Meta-Analysis
Copyright ©The Author(s) 2015.
World J Gastroenterol. May 14, 2015; 21(18): 5707-5718
Published online May 14, 2015. doi: 10.3748/wjg.v21.i18.5707
Table 1 Characteristics of the included studies focusing on IL-17 genetic polymorphisms
Ref.YearCountrySample size
Gender (M/F)
Age (yr)
Genotyping methodsGeneSNPSTROBE
CaseControlCaseControlCaseControl
Wu et al[30]2014China945768----PCR-RFLPIL-17Ars2275913 G>A29
Zhang et al[23]2014China260512162/98280/23260.6 ± 10.751.3 ± 11.2Sequenom MassArrayIL-17Ars2275913 G>A30
rs763780 T>C
Zhu et al[2]2014China293550189/104312/23857.5 ± 11.356.7 ± 12.7Sequenom MassArrayIL-17Ars2275913 G>A31
IL-17Frs763780 T>C
Rafiei et al[7]2013Iran16117189/7284/8762.6 ± 12.460.8 ± 12.8PCR-RFLPIL-17Ars2275913 G>A27
Arisawa et al[29]2012China337587234/103314/27365.3 ± 11.461.4 ± 13.7PCR-SSCPIL-17Ars2275913 G>A33
Zeng et al[31]2010China927777----PCR-RFLPIL-17Frs763780 T>C29
Shibata et al[20]2009Japan287524203/84307/21765.0 ± 11.855.7 ± 18.3PCR-SSCPIL-17Ars2275913 G>A32
IL-17Frs763780 T>C
Table 2 Meta-analysis of the association between IL-17 genetic polymorphisms and gastric cancer
Subgroup analysisW allele vs M(Allele model)
WW + WM vs MM(Dominant model)
WW vs WM + MM(Recessive model)
WW vs MM(Homozygous model)
WW vs WM(Heterozygous model)
OR95%CIP valueOR95%CIP valueOR95%CIP valueOR95%CIP valueOR95%CIP value
rs2275913 G>A1.331.12-1.570.0011.341.11-1.620.0031.501.15-1.940.0021.651.23-2.200.0011.421.10-1.840.008
Country
China1.471.05-2.050.0241.591.19-2.110.0011.600.95-2.700.0781.981.12-3.500.0191.430.86-2.380.167
Iran1.220.90-1.650.2071.070.66-1.730.7881.490.93-2.390.0951.390.79-2.440.2581.570.94-2.630.087
Japan1.191.04-1.370.0131.120.89-1.400.3221.371.11-1.700.0041.361.04-1.770.0221.381.10-1.740.006
Genotyping method
PCR-RFLP1.110.98-1.260.0881.241.02-1.520.0341.150.79-1.690.4681.230.97-1.570.0881.130.67-1.930.644
MassArray1.721.48-2.00< 0.0011.851.43-2.41< 0.0012.061.66-2.56< 0.0012.611.95-3.49< 0.0011.831.45-2.32< 0.001
PCR-SSCP1.191.04-1.370.0131.120.89-1.400.3221.371.11-1.700.0041.361.04-1.770.0221.381.10-1.740.006
rs763780 T>C1.951.47-2.59< 0.0011.210.85-1.720.2992.471.63-3.74< 0.0011.541.15-2.050.0042.831.63-4.91< 0.001
Country
China1.851.32-2.59< 0.0011.130.84-1.540.4212.421.40-4.180.0021.451.07-1.950.0162.931.34-6.390.007
Japan2.311.71-3.12< 0.0012.600.88-7.720.0852.681.91-3.75< 0.0013.441.15-10.260.0272.621.86-3.70< 0.001
Genotyping method
PCR-RFLP1.401.19-1.66< 0.0011.400.91-2.140.1221.511.24-1.84< 0.0011.601.04-2.460.0331.501.21-1.85< 0.001
MassArray2.171.78-2.66< 0.0010.940.62-1.410.7593.142.45-4.01< 0.0011.320.87-1.990.1944.203.14-5.62< 0.001
PCR-SSCP2.311.71-3.12< 0.0012.600.88-7.720.0852.681.91-3.75< 0.0013.441.15-10.260.0272.621.86-3.70< 0.001
Table 3 Univariate and multivariate meta-regression analyses of the potential source of heterogeneity
Heterogeneity factorsrs2275913 G>A
rs763780 T>C
CoefficientSEZP value95%CI
CoefficientSEZP value95%CI
LLULLLUL
Publication year
Univariate0.0420.0480.870.386-0.0530.1370.0340.0650.520.601-0.0930.161
Multivariate0.0400.0301.320.185-0.0190.098-0.0930.056-1.670.094-0.2020.016
Country
Univariate-0.1190.123-0.970.332-0.3600.1210.2250.3350.670.502-0.4320.882
Multivariate0.0350.0870.410.684-0.1350.2060.2790.1671.670.094-0.0480.606
Genotyping method
Univariate-0.2090.049-4.270.000-0.305-0.113-0.2160.091-2.360.018-0.395-0.037
Multivariate-0.2180.051-4.310.000-0.3170.119-0.2190.067-3.270.001-0.350-0.087