A fixed-effects or random-effects model was used to pool the data based on the Mantel–Haenszel method and DerSimonian and Laird method, respectively [31, 32]. These two models provide similar results when between-studies heterogeneity is absent; otherwise, the random-effects model is more appropriate. Heterogeneity between the studies was assessed by the chi-squared Q statistic (a higher number indicating more heterogeneity between studies) and I2 value (50% indicating heterogeneity), and P < 0.05 was considered to indicate statistical significance. Meta-regression and subgroup analyses were performed to quantify between-study heterogeneity, which were accounted for by publication year, study population, study design, and tobacco smoking status (non- and ever-smokers). We also performed a sensitivity analysis by examining changes in the results produced by the exclusion of each study. To assess publication bias, funnel plots (the natural logarithm of the OR and its standard error (SE)) were constructed. The circles correspond to the log OR from individual studies, and the diagonal lines show the expected 95% CI of the summary estimate. Furthermore, we performed a linear regression test of funnel plot asymmetry to evaluate more potential factors and obtained the results of Egger’s test to indicate publication bias.

All statistical analyses and graphs were conducted using RevMan (Review Manager statistical software, version 5.3), R software (software, version 3.6.2, https://www.r-project.org/) and OriginPro software (Origin Software, Inc., San Clemente, CA; version

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