Interstitial lung disease (ILD) results in high morbidity and healthcare utilization. Diagnostic delays remain common and often occur in non-pulmonology settings. Screening for ILD in these settings has the potential to reduce diagnostic delays and improve patient outcomes.
Can a pulmonary function test (PFT)-derived diagnostic prediction tool (ILD-Screen) accurately identify incident ILD cases in patients undergoing PFT in non-pulmonology settings.
Clinical and physiologic PFT variables predictive of ILD were identified using iterative multivariable logistic regression models. ILD status was determined using a multi-reader approach. An ILD-Screen score was generated using final regression model coefficients, with a score ≥8 considered positive. ILD-Screen test performance was validated in an independent external cohort and applied prospectively to PFTs over one-year to identify incident ILD cases at our institution.
Variables comprising the ILD-Screen were age, height, total lung capacity, forced expiratory volume in one second, diffusion capacity and PFT indication. The ILD-Screen demonstrated consistent test performance across cohorts, with a sensitivity of 0.79 and specificity of 0.83 when applied prospectively. A positive ILD-Screen strongly predicted ILD (OR 18.6, 95% CI 9.4-36.9) and outperformed common ILD clinical features, including cough, dyspnea, lung crackles and restrictive lung physiology. Prospective ILD-Screen application resulted in a higher proportion of patients undergoing chest CT when compared to a historical control cohort (74% vs. 56%, respectively, p=0.003), with a significantly shorter median time to chest imaging (5.6 vs 21.1 months, respectively, p<0.001).
The ILD-Screen demonstrated good test performance in predicting ILD across diverse geographic settings and when applied prospectively. Systematic ILD-Screen application has the potential to reduce diagnostic delays and facilitate earlier intervention in patients with ILD.

Copyright © 2020. Published by Elsevier Inc.

Author