Figure 1.
Flow chart of study selection.
Table 1.
Characteristics of the studies related with the effects of GSTs genetic polymorphisms and HCC risk.
Figure 2.
Association between GSTM1 null genotype and HCC risk analyzed by forest plot of meta-analysis.
The forest plots of pooled OR with 95% CI (Null genotype vs. Present genotype; OR = 1.47, 95% CI: 1.21 to 1.79; Random-effects model, P<0.001).
Figure 3.
Association between GSTT1 null genotype and HCC risk analyzed by forest plot of meta-analysis.
The forest plots of pooled OR with 95% CI (Null genotype vs. Present genotype; OR = 1.38, 95% CI: 1.14 to 1.65; Random-effects model, P<0.001).
Figure 4.
Association between GSTM1-GSTT1 dual-null genotype and HCC risk analyzed by forest plot of meta-analysis.
The forest plots of pooled OR with 95% CI (Dual-null genotype vs. Present genotype; OR = 1.79, 95% CI: 1.26 to 2.53; Random-effects model, P<0.001).
Table 2.
Subgroup analysis of the association between GSTM1 null genotype and HCC risk.
Table 3.
Subgroup analysis of the association between GSTT1 null genotype and HCC risk.
Table 4.
Subgroup analysis of the association between GSTM1-GSTT1 null genotype and HCC risk.
Figure 5.
Galbraith plot of association between GST polymorphisms and HCC risk.
Each figure represents a unique article in this meta-analysis. The figures outside the three lines are spotted as the outliers and the possible sources of heterogeneity in the analysis pooled of total available studies. (A) Galbraith plot identifies the outliers from 26 studies about GSTM1 polymorphisms and HCC risk. (B) Galbraith plot identifies the outliers from 21 studies about GSTT1 polymorphisms and HCC risk. (C) Galbraith plot identifies the outliers from 12 studies about GSTM1-GSTT1 polymorphisms and HCC risk.
Table 5.
Subgroup analysis of $the adjusted association between GSTT1 null genotype and HCC risk.
Table 6.
Subgroup analysis of $the adjusted association between GSTM1-GSTT1 null genotype and HCC risk.
Figure 6.
Beggar’s test and Egger’s test of GST polymorphisms and HCC risk.
Beggar’s funnel plot is used to detect potential publication bias in which a symmetric funnel shape means no publication bias. Egger’s linear regression test is used to quantify the potential presence of publication bias. Both Beggar’s test and Egger’s test show that no publication bias has been found from 26 inclusive studies about the association between GSTM1 polymorphisms and HCC risk (A and B), 21 inclusive studies about the association between GSTT1 polymorphisms and HCC risk (C and D), and 12 inclusive studies about the association between dual-null genotype of GSTM1-GSTT1 and HCC risk polymorphisms and HCC risk (E and F).