Genetic association studies report potentially conflicting findings which meta-analysis seeks to quantifyand objectively summarize. Attributing cancer to a single gene variant requires large sample sizes, whichmay strain resources in a primary study. Properly used, meta-analysis is a powerful tool for resolvingdiscrepancies in genetic association studies given the exponential increase in sample sizes when data arecombined. The several steps involved in this methodology require careful attention to critical issues in metaanalysis,heterogeneity and publication bias, evaluation of which can be graphical or statistical. Overallsummary effects of a meta-analysis may or may not reflect similar associations when the component studiesare sub grouped. Overall associations and that of the subgroups are evaluated for tenability using sensitivityanalysis. The low association between a polymorphism and cancer is offset by detectable changes in cancerincidence in the general population making them an important issue from a public health point of view.Asian meta-analytic publications in cancer genetics come from six countries with an output that numberfrom one to two. The exception is China, whose publication output has increased exponentially since 2008.