The aim of the present work was to perform a meta-analysis to evaluate the association between the interleukin 10 (IL-10) -819C/T (rs1800871) polymorphism and cancer risk. A total of 73 studies, including 15,942 cancer cases and 22,336 controls, were identified in this meta-analysis. The odds ratios (ORs) with 95% confidence intervals (CIs) were calculated using the random-effects model. Overall, no significant association was identified between the IL-10 -819C/T polymorphism and cancer risk. In the subgroup analyses, the T allele and TT genotype were associated with a moderately reduced cancer risk in the Asian population (T allele vs. C allele: OR=0.93, 95%CI: 0.87, 0.99; TT vs. CC: OR=0.86, 95%CI: 0.76, 0.98; TT vs. CT/CC: OR=0.90, 95%CI: 0.82, 0.98). Individuals who were homozygous for the T allele (TT) were found to be associated with significantly reduced gastric cancer risk in the Asian population. The heterozygous variant (CT) and the dominant model (TT/CT vs. CC) were associated with an increased risk for cervical and ovarian cancer. However, the IL-10 -819C/T polymorphism was not significantly associated with breast cancer, colorectal cancer, lung cancer, hepatocellular carcinoma, prostate cancer, lymphoma, or melanoma. The depressed cancer risk of the TT genotype occurred in the studies of hospital-based case-control studies and the studies recruited less than 500 subjects, but no statistically significant results were found in the stratified analyses using genotyping method. The results suggest that the IL-10 -819TT genotype may be a protective factor for cancer in Asians, especially gastric cancer. In contrast, the CT genotype and the dominant model could be risk factors for cervical and ovarian cancer. The importance of stratifying by ethnicity, cancer type, study design, and sample size needs to be standardized in future studies, together with considering the association between the IL-10 -819C/T polymorphism and cancer risk. Furthermore, the linkage of -819C/T with other polymorphisms of the IL-10 gene may help explain the variability in findings.