Clinical decision rule to predict the presence of interstitial lung disease in systemic sclerosis

Objective To develop a clinical decision rule to predict the presence of interstitial lung disease (ILD) in systemic sclerosis (SSc; scleroderma) and to estimate the prevalence of SSc-ILD. Methods. Patient data were extracted from the Canadian Scleroderma Research Group registry. Three algorithms for the clinical decision rule were considered based on lung auscultation, chest radiography (CXR), and % predicted forced vital capacity (FVC). High-resolution computed tomography (HRCT) scans were used as the gold standard to determine the diagnostic properties of the 3 algorithms. Multiple imputation was used to impute HRCT data when missing, thereby avoiding bias due to differential referral for HRCT. Results. This study included 1,168 patients. Of the patients with HRCT scans, 65% had evidence of ILD, compared to 26% by physical examination and 22% by CXR. The FVC of those who did not have HRCT was 8.8% greater than those who did (95% confidence interval [95% CI] 6.0-11.6%). Algorithm A, which identified the presence of ILD based on crackles on lung auscultation and/or findings on CXR, had a likelihood ratio of 3.9, compared to 3.2 for Algorithm B (which included patients with FVC < 70%) and 2.2 for Algorithm C (which included patients with FVC < 80%). The prevalence of ILD in the cohort was estimated to be 52% (95% CI 46-59%). Conclusion. We developed a simple clinical decision rule to predict SSc-ILD with good test characteristics. The prevalence of ILD in a large, unselected SSc cohort was estimated to be 52%.