Credit: Original article published here.
In a recent study, published in Rheumatology International, researchers sought to determine predictive variables for development of interstitial lung disease (ILD) among patients with rheumatoid arthritis (RA), a common complication associated with increased morbidity and mortality.
After retrospective analysis, the study’s lead author, Gouri Mani Koduri, and colleagues developed a novel risk-stratification model for ILD in patients with RA based on 4 clinical variables: age, smoking history, anti-cyclic citrullinated peptide antibodies, and rheumatoid factor.
The investigators reviewed data on 430 patients with RA that was collected across 20 centers between 2010 and 2020. Of the participants, 210 had ILD confirmed by high-resolution computed tomography (HRCT).
4 Variables Effectively Predict Interstitial Lung Disease
In independent variable analysis, researchers identified past or present smoking, older age, and rheumatoid factor/anti-cyclic citrullinated peptide positivity as key significant variables associated with risk of developing ILD among patients with RA.
Using multivariate logistic regression models, the study’s authors constructed a 0-9 point scoring system with a threshold at 5 points for differentiating patients as high-risk or low-risk. The report noted the model had an area under the receiver operating characteristic curve of 0.76 (95% CI, 0.71-0.82), as well as a sensitivity and specificity of 86% and 58%, respectively.
Overall, Koduri and colleagues reported their predictive scoring system effectively identified the presence of ILD in patients with RA, and suggested that, “high-risk patients should be considered for investigation with HRCT and monitored closely.”
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