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Meta-analysis approach to study the prevalence of chronic obstructive pulmonary disease among current, former and non-smokers.

ABSTRACT: Comparative risk assessment for Chronic Obstructive Pulmonary Disease (COPD) among current, former and non-smokers categories remains controversial and not studied in detail. We conducted a meta-analysis to summarize all the relevant published studies on this topic and to update the association between smoking and prevalence of COPD in current, former and non-smokers. Identification, screening, eligibility and inclusion of articles for the study were conducted as per the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines. Quality assessment of included studies was undertaken using a scoring sheet. Meta-analysis after the final synthesis of the selected studies was performed using the STATA and Comprehensive Meta-Analysis (CMA) software. Estimates from forty two independent studies reporting 547,391 individuals were identified. Twenty two studies were conducted in Europe, nine in America and ten in Asia and one from New Zealand. The meta-analysis showed that the prevalence of COPD was significantly higher in current smokers compared with former and non-smokers. However, owing to large heterogeneity among the estimates obtained from the studies, stratification was done with respect to continent, diagnostic criteria of COPD and study design which also showed similar results. The stratified analysis also revealed similar trend of results with prevalence of COPD being higher in current smokers as compared to former and non-smokers. The present meta-analysis highlights the positive association between smoking and COPD prevalence. There is an urgent need to implement more effective policies towards the restriction of tobacco use, to reduce the burden of COPD.

SUBMITTER: Kamal R

PROVIDER: S-EPMC5598418 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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Meta-analysis approach to study the prevalence of chronic obstructive pulmonary disease among current, former and non-smokers.

Kamal Ritul R Srivastava Anup Kumar AK Kesavachandran Chandrasekharan Nair CN

Toxicology reports 20150721

Comparative risk assessment for Chronic Obstructive Pulmonary Disease (COPD) among current, former and non-smokers categories remains controversial and not studied in detail. We conducted a meta-analysis to summarize all the relevant published studies on this topic and to update the association between smoking and prevalence of COPD in current, former and non-smokers. Identification, screening, eligibility and inclusion of articles for the study were conducted as per the Preferred Reporting Item ...[more]

PMID: 28962448

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Project description:Background Heavy smokers perform worse on neuropsychological assessment than age-matched peers. However, traditional pulmonary measures of airflow limitation and hypoxemia explain only a modest amount of variance in cognition. The current objective was to determine whether carotid artery stiffness is associated with cognition in former smokers beyond the effects of amount of smoking and pulmonary function. Methods and Results Eighty-four former smokers including individuals across a spectrum of airflow limitation severity were included: 30 without chronic obstructive pulmonary disease (Global Initiative for Chronic Obstructive Lung Disease [GOLD] 0 with normal spirometry and lung computed tomography), 31 with mild-moderate chronic obstructive pulmonary disease (GOLD 1-2), and 23 with severe-very severe chronic obstructive pulmonary disease (GOLD 3-4). Participants completed questionnaires, spirometry, carotid ultrasonography, and neuropsychological testing. Multiple linear regression was used to determine whether carotid artery stiffness is associated with neuropsychological performance in 4 cognitive domains after adjusting for age, sex, pack-years of smoking, estimated premorbid intellectual functioning, and airflow limitation. Higher carotid artery β-stiffness index was associated with reduced executive functioning-processing speed in the fully adjusted model (β=-0.49, SE=0.14; P=0.001). Lower premorbid intellectual function, male sex, and presence of airflow limitation (GOLD 1 or 2 and GOLD 3 or 4) were also associated with worse executive functioning-processing speed. β-Stiffness index was not significantly associated with performance in other cognitive domains. Conclusions Carotid artery stiffness is associated with worse performance on executive functioning-processing speed in former smokers beyond the effects of aging, amount of past smoking, severity of airflow limitation, and hypoxemia. Future research should examine whether carotid stiffness can be used to identify former smokers at risk for subsequent cognitive impairment.

Project description:BACKGROUND:Chronic obstructive pulmonary disease (COPD) is significantly underdiagnosed in Kazakhstan, and there is no previously conducted study on COPD prevalence in the country. OBJECTIVE:The purpose of this study is to assess the prevalence of COPD among individuals aged 40 to 59 years based on results of spirometry before and after bronchodilator, presence of structural changes in the lungs (emphysema, inflammatory changes, and thickening of the walls of the large and small airways) detected by computer tomography, and the symptoms of COPD. The study has 3 study groups: smokers of conventional cigarettes, those who had quit smoking 1 to 5 years ago, and those who haven't smoked cigarettes. METHODS:This is an observational study with a cross-sectional design among individuals aged 40 to 59 years in Almaty, Kazakhstan. The sample of 900 individuals of both sexes contains 500 smokers, 200 ex-smokers, and 200 never-smokers. Study measures include spirometry, chest computed tomography, electrocardiography, physical exams, laboratory testing of serum, anthropometry, and 6-minute walk test. Data are collected by computer-assisted personal interviewing with tablets. The questionnaire was designed to explore possible COPD risk factors including history of smoking, current smoking, level of smoking exposure (in pack-years), passive smoking, occupational and environmental hazards, and covariates: age, gender, ethnicity, education, occupation, and self-reported morbidity. COPD Assessment Test (CAT) is used to collect information about COPD symptoms. RESULTS:We have completed the participant recruitment and study procedures. Currently, we are working on data processing and data analysis. The authors anticipate the preliminary results should be available by September 2017. Study results will be published in peer-reviewed scientific journals. CONCLUSIONS:This is the first study in Kazakhstan that assesses prevalence of COPD and its comorbidities in the adult population aged 40 to 59 years. The results of the study will be useful for improving COPD preventive measures, better COPD screening, identification, and registration. Findings of the study will also contribute to global knowledge on the epidemiology of COPD. TRIAL REGISTRATION:ClinicalTrials.gov NCT02926534; https://clinicaltrials.gov/ct2/show/NCT02926534 (Archived by WebCite at http://www.webcitation.org/6rjwGsPOZ).

