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We performed a descriptive analysis of the frequency and percentage use of quality assessment tools. We tabulated the frequency of quality assessment tools used, type of tools, types of scales used, how the quality information was presented, types of methods used to deal with risk of bias or low quality. We also looked at frequency of high risk of bias or low quality studies being included in data set of articles, and if studies were included, were they dealt with using subgroup analysis, meta-regression, or sensitivity analysis \ref{fig:FIGURE_2}. Statistical analyses were performed with STATA version 13.1 software (State Corporation, College Station, Texas, USA).     \section{Results}  Our overall dataset included 337 studies during just the identification process of articles (Figure 1). From that initial dataset 79 articles were excluded during the screening process due to the fact that they were neither meta-analyses nor systematic reviews. The remaining set of articles that were assessed for meeting our eligibility criteria was 258. An additional 76 studies were removed after individual and group consensus was reached about reasons to remove those articles from our dataset. The studies removed were genetic studies, individual patient data meta-analyses, genomic studies, histological studies, and a letter to an editor. Our final dataset contained 182 articles.   Within this data set, quality or risk of bias assessment was conducted in 91 articles (50 percent, \ref{fig:Table_3}). The tools that were used most commonly were those assessed by the author independently   
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