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Additional file 1: Table S1. PRISMA checklist. Table S2. Search strategy. Table S2. Search strategy. Table S3. Inclusion and partial exclusion for patients with active TB. Table S4. Inclusion and partial exclusion for populations with very low risk of TB exposure. Table S5. Inclusion and partial exclusion for high-risk populations. Table S6. Populations considered high-risk. Table S7. Details of excluded criteria. Table S8. QUADAS-2 adapted quality assessment criteria for patients with active TB. Table S9. Quality score of 12 studies for patients with active TB. Table S10. QUADAS-2 adapted quality assessment criteria for populations with very low risk of TB exposure. Table S11. Quality score of 7 studies for populations with very low risk of TB exposure. Table S12. QUADAS-2 adapted quality assessment criteria for high-risk groups. Table S13. Quality score of 31 studies for high-risk groups. Table S14. Reasons for exclusion of 42 studies that were read in full-text review. Table S15. Characteristics of the 12 studies included in the sensitivity analysis. Table S16. Characteristics of the 7 studies included in the specificity analysis. Table S17. Characteristics of the 31 studies included in the positive rates. Table S18. Linearregression test of funnel plot asymmetry results of QFT-PLUS compared to QFT-GIT, T-SPOT.TB and TST in three populations. Figure S1. Forest plot of studies estimating the sensitivity of QFT-Plus (A) and QFT-GIT (B) in patients with active tuberculosis. Figure S2. Forest plot of studies estimating the sensitivity of QFT-Plus (A) and T-SPOT.TB (B) in patients with active tuberculosis. Figure S3. Forest plot of studies estimating the specificity of QFT-Plus (A) and QFT-GIT (B) in populations with very low risk of TB exposure. Figure S4. Forest plot of studies estimating the specificity of QFT-Plus (A) and T-SPOT.TB (B) in populations with very low risk of TB exposure. Figure S5. Forest plot of studies estimating the specificity of QFT-Plus (A) and TST (B) in populations with very low risk of TB exposure. Figure S6. Forest plot of studies estimating the positive rate Plus (A) and QFT-GIT (B) in high-risk populations. Figure S7. Forest plot of studies estimating the positive rate of QFT-Plus (A) and T-SPOT.TB (B) in high-risk populations. Figure S8. Forest plot of studies estimating the positive rate of QFT-Plus (A) and TST (B) in high-risk populations. Figure S9. Forest plot of studies estimating the sensitivity in patients with active tuberculosis for age of the participants (A), TB burden of the areas (B) and number of participants (C) subgroup analysis of QFT-PLUS compared with QFT-GIT. Figure S10. Forest plot of studies estimating the sensitivity in patients with active tuberculosis for number of participants subgroup analysis of QFT-PLUS compared with T-SPOT.TB. Figure S11. Forest plot of studies estimating the Specificity in populations with very low risk of TB exposure for TB burden of the areas (A) and number of participants (B) subgroup analysis of QFT-PLUS compared with QFT-GIT. Figure S12. Forest plot of studies estimating the positive rate in high-risk populations for age of the participants (A), TB burden of the areas (B), number of participants (C) and population (D)subgroup analysis of QFT-PLUS compared with QFT-GIT. Figure S13. Forest plot of studies estimating the positive rate in high-risk populations for age of the participants (A), TB burden of the areas (B), number of participants (C) and population (D)subgroup analysis of QFT-PLUS compared with T-SPOT.TB. Figure S14. Forest plot of studies estimating the positive rate in high-risk populations for age of the participants (A), TB burden of the areas (B), number of participants (C) and population (D)subgroup analysis of QFT-PLUS compared with TST. Figure S15. Sensitivity analysis of QFT-PLUS compared to QFT-GIT (A) and T-SPOT.TB (B) in patients with active TB. Figure S16. Sensitivity analysis of QFT-PLUS compared to QFT-GIT (A), T-SPOT.TB (B) and TST(C) in populations with very low risk of TB exposure. Figure S17. Sensitivity analysis of QFT-PLUS compared to QFT-GIT (A), T-SPOT.TB (B) and TST(C) in high-risk populations. Figure S18. Funnel plot of QFT-PLUS compared to QFT-GIT in patients with active TB. Figure S19. Funnel plot of QFT-PLUS compared to QFT-GIT (A) and TST (B) in high-risk populations.

Background: Fourteen meta-analyses reported the individual effects of the GSTM1 and GSTT1 polymorphisms on leukemia risk. However, over 40 studies were not included in previously published meta-analyses. Moreover, one key aspect was that previous meta-analyses did not conduct the false-positive test on the aforementioned issues. Furthermore, previous meta-analyses did not observe the combined effects of GSTM1 present/null and GSTT1 present/null polymorphism with leukemia risk. Therefore, we conducted the current study to further analyze these associations.Objectives: This study aimed to investigate the association between the individual and combined effects of the GSTM1 present/null and GSTT1 present/null polymorphisms and the risk of leukemia.Methods: A meta-analysis was performed applying Meta-analyses of Observational Studies in Epidemiology (MOOSE) guidelines. Moreover, false-positive report probability (FPRP) and Bayesian false discovery probability (BFDP) were applied to investigate the false-positive results.Results: The individual GSTM1 and GSTT1 null genotypes and combined effects of the two genes were associated with a significantly increased leukemia risk in overall and several subgroup analyses, such as Asians, Caucasians, and so on. Then, further analysis was conducted using FPRP and BFDP. Significant associations were considered as “positive” results on the GSTM1 null genotype with leukemia risk in overall populations (FPRP < 0.001 and BFDP = 0.006), Asians (FPRP < 0.001 and BFDP < 0.001), and East Asian population (FPRP < 0.001 and BFDP = 0.002). For the GSTT1 null genotype, significant associations were regarded “positive” results in overall populations, acute myeloid leukemia (AML), Asians, and East Asian population. For the combined effects of the GSTM1 and GSTT1 polymorphisms, significant associations were also considered “positive” results in the overall analysis of Asians, Indians, and East Asian population.Conclusion: This study strongly indicates that the individual GSTM1 and GSTT1 null genotypes and combined effects of the two genes are associated with increased leukemia risk in Asians, especially in the East Asian population; the GSTT1 null genotype is associated with increased AML risk; the combined effects of the two genes are associated with increased leukemia risk in Indians.