Han, MeiLan K.

Abstract Rationale Inflammation is central to chronic obstructive pulmonary disease (COPD) pathogenesis but incompletely represented in COPD prognostic models. The neutrophil-to-lymphocyte ratio (NLR) is a readily available inflammatory biomarker. Objectives To explore the associations of NLR with smoking status, clinical features of COPD, and future adverse outcomes. Methods We analyzed NLR calculated from the complete blood count of participants who currently or formerly smoked (n = 2,624) and tobacco-naive control subjects (n = 187) in the SPIROMICS multicenter observational cohort study. We assessed the stability of NLR at 6 weeks and 1 year, the association with select blood biomarkers, and the impact of smoking on NLR and cell counts. We stratified participants by NLR quartiles to compare cross-sectional clinical features at enrollment, prospectively observed exacerbations at 1 year, and mortality during longitudinal follow up. Results Higher NLR quartiles were broadly associated with more severe clinical features of COPD. NLR values were repeatable at 6 weeks (intraclass correlation coefficient, 0.74) and 1 year (intraclass correlation coefficient, 0.62). The impact of smoking on NLR varied with the severity of airflow limitation, mediated by an interaction between smoking, forced expiratory volume in 1 second percent predicted, and neutrophil counts but not lymphocyte counts. The highest NLR quartile (>3.11) was associated with an increased risk of exacerbation over 1 year (adjusted odds ratio, 1.51; 95% confidence interval, 1.18, 1.92) and increased risk of mortality (adjusted hazard ratio, 1.41; 95% confidence interval, 1.20, 1.66) compared with quartiles 1–3. Conclusions Elevated NLR in stable COPD is a widely available biomarker associated with increased risk for exacerbation and death. The impact of cigarette smoking on NLR varies with disease severity.

Abstract Rationale Idiopathic pulmonary fibrosis (IPF) and other idiopathic interstitial pneumonias (IIPs) have similar clinical and radiographic features, but their histopathology, response to therapy, and natural history differ. A surgical lung biopsy is often required to distinguish between these entities. Objectives We sought to determine if clinical variables could predict a histopathologic diagnosis of IPF in patients without honeycomb change on high-resolution computed tomography (HRCT). Methods Data from 97 patients with biopsy-proven IPF and 38 patients with other IIPs were examined. Logistic regression models were built to identify the clinical variables that predict histopathologic diagnosis of IPF. Measurements and Main Results Increasing age and average total HRCT interstitial score on HRCT scan of the chest may predict a biopsy confirmation of IPF. Sex, pulmonary function, presence of desaturation, or distance walked during a 6-minute walk test did not help discriminate pulmonary fibrosis from other IIPs. Conclusions Clinical data may be used to predict a diagnosis of IPF over other IIPs. Validation of these data with a prospective study is needed.