Analysis of the Construction of a Predictive Model for Eosinophilic Chronic Rhinosinusitis

IF 3.7 3区医学 Q2 ALLERGY

Journal of Asthma and Allergy Pub Date : 2024-02-28 DOI:10.2147/jaa.s450514

Shuo Wu, Jiahong Lao, Feitong Jian

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引用次数: 0

Abstract

Purpose: This study aimed to determine indices to diagnose and predict eosinophilic chronic rhinosinusitis (ECRS) during the initial clinic visit.
Patients and Methods: We retrospectively analyzed 116 patients with chronic rhinosinusitis who underwent endoscopic sinus surgery and were classified according to the postoperative pathological diagnosis. General data and various clinical indicators were analyzed, and indicators with statistically significant differences between groups were further incorporated into a multivariate logistic regression to establish a comprehensive prediction model. The receiver operating characteristic (ROC) curve was used to compare the two significant valuable single factors from previous studies, the difference in CT scores between the ethmoid sinus and the sum difference of the maxillary sinus (EM difference) and the absolute value of peripheral blood eosinophil (bEOS), with a comprehensive prediction model.
Results: There were significant differences in history of allergic asthma (p < 0.001), visual analog scale (VAS) score (p=0.005), sino-nasal outcome test-22(SNOT-22) scale score (p=0.004), Lund-Mackay scale score (p=0.017), EM difference (p=0.002), percentage of bEOS (%)(p=0.001), and absolute value of bEOS (× 109/L) (p=0.000) between the two groups (p< 0.05). The history of allergic disease, VAS and bEOS were screened out and included in the comprehensive prediction model. The area under the curve (AUC) of the comprehensive prediction model (0.804)> the AUC of the absolute value of the bEOS (0.764)>the AUC of the EM difference (0.655). The AUC of the EM difference and the comprehensive prediction model were statistically different (P=0.025). There was no statistical difference between the absolute value of bEOS and the AUC of the comprehensive prediction model.
Conclusion: The comprehensive prediction model covering the three aspects of allergic asthma history, VAS score, and bEOS count had the highest AUC compared to the other predictors and had good predictive power for the diagnosis of ECRS.

Keywords: eosinophilic chronic rhinosinusitis, non-eosinophilic chronic rhinosinusitis, prediction model, the difference of the CT scores between the ethmoid sinus and maxillary sinus, European position paper on rhinosinusitis and nasal polyps 2020

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嗜酸性粒细胞慢性鼻炎预测模型构建分析

目的：本研究旨在确定在初诊时诊断和预测嗜酸性粒细胞性慢性鼻炎（ECRS）的指标：我们回顾性分析了116例接受内窥镜鼻窦手术的慢性鼻炎患者，并根据术后病理诊断进行了分类。对一般资料和各种临床指标进行分析，并将组间差异有统计学意义的指标进一步纳入多变量逻辑回归，以建立综合预测模型。利用接收器操作特征曲线（ROC）将以往研究中两个有价值的重要单因素，即乙状窦与上颌窦CT评分总和差值（EM差值）和外周血嗜酸性粒细胞绝对值（bEOS）与综合预测模型进行比较：结果：过敏性哮喘病史（p <0.001）、视觉模拟量表（VAS）评分（p=0.005）、窦鼻结局测试-22（SNOT-22）量表评分（p=0.004）、Lund-Mackay 量表评分（P=0.017）、EM 差值（P=0.002）、bEOS 百分比（%）（P=0.001）、两组间 bEOS 绝对值（×109/L）（P=0.000）（P< 0.05）。筛选出过敏性疾病史、VAS 和 bEOS，并将其纳入综合预测模型。综合预测模型的曲线下面积（AUC）（0.804）>bEOS 绝对值的 AUC（0.764）>EM 差值的 AUC（0.655）。EM 差值和综合预测模型的 AUC 有统计学差异（P=0.025）。bEOS的绝对值与综合预测模型的AUC无统计学差异：关键词：嗜酸性粒细胞慢性鼻炎；非嗜酸性粒细胞慢性鼻炎；预测模型；乙状窦与上颌窦CT评分差值；欧洲鼻炎与鼻息肉立场文件 2020年

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来源期刊

Journal of Asthma and Allergy Medicine-Immunology and Allergy

CiteScore

5.30

自引率

6.20%

发文量

185

审稿时长

16 weeks

期刊介绍： An international, peer-reviewed journal publishing original research, reports, editorials and commentaries on the following topics: Asthma; Pulmonary physiology; Asthma related clinical health; Clinical immunology and the immunological basis of disease; Pharmacological interventions and new therapies. Although the main focus of the journal will be to publish research and clinical results in humans, preclinical, animal and in vitro studies will be published where they shed light on disease processes and potential new therapies.