Design of the Subpopulations and Intermediate Outcome Measures in COPD (SPIROMICS) AIR Study.

IntroductionPopulation-based epidemiological evidence suggests that exposure to ambient air pollutants increases hospitalisations and mortality from chronic obstructive pulmonary disease (COPD), but less is known about the impact of exposure to air pollutants on patient-reported outcomes, morbidity and progression of COPD.Methods and analysisThe Subpopulations and Intermediate Outcome Measures in COPD (SPIROMICS) Air Pollution Study (SPIROMICS AIR) was initiated in 2013 to investigate the relation between individual-level estimates of short-term and long-term air pollution exposures, day-to-day symptom variability and disease progression in individuals with COPD. SPIROMICS AIR builds on a multicentre study of smokers with COPD, supplementing it with state-of-the-art air pollution exposure assessments of fine particulate matter, oxides of nitrogen, ozone, sulfur dioxide and black carbon. In the parent study, approximately 3000 smokers with and without airflow obstruction are being followed for up to 3 years for the identification of intermediate biomarkers which predict disease progression. Subcohorts undergo daily symptom monitoring using comprehensive daily diaries. The air monitoring and modelling methods employed in SPIROMICS AIR will provide estimates of individual exposure that incorporate residence-specific infiltration characteristics and participant-specific time-activity patterns. The overarching study aim is to understand the health effects of short-term and long-term exposures to air pollution on COPD morbidity, including exacerbation risk, patient-reported outcomes and disease progression.Ethics and disseminationThe institutional review boards of all the participating institutions approved the study protocols. The results of the trial will be presented at national and international meetings and published in peer-reviewed journals

Defining a standard Set of health outcomes for patients with squamous cell carcinoma of the head and neck in Spain

Purpose: A systematic, standardized collection of health outcomes during patient treatment and follow-up, relevant from the perspective of all stakeholders, is a crucial step toward effective and efficient disease management. This project aimed to define a standard set of health outcomes for patients with squamous cell carcinoma of the head and neck (SCCHN). Methods: The project was led and coordinated by a scientific committee (SC). It comprised: (1) a literature review (to identify variables used during SCCHN management); (2) 1st-SC meeting (to select the variables for presentation during nominal groups-NG); (3) five NG (n=42 experts) and four interviews with patients (to reach consensus on the variables for inclusion); and (4) final-SC meeting (to review the results of NG ensuring consensus on the variables where consensus was not reached). Results: Experts agreed to include the following variables in the standard set: treatment-related (treatment intent and type, response to treatment, treatment toxicity/complication, treatment completion), degree of health (performance status, patient-reported health status, pain, dysphonia, feeding and speech limitations, body image alteration, tracheotomy), survival (overall and progression-free survival, cause of death), nutritional (weight, nutritional intervention), other variables (smoking status, alcohol consumption, patient satisfaction with aftermath care, employment status), and case-mix variables (demographic, tumor-related, clinical and nutritional factors). Conclusions: This project may pave the way to standardizing the collection of health outcomes in SCCHN and promote the incorporation of patients’ perspective in its management. The information provided through the systematic compilation of this standard set may define strategies to achieve high-quality, patient-centered care

The association of plasma biomarkers with computed tomography-assessed emphysema phenotypes

Rationale: Chronic obstructive pulmonary disease (COPD) is a phenotypically heterogeneous disease. In COPD, the presence of emphysema is associated with increased mortality and risk of lung cancer. High resolution computed tomography (HRCT) scans are useful in quantifying emphysema but are associated with radiation exposure and high incidence of false positive findings (i.e., nodules). Using a comprehensive biomarker panel, we sought to determine if there was a peripheral blood biomarker signature of emphysema. Methods: 114 plasma biomarkers were measured using a custom assay in 588 individuals enrolled in the COPDGene study. Quantitative emphysema measurements included percent low lung attenuation (%LAA) ≤ −950 HU, ≤ − 910 HU and mean lung attenuation at the 15th percentile on lung attenuation curve (LP15A). Multiple regression analysis was performed to determine plasma biomarkers associated with emphysema independent of covariates age, gender, smoking status, body mass index and FEV1. The findings were subsequently validated using baseline blood samples from a separate cohort of 388 subjects enrolled in the Treatment of Emphysema with a Selective Retinoid Agonist (TESRA) study. Results: Regression analysis identified multiple biomarkers associated with CT-assessed emphysema in COPDGene, including advanced glycosylation end-products receptor (AGER or RAGE, p < 0.001), intercellular adhesion molecule 1 (ICAM, p < 0.001), and chemokine ligand 20 (CCL20, p < 0.001). Validation in the TESRA cohort revealed significant associations with RAGE, ICAM1, and CCL20 with radiologic emphysema (p < 0.001 after meta-analysis). Other biomarkers that were associated with emphysema include CDH1, CDH 13 and SERPINA7, but were not available for validation in the TESRA study. Receiver operating characteristics analysis demonstrated a benefit of adding a biomarker panel to clinical covariates for detecting emphysema, especially in those without severe airflow limitation (AUC 0.85). Conclusions: Our findings, suggest that a panel of blood biomarkers including sRAGE, ICAM1 and CCL20 may serve as a useful surrogate measure of emphysema, and when combined with clinical covariates, may be useful clinically in predicting the presence of emphysema compared to just using covariates alone, especially in those with less severe COPD. Ultimately biomarkers may shed light on disease pathogenesis, providing targets for new treatments. Electronic supplementary material The online version of this article (doi:10.1186/s12931-014-0127-9) contains supplementary material, which is available to authorized users

