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

ABSTRACT: 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.

SUBMITTER: Xue J

PROVIDER: S-EPMC9245420 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:ObjectivePatients at high risk of rheumatoid arthritis-associated interstitial lung disease (RA-ILD) would benefit from being identified before the onset of respiratory symptoms; this can be done by screening patients with the use of chest high-resolution computed tomography (HRCT). Our objective was to develop and validate a risk score for patients who have subclinical RA-ILD.MethodsOur study included a discovery population and a replication population from 2 prospective RA cohorts (ESPOIR and TRANSLATE2, respectively) without pulmonary symptoms who had received chest HRCT scans. All patients were genotyped for MUC5B rs35705950. After multiple logistic regression, a risk score based on independent risk factors for subclinical RA-ILD was developed in the discovery population and tested for validation in the replication population.ResultsThe discovery population included 163 patients with RA, and the replication population included 89 patients with RA. The prevalence of subclinical RA-ILD was 19.0% and 16.9%, respectively. In the discovery population, independent risk factors for subclinical RA-ILD were presence of the MUC5B rs35705950 T allele (odds ratio [OR] 3.74 [95% confidence interval (95% CI) 1.37, 10.39]), male sex (OR 3.93 [95% CI 1.40, 11.39]), older age at RA onset (for each year, OR 1.10 [95% CI 1.04, 1.16]), and increased mean Disease Activity Score in 28 joints using the erythrocyte sedimentation rate (for each unit, OR 2.03 [95% CI 1.24, 3.42]). We developed and validated a derived risk score with receiver operating characteristic areas under the curve of 0.82 (95% CI 0.70-0.94) for the discovery population and 0.78 (95% CI 0.65-0.92) for the replication population. Excluding MUC5B rs35705950 from the model provided a lower goodness of fit (likelihood ratio test, P = 0.01).ConclusionWe developed and validated a risk score that could help identify patients at high risk of subclinical RA-ILD. Our findings support an important contribution of MUC5B rs35705950 to subclinical RA-ILD risk.

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

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