Prediction of progressive fibrosing interstitial lung disease in patients with systemic sclerosis: insight from the CRDC cohort study.

Background: This study aims to establish a reliable prediction model of progressive fibrosing interstitial lung disease (PF-ILD) in patients with systemic sclerosis (SSc)-ILD, to achieve early risk stratification and to help better in preventing disease progression.

Methods: 304 SSc-ILD patients with no less than three pulmonary function tests within 6-24 months were included. We collected data at baseline and compared differences between SSc patients with and without PF-ILD. Least absolute shrinkage and selection operator regularisation regression and multivariable Cox regression were used to construct the prediction model, which were presented as nomogram and forest plot.

Results: Among the 304 patients with SSc-ILD included, 92.1% were women, with a baseline average age of 46.7 years. Based on the 28 variables preselected by comparison between SSc patients without PF-ILD group (n=150) and patients with SSc PF-ILD group (n=154), a 9-variable prediction model was constructed, including age≥50 years (HR 1.8221, p=0.001), hyperlipidemia (HR 4.0516, p<0.001), smoking history (HR 3.8130, p<0.001), diffused cutaneous SSc subtype (HR 1.9753, p<0.001), arthritis (HR 2.0008, p<0.001), shortness of breath (HR 2.0487, p=0.012), decreased serum immunoglobulin A level (HR 2.3900, p=0.002), positive anti-Scl-70 antibody (HR 1.9573, p=0.016) and usage of cyclophosphamide/mycophenolate mofetil (HR 0.4267, p<0.001). The concordance index after enhanced bootstrap resampling adjustment was 0.874, while the optimism-corrected Brier Score was 0.144 in internal validation.

Conclusion: This study developed the first prediction model for PF-ILD in patients with SSc-ILD, and internal validation showed favourable accuracy and stability of the model.