Robust deep labeling of radiological emphysema subtypes using squeeze and excitation convolutional neural networks: The MESA Lung and SPIROMICS Studies

Pulmonary emphysema, the progressive, irreversible loss of lung tissue, is conventionally categorized into three subtypes identifiable on pathology and on lung computed tomography (CT) images. Recent work has led to the unsupervised learning of ten spatially-informed lung texture patterns (sLTPs) on lung CT, representing distinct patterns of emphysematous lung parenchyma based on both textural appearance and spatial location within the lung, and which aggregate into 6 robust and reproducible CT Emphysema Subtypes (CTES). Existing methods for sLTP segmentation, however, are slow and highly sensitive to changes in CT acquisition protocol. In this work, we present a robust 3-D squeeze-and-excitation CNN for supervised classification of sLTPs and CTES on lung CT. Our results demonstrate that this model achieves accurate and reproducible sLTP segmentation on lung CTscans, across two independent cohorts and independently of scanner manufacturer and model

The association of plasma biomarkers with computed tomography-assessed emphysema phenotypes

Abstract Rationale Chronic obstructive pulmonary disease (COPD) is a phenotypically heterogeneous disease. In COPD, the presence of emphysema is associated with increased mortality and risk of lung cancer. High resolution computed tomography (HRCT) scans are useful in quantifying emphysema but are associated with radiation exposure and high incidence of false positive findings (i.e., nodules). Using a comprehensive biomarker panel, we sought to determine if there was a peripheral blood biomarker signature of emphysema. Methods 114 plasma biomarkers were measured using a custom assay in 588 individuals enrolled in the COPDGene study. Quantitative emphysema measurements included percent low lung attenuation (%LAA)≤ - 950 HU, ≤ -910 HU and mean lung attenuation at the 15th percentile on lung attenuation curve (LP15A). Multiple regression analysis was performed to determine plasma biomarkers associated with emphysema independent of covariates age, gender, smoking status, body mass index and FEV1. The findings were subsequently validated using baseline blood samples from a separate cohort of 388 subjects enrolled in the Treatment of Emphysema with a Selective Retinoid Agonist (TESRA) study. Results Regression analysis identified multiple biomarkers associated with CT-assessed emphysema in COPDGene, including advanced glycosylation end-products receptor (AGER or RAGE, p < 0.001), intercellular adhesion molecule 1 (ICAM, p < 0.001), and chemokine ligand 20 (CCL20, p < 0.001). Validation in the TESRA cohort revealed significant associations with RAGE, ICAM1, and CCL20 with radiologic emphysema (p < 0.001 after meta-analysis). Other biomarkers that were associated with emphysema include CDH1, CDH 13 and SERPINA7, but were not available for validation in the TESRA study. Receiver operating characteristics analysis demonstrated a benefit of adding a biomarker panel to clinical covariates for detecting emphysema, especially in those without severe airflow limitation (AUC 0.85). Conclusions Our findings, suggest that a panel of blood biomarkers including sRAGE, ICAM1 and CCL20 may serve as a useful surrogate measure of emphysema, and when combined with clinical covariates, may be useful clinically in predicting the presence of emphysema compared to just using covariates alone, especially in those with less severe COPD. Ultimately biomarkers may shed light on disease pathogenesis, providing targets for new treatments.http://deepblue.lib.umich.edu/bitstream/2027.42/134591/1/12931_2014_Article_127.pd

Genetic susceptibility for chronic bronchitis in chronic obstructive pulmonary disease

