

摘要

目的:抗黑色素瘤分化相关基因5阳性皮肌炎相关间质性肺疾病(MDA5+DM-ILD)常导致急性呼吸衰竭,危及生命。本研究定量分析胸部高分辨率计算机断层扫描(HRCT)图像,评估MDA5+DM-ILD,并建立6个月内严重ILD的风险预测模型。方法:我们开发了一种“标准化阈值比分析与分布”(STRAD)来分析肺部HRCT图像。本回顾性研究纳入51例MDA5+DM- ild患者,根据MDA5+DM诊断后6个月内急性呼吸衰竭的发生情况分为重度ild组和非重度ild组。比较两组患者的STRAD参数、临床指标及治疗方法。采用最小绝对收缩和选择算子(LASSO)回归选择最佳的STRAD参数。多因素分析选择临床因素进一步与STRAD联合,以提高最终模型(STRAD- ro52模型)的预测性能。结果:两组患者STRAD参数、抗ro52抗体滴度、抗ro52抗体存在情况、年龄、ESR、ALB、Pa/FiO2、IgM、IL-4水平差异均有统计学意义。STRAD参数与人口统计学、炎症、器官功能和免疫学指标有显著相关。Lasso logistic回归分析发现-699 ~ -650 HU肺组织比例(%V7)是预测严重ILD和S6·%V7的最佳参数,%V7在肺中部的分布是最佳空间参数。临床指标多因素回归显示抗ro52抗体的存在是严重ILD的独立危险因素,由此建立STRAD-Ro52模型。结论:STRAD-Ro52模型有助于识别MDA5+DM患者在6个月内发展为严重ILD的风险,进一步优化精确的疾病管理和临床研究设计。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Severe interstitial lung disease risk prediction in anti-melanoma differentiation-associated protein 5 positive dermatomyositis: the STRAD-Ro52 model.

Objective: Anti-melanoma differentiation-associated gene 5-positive dermatomyositis-associated interstitial lung disease (MDA5+DM-ILD) often leads to acute respiratory failure and endangers lives. This study quantitatively analysed chest high-resolution computed tomography (HRCT) images to assess MDA5+DM-ILD and establish a risk prediction model for severe ILD within six months.

Methods: We developed a 'Standardized Threshold Ratio Analysis & Distribution' (STRAD) to analyse lung HRCT images. In this retrospective study, 51 patients with MDA5+DM-ILD were included and divided into severe-ILD and non-severe-ILD groups based on the occurrence of acute respiratory failure within six months post-diagnosis of MDA5+DM. The STRAD parameters, clinical indicators and treatments were compared between the two groups. Least absolute shrinkage and selection operator (LASSO) regression was used to select the optimal STRAD parameters. Multivariate analysis selected clinical factors to be further combined with STRAD to enhance the predictive performance of the final model (STRAD-Ro52 model).

Results: Significant differences were observed between the two groups in STRAD parameters, anti-Ro52 antibody titers, presence of anti-Ro52 antibodies, age, ESR, ALB, Pa/FiO2, IgM and IL-4 levels. The STRAD parameters were significantly correlated with demographic, inflammatory, organ function and immunological indicators. Lasso logistic regression analysis identified the -699 to -650 HU lung tissue proportion (%V7) as the optimal parameter for predicting severe ILD and S6·%V7, and the distribution of %V7 in the mid lungs was the optimal space parameter. Multifactorial regression of clinical indicators showed that the presence of anti-Ro52 antibodies was an independent risk factor for severe ILD, leading to the establishment of the STRAD-Ro52 model.

Conclusions: The STRAD-Ro52 model assists in identifying MDA5+DM patients at risk of developing severe ILD within six months, further optimizing precise disease management and clinical research design.

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