Project description:Background DNA methylation (DNAm) performs excellently in the discrimination of current and former smokers from never smokers, where AUCs > 0.9 are regularly reported using a single CpG site (cg05575921; AHRR). However, there is a paucity of DNAm models which attempt to distinguish current, former and never smokers as individual classes. Derivation of a robust DNAm model that accurately distinguishes between current, former and never smokers would be particularly valuable to epidemiological research (as a more accurate smoking definition vs. self-report) and could potentially translate to clinical settings. Therefore, we appraise 4 DNAm models of ternary smoking status (that is, current, former and never smokers): methylation at cg05575921 (AHRR model), weighted scores from 13 CpGs created by Maas et al. (Maas model), weighted scores from a LASSO model of candidate smoking CpGs from the literature (candidate CpG LASSO model), and weighted scores from a LASSO model supplied with genome-wide 450K data (agnostic LASSO model). Discrimination is assessed by AUC, whilst classification accuracy is assessed by accuracy and kappa, derived from confusion matrices. Results We find that DNAm can classify ternary smoking status with reasonable accuracy, including when applied to external data. Ternary classification using only DNAm far exceeds the classification accuracy of simply assigning all classes as the most prevalent class (63.7% vs. 36.4%). Further, we develop a DNAm classifier which performs well in discriminating current from former smokers (agnostic LASSO model AUC in external validation data: 0.744). Finally, across our DNAm models, we show evidence of enrichment for biological pathways and human phenotype ontologies relevant to smoking, such as haemostasis, molybdenum cofactor synthesis, body fatness and social behaviours, providing evidence of the generalisability of our classifiers. Conclusions Our findings suggest that DNAm can classify ternary smoking status with close to 65% accuracy. Both the ternary smoking status classifiers and current versus former smoking status classifiers address the present lack of former smoker classification in epigenetic literature; essential if DNAm classifiers are to adequately relate to real-world populations. To improve performance further, additional focus on improving discrimination of current from former smokers is necessary. Supplementary Information The online version contains supplementary material available at 10.1186/s13148-021-01191-6.

Project description:BACKGROUND:Chronic obstructive pulmonary disease (COPD) is combination of progressive lung diseases. The diagnosis of COPD is generally based on the pulmonary function testing, however, difficulties underlie in prognosis of smokers or early stage of COPD patients due to the complexity and heterogeneity of the pathogenesis. Computational analyses of omics technologies are expected as one of the solutions to resolve such complexities. METHODS:We obtained transcriptomic data by in vitro testing with exposures of human bronchial epithelial cells to the inducers for early events of COPD to identify the potential descriptive marker genes. With the identified genes, the machine learning technique was employed with the publicly available transcriptome data obtained from the lung specimens of COPD and non-COPD patients to develop the model that can reflect the risk continuum across smoking and COPD. RESULTS:The expression levels of 15 genes were commonly altered among in vitro tissues exposed to known inducible factors for earlier events of COPD (exposure to cigarette smoke, DNA damage, oxidative stress, and inflammation), and 10 of these genes and their corresponding proteins have not previously reported as COPD biomarkers. Although these genes were able to predict each group with 65% accuracy, the accuracy with which they were able to discriminate COPD subjects from smokers was only 29%. Furthermore, logistic regression enabled the conversion of gene expression levels to a numerical index, which we named the "potential risk factor (PRF)" index. The highest significant index value was recorded in COPD subjects (0.56 at the median), followed by smokers (0.30) and non-smokers (0.02). In vitro tissues exposed to cigarette smoke displayed dose-dependent increases of PRF, suggesting its utility for prospective risk estimation of tobacco products. CONCLUSIONS:Our experimental-based transcriptomic analysis identified novel genes associated with COPD, and the 15 genes could distinguish smokers and COPD subjects from non-smokers via machine-learning classification with remarkable accuracy. We also suggested a PRF index that can quantitatively reflect the risk continuum across smoking and COPD pathogenesis, and we believe it will provide an improved understanding of smoking effects and new insights into COPD.

Dataset Information

Meta-analysis approach to study the prevalence of chronic obstructive pulmonary disease among current, former and non-smokers.

Publications

Meta-analysis approach to study the prevalence of chronic obstructive pulmonary disease among current, former and non-smokers.

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