Background: Chronic bronchitis (CB) is one of the classic phenotypes of COPD. The aims of our study were to investigate genetic variants associated with COPD subjects with CB relative to smokers with normal spirometry, and to assess for genetic differences between subjects with CB and without CB within the COPD population. Methods: We analyzed data from current and former smokers from three cohorts: the COPDGene Study; GenKOLS (Bergen, Norway); and the Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints (ECLIPSE). CB was defined as having a cough productive of phlegm on most days for at least 3 consecutive months per year for at least 2 consecutive years. CB COPD cases were defined as having both CB and at least moderate COPD based on spirometry. Our primary analysis used smokers with normal spirometry as controls; secondary analysis was performed using COPD subjects without CB as controls. Genotyping was performed on Illumina platforms; results were summarized using fixed-effect meta-analysis. Results: For CB COPD relative to smoking controls, we identified a new genome-wide significant locus on chromosome 11p15.5 (rs34391416, OR = 1.93, P=4.99× 10-8) as well as significant associations of known COPD SNPs within FAM13A. In addition, a GWAS of CB relative to those without CB within COPD subjects showed suggestive evidence for association on 1q23.3 (rs114931935, OR = 1.88, P= 4.99 ×10-7). Conclusions: We found genome-wide significant associations with CB COPD on 4q22.1 (FAM13A) and 11p15.5 (EFCAB4A, CHID1 and AP2A2), and a locus associated with CB within COPD subjects on 1q23.3 (RPL31P11 and ATF6). This study provides further evidence that genetic variants may contribute to phenotypic heterogeneity of COPD.publishedVersio

Lower serum IgA is associated with COPD exacerbation risk in SPIROMICS

Background Decreased but measurable serum IgA levels (≤70 mg/dL) have been associated with risk for infections in some populations, but are unstudied in COPD. This study tested the hypothesis that subnormal serum IgA levels would be associated with exacerbation risk in COPD. Methods Data were analyzed from 1,049 COPD participants from the observational cohort study SPIROMICS (535 (51%) women; mean age 66.1 (SD 7.8), 338 (32%) current smokers) who had baseline serum IgA measured using the Myriad RBM biomarker discovery platform. Exacerbation data was collected prospectively (mean 944.3 (SD 281.3) days), and adjusted linear, logistic and zero-inflated negative binomial regressions were performed. Results Mean IgA was 269.1 mg/dL (SD 150.9). One individual had deficient levels of serum IgA (<7 mg/dL) and 25 (2.4%) had IgA level ≤70 mg/dL. Participants with IgA ≤70 mg/dL were younger (62 vs. 66 years, p = 0.01) but otherwise similar to those with higher IgA. In adjusted models, IgA ≤70 mg/dL was associated with higher exacerbation incidence rates (IRR 1.71, 95% CI 1.01–2.87, p = 0.044) and greater risk for any severe exacerbation (OR 2.99, 95% CI 1.30–6.94, p = 0.010). In adjusted models among those in the lowest decile (<120 mg/dL), each 10 mg/dL decrement in IgA (analyzed continuously) was associated with more exacerbations during follow-up (β 0.24, 95% CI 0.017–0.46, p = 0.035). Conclusions Subnormal serum IgA levels were associated with increased risk for acute exacerbations, supporting mildly impaired IgA levels as a contributing factor in COPD morbidity. Additionally, a dose-response relationship between lower serum IgA and number of exacerbations was found among individuals with serum IgA in the lowest decile, further supporting the link between serum IgA and exacerbation risk. Future COPD studies should more comprehensively characterize immune status to define the clinical relevance of these findings and their potential for therapeutic correction

Imaging-based clusters in current smokers of the COPD cohort associate with clinical characteristics: the SubPopulations and Intermediate Outcome Measures in COPD Study (SPIROMICS)

Background Classification of COPD is usually based on the severity of airflow, which may not sensitively differentiate subpopulations. Using a multiscale imaging-based cluster analysis (MICA), we aim to identify subpopulations for current smokers with COPD. Methods Among the SPIROMICS subjects, we analyzed computed tomography images at total lung capacity (TLC) and residual volume (RV) of 284 current smokers. Functional variables were derived from registration of TLC and RV images, e.g. functional small airways disease (fSAD%). Structural variables were assessed at TLC images, e.g. emphysema and airway wall thickness and diameter. We employed an unsupervised method for clustering. Results Four clusters were identified. Cluster 1 had relatively normal airway structures; Cluster 2 had an increase of fSAD% and wall thickness; Cluster 3 exhibited a further increase of fSAD% but a decrease of wall thickness and airway diameter; Cluster 4 had a significant increase of fSAD% and emphysema. Clinically, Cluster 1 showed normal FEV1/FVC and low exacerbations. Cluster 4 showed relatively low FEV1/FVC and high exacerbations. While Cluster 2 and Cluster 3 showed similar exacerbations, Cluster 2 had the highest BMI among all clusters. Conclusions Association of imaging-based clusters with existing clinical metrics suggests the sensitivity of MICA in differentiating subpopulations