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\subsection{\textbf{Data Analysis}}  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. In assessing the types of tools used to measure quality, we had some additional categories such as author independently assessed, other, and unspecified. For studies to fit into the author independently assessed category, we specifically looked for the terms 'independent assessment completed by two outside reviewers' and if no additional quality assessment criteria was listed, then the label author independently assessed was assigned. In a situation where the author of the study used a quality assessment adapted from another study, we labeled these studies as other. For example, one of our studies indicated in the text that Slim K et al. criteria known as "Methodological index for non-randomized studies (minors): Development and validation of a new instrument" was utilized to assess quality and so for this study, we considered these studies to fall into a separate category labeled as other \cite{Valsecchi_2011}. There were studies where it was indicated either in the abstract or in the methods section that quality was assessed, but there was no specification of how quality was assessed, and so those articles were listed under the 'unspecified' category.  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.  
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