Predictors of idiopathic pulmonary fibrosis in absence of radiologic honeycombing: A cross sectional analysis in ILD patients undergoing lung tissue sampling. (September 2016)

• Record Type: Journal Article
• Authors: Salisbury, Margaret L.; Xia, Meng; Murray, Susan; Bartholmai, Brian J.; Kazerooni, Ella A.; Meldrum, Catherine A.; Martinez, Fernando J.; Flaherty, Kevin R.
• Is Part Of: Respiratory medicine. Volume 118(2016)
• Page Start: 88
• Page End: 95
• Publication Date: 2016-09
• Subjects: Interstitial lung disease -- Idiopathic pulmonary fibrosis -- High resolution computed tomography -- Diagnosis; HRCT High Resolution Computed Tomography -- HP Hypersensitivity Pneumonia -- IPF Idiopathic Pulmonary Fibrosis -- ILD Interstitial Lung Disease -- LTRC Lung Tissue Research Consortium -- NSIP Nonspecific Interstitial Pneumonitis -- UIP Usual Interstitial Pneumonia; Chest -- Diseases -- Periodicals; Chest -- Diseases -- Great Britain -- Periodicals; Respiratory organs -- Diseases -- Periodicals; Respiratory Tract Diseases -- Periodicals; Appareil respiratoire -- Maladies -- Périodiques; Thorax -- Maladies -- Périodiques; Appareil respiratoire -- Maladies -- Traitement -- Périodiques; Electronic journals; 616.2
• DOI: 10.1016/j.rmed.2016.07.016
• Languages: English
• ISSNs: 0954-6111

Abstract

Abstract: Background: Idiopathic pulmonary fibrosis (IPF) can be diagnosed confidently and non-invasively when clinical and computed tomography (CT) criteria are met. Many do not meet these criteria due to absence of CT honeycombing. We investigated predictors of IPF and combinations allowing accurate diagnosis in individuals without honeycombing. Methods: We utilized prospectively collected clinical and CT data from patients enrolled in the Lung Tissue Research Consortium. Included patients had no honeycombing, no connective tissue disease, underwent diagnostic lung biopsy, and had CT pattern consistent with fibrosing ILD (n = 200). Logistic regression identified clinical and CT variables predictive of IPF. The probability of IPF was assessed at various cut-points of important clinical and CT variables. Results: A multivariable model adjusted for age and gender found increasingly extensive reticular densities (OR 2.93, CI 95% 1.55–5.56, p = 0.001) predicted IPF, while increasing ground glass densities predicted a diagnosis other than IPF (OR 0.55, CI 95% 0.34–0.89, p = 0.02). The model-based probability of IPF was 80% or greater in patients with age at least 60 years and extent of reticular density one-third or more of total lung volume; for patients meeting or exceeding these clinical thresholds the specificity for IPF is 96% (CI 95% 91–100%) with 21 of 134 (16%) biopsies avoided. Conclusions: In patients with suspected fibrotic ILD and absence of CT honeycombing, extent of reticular and ground glass densities predict a diagnosis of IPF. The probability of IPF exceeds 80% in subjects over age 60 years with one-third of total lung having reticular densities. Highlights: Predictors of IPF are evaluated in patients without radiologic honeycombing. All had fibrotic interstitial lung disease and underwent diagnostic lung biopsy. More extensive reticular densities are associated with a diagnosis of IPF. IPF probability exceeds 80% when over 1/3 of lung contains reticular densities.