Precision medicine is a patient-specific approach that integrates all relevant clinical, genetic and biological information in order to optimise the therapeutic benefit relative to the possibility of side-effects for each individual. Recent clinical trials have shown that higher blood eosinophil counts are associated with a greater efficacy of inhaled corticosteroids (ICSs) in chronic obstructive pulmonary disease (COPD) patients. Blood eosinophil counts are a biomarker with potential to be used in clinical practice, to help target ICS treatment with more precision in COPD patients with a history of exacerbations despite appropriate bronchodilator treatment.The Global Initiative for Chronic Obstructive Lung Disease (GOLD) 2017 pharmacological treatment algorithms, based on the ABCD assessment, can be applied relatively easily to treatment-naive individuals at initial presentation. However, their use is more problematic during follow-up in patients who are already on maintenance treatment. There is a need for a different system to guide COPD pharmacological management during follow-up.Recent large randomised controlled trials have provided important new information concerning the therapeutic effects of ICSs and long-acting bronchodilators on exacerbations. The new evidence regarding blood eosinophils and inhaled treatments, and the need to distinguish between initial and follow-up pharmacological management, led to changes in the GOLD pharmacological treatment recommendations. This article explains the evidence and rationale for the GOLD 2019 pharmacological treatment recommendations.
Triple therapy with fluticasone furoate, umeclidinium, and vilanterol resulted in a lower rate of moderate or severe COPD exacerbations than fluticasone furoate-vilanterol or umeclidinium-vilanterol in this population. Triple therapy also resulted in a lower rate of hospitalization due to COPD than umeclidinium-vilanterol. (Funded by GlaxoSmithKline; IMPACT ClinicalTrials.gov number, NCT02164513 .).
Although culture-independent techniques have shown that the lungs are not sterile, little is known about the lung microbiome in chronic obstructive pulmonary disease (COPD). We used pyrosequencing of 16S amplicons to analyze the lung microbiome in two ways: first, using bronchoalveolar lavage (BAL) to sample the distal bronchi and air-spaces; and second, by examining multiple discrete tissue sites in the lungs of six subjects removed at the time of transplantation. We performed BAL on three never-smokers (NS) with normal spirometry, seven smokers with normal spirometry (“heathy smokers”, HS), and four subjects with COPD (CS). Bacterial 16 s sequences were found in all subjects, without significant quantitative differences between groups. Both taxonomy-based and taxonomy-independent approaches disclosed heterogeneity in the bacterial communities between HS subjects that was similar to that seen in healthy NS and two mild COPD patients. The moderate and severe COPD patients had very limited community diversity, which was also noted in 28% of the healthy subjects. Both approaches revealed extensive membership overlap between the bacterial communities of the three study groups. No genera were common within a group but unique across groups. Our data suggests the existence of a core pulmonary bacterial microbiome that includes Pseudomonas, Streptococcus, Prevotella, Fusobacterium, Haemophilus, Veillonella, and Porphyromonas. Most strikingly, there were significant micro-anatomic differences in bacterial communities within the same lung of subjects with advanced COPD. These studies are further demonstration of the pulmonary microbiome and highlight global and micro-anatomic changes in these bacterial communities in severe COPD patients.
Chronic obstructive pulmonary disease (COPD) is increasingly being recognized as a highly heterogeneous disorder, composed of varying pathobiology. Accurate detection of COPD subtypes by image biomarkers are urgently needed to enable individualized treatment thus improving patient outcome. We adapted the Parametric Response Map (PRM), a voxel-wise image analysis technique, for assessing COPD phenotype. We analyzed whole lung CT scans of 194 COPD individuals acquired at inspiration and expiration from the COPDGene Study. PRM identified the extent of functional small airways disease (fSAD) and emphysema as well as provided CT-based evidence that supports the concept that fSAD precedes emphysema with increasing COPD severity. PRM is a versatile imaging biomarker capable of diagnosing disease extent and phenotype, while providing detailed spatial information of disease distribution and location. PRMs ability to differentiate between specific COPD phenotypes will allow for more accurate diagnosis of individual patients complementing standard clinical techniques.
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