Development and validation of a clinical, CT, genomic classifier and BAL scoring system for diagnosing idiopathic pulmonary fibrosis

Abstract

Background: The utility of incorporating a usual interstitial pneumonia (UIP) genomic classifier (GC) and bronchoalveolar lavage (BAL) cell count analysis alongside traditional clinical-imaging assessment in aiding in the multidisciplinary diagnosis of idiopathic pulmonary fibrosis (IPF) in patients with a non-definite high-resolution computed tomography (HRCT) UIP pattern is uncertain.

Methods: We reviewed consecutive adult patients presenting with fibrotic interstitial lung disease (fILD) and a non-definite HRCT UIP pattern who underwent BAL and GC. The initial fILD diagnoses were re-evaluated after bronchoscopy and a final multidisciplinary consensus diagnosis was provided. We created a clinical score by analysing fILD clinical characteristics, GC and BAL results from 139 National Jewish Health patients and validated it at the University of Arizona (n=52). A multivariable model was developed and assessed using receiver operating characteristic curves.

Results: 43/139 (31%) and 29/52 (56%) patients in the derivation and validation cohort, respectively, were diagnosed with IPF after bronchoscopy, and 85/139 (61%) and 32/52 (61%) had a change in treatment, respectively. Compared to non-IPF, IPF patients had a similar progression-free survival (hazard ratio 1.50, 95% CI 0.76-2.95). The final model assigned a score to eight predictors: age, sex, HRCT probable UIP pattern, exposures, connective tissue disease signs/symptoms, Velcro crackles, GC results and BAL lymphocyte and macrophage counts. The final score demonstrated an area under the curve of 0.90 (95% CI 0.85-0.95) in the derivation cohort and 0.91 (95% CI 0.83-0.99) in the validation cohort.

Conclusion: The clinical-HRCT-BAL-GC IPF score may accurately estimate the post-test probability of IPF in patients with a non-definite HRCT UIP pattern.