Weisan Zhang1,2, Fengtan Li3, Wenyuan Gao1. 1. School of Pharmaceutical Science and Technology, Tianjin University, Tianjin, China. 2. Department of Geriatrics, Tianjin Medical University General Hospital, Tianjin, China. 3. Department of Radiology, Tianjin Medical University General Hospital, Tianjin, China.
We read the original study published by Chen et al. in your journal, “Traffic‐related air pollution and lung cancer: A meta‐analysis,” with great interest.1 The authors included 36 publications in the meta‐analysis and generally found that exposure to traffic‐related air pollution significantly increased the risk of lung cancer. The authors also conducted sub‐group analysis according to different exposures. Exposure to nitrogen dioxide (meta‐odds ratio [OR] 1.06, 95% confidence interval [CI] 0.99–1.13), nitrogen oxide (meta‐OR 1.04, 95% CI 1.01–1.07), sulfur dioxide (meta‐OR 1.03, 95% CI 1.02–1.05), and fine particulate matter (meta‐OR 1.11, 95% CI 1.00–1.22) were positively associated with a risk of lung cancer. Occupational exposure to air pollution among professional drivers significantly increased the incidence (meta‐OR 1.27, 95% CI 1.19–1.36) and mortality of lung cancer (meta‐OR 1.14, 95% CI 1.04–1.26). The authors made quality assessments for each included study according to the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement.2 This is most important to guarantee the general quality of the meta‐analysis, as results and conclusions are untrustworthy if pooling data from poor quality original studies.3 The authors did very well in this respect.However, we found significant heterogeneity in the evaluation of the association between ambient exposure to nitrogen dioxide and lung cancer risk (I2 = 59%, P = 0.05), the relationship between ambient exposure to fine particulate matter and lung cancer (I2 = 64%, P = 0.02), and the risk of lung cancer incidence among professional drivers (I2 = 44%, P = 0.02). This significant heterogeneity limits the statistical power and conclusion.4We suggest that the authors conduct meta‐regression analysis to evaluate the sources of the heterogeneity. Moreover, the conclusion of this meta‐analysis would be significantly more credible if the authors provide information on publication bias.
Authors: Richard G White; Avi J Hakim; Matthew J Salganik; Michael W Spiller; Lisa G Johnston; Ligia Kerr; Carl Kendall; Amy Drake; David Wilson; Kate Orroth; Matthias Egger; Wolfgang Hladik Journal: J Clin Epidemiol Date: 2015-05-01 Impact factor: 6.437
Authors: Theo Lorenc; Lambert Felix; Mark Petticrew; G J Melendez-Torres; James Thomas; Sian Thomas; Alison O'Mara-Eves; Michelle Richardson Journal: Syst Rev Date: 2016-11-16