4.8 Article

Development of a Risk Nomogram Model for Identifying Interstitial Lung Disease in Patients With Rheumatoid Arthritis

Journal

FRONTIERS IN IMMUNOLOGY
Volume 13, Issue -, Pages -

Publisher

FRONTIERS MEDIA SA
DOI: 10.3389/fimmu.2022.823669

Keywords

nomogram; rheumatoid arthritis; interstitial lung disease; matrix metalloproteinase-3; risk factors

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Funding

  1. National Natural Science Foundation of China [81860132]
  2. Natural Science Foundation of Ningxia [2019AAC03176, 2021AAC03369]

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The aim of this study was to construct a nomogram for identifying interstitial lung disease (ILD) in rheumatoid arthritis (RA) patients. Plasma matrix metalloproteinase-3 (MMP-3) levels were found to be elevated in RA-ILD patients. Several risk factors were identified through regression analysis for the construction of the nomogram. The accuracy of the nomogram was validated and it can serve as a non-invasive tool to assist physicians in treatment decisions for RA patients with ILD.
The clinical features of rheumatoid arthritis (RA)-associated interstitial lung disease (ILD) (RA-ILD) usually manifest to an advanced stage of lung disease, which leads the challenge of early diagnosis and the difficulty in guiding treatments for patients with RA-ILD in clinical settings. The aim of this study was to construct a nomogram for identifying ILD in RA patients. Through the incorporation of the level of matrix metalloproteinase-3 (MMP-3) in plasma, demographics, clinical feature, and laboratory parameters of 223 RA patients (85 RA-ILD) which were grouped as training cohorts and validation cohorts, an identifying nomogram of RA-ILD was built. Candidate variables for the nomogram were screened using univariable analysis and multivariable logistic regression analysis. The accuracy of the diagnostic nomogram was measured via concordance index (C-index), calibration plots, and decision curve analysis (DCA). Results showed that plasma MMP-3 protein was elevated in RA-ILD patients compared with non-ILD RA patients in both training cohorts (p = 0.0475) and validation cohorts (p = 0.0006). Following a final regression analysis, the gender of male, current smoking state, levels of circulating rheumatoid factor (RF), C-reactive protein (CRP), and MMP-3 were identified as risk factors for the construction of the nomogram. The calibration plots further showed a favorable consistency between the identifying nomogram and actual clinical findings. In consistence, the C-index (0.826 for both training cohorts and validation cohorts) indicated the satisfactory discriminative ability of the nomogram. Although the incorporation of MMP-3 failed to significantly improve identified outcomes of the nomogram as determined by DCA, including the level of circulating MMP-3 increased the diagnostic accuracy of the nomogram for ILD in RA patients. Thus, our proposed model can serve as a non-invasive tool to identify ILD in RA patients, which may assist physicians to make treatment decisions for RA patients.

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