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\subsection{\textbf{Methods:}}  We performed a search of systematic reviews from high impact factor journals in oncology from 2007 to 2015 through PubMed. Covidence was used to screen articles based on the title and abstract. The methodological quality and reporting of risk of bias were evaluated by three rounds of coding from two independent reviewers using the same checklist. Differences in assessment were resolved through group consensus.  \subsection{\textbf{Results:}}  Quality assessment was studied on 182 articles after exclusion. Quality or risk of bias assessment was assessed in 50\% of articles. More common were tools adapted from other sources (25\%), (29\%),  author independently assessed (21\%) (22\%)  and unspecified (13\%). (14\%).  Low Quality or High risk of bias studies were found in 46 studies. From included studies, subgroup analysis was conducted in 18\%, meta-regression in 9\%, and sensitivity analysis in 18\%. Quality and risk of bias was not reported in 37 studies. Quality measures were articulated in narrative format (47\%) or not at all (40\%). \subsection{\textbf{Conclusions:}}  Quality and risk of bias were assessed in only half of systematic reviews, and even when addressed, methods of assessment are more commonly determined by authors rather than following recommended guidelines. This analysis provides further evidence for inconsistent quality measure reporting for clinical findings in oncology manuscripts. Differences between bias assessment and quality reporting could misdirect intervention results in oncology journals.  \subsection{\textbf{Keywords:}} 
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  \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\%) (48\%)  \ref{fig:FIGURE_3}. Most common tools used were those adapted from other sources (24\%, n=25/91) (29\%, n=25/87)  such as other authors \ref{fig:FIGURE_3}. The second highest used tools were those in which the author independently assessed (21\%, n=19/91) (22\%, n=19/87)  and those that were unspecified (13\%, n=12/91) (14\%, n=12/87)  \ref{fig:FIGURE_3}. QUORUM was Jadad and Newcastle-Ottawa Scale tied for  the fourth highest used tool tools  in Oncology Journals and was used 12\%, n=11/91\ref{fig:FIGURE_3}. 9\%, n=8/87 \ref{fig:FIGURE_3}.  Quality or High Risk of Bias studies were isolated \ref{fig:FIGURE_4}.There were 35 studies in which low quality or high risk of bias were found and included with (76\%, n=35/46) \ref{fig:FIGURE_4}.From included studies, subgroup analysis was conducted in 17\%, n=16/91) \ref{fig:FIGURE_4}. Meta regression was used to address bias and quality problems in 9\% of the 46 articles that assessed quality \ref{fig:FIGURE_4}. Sensitivity analysis was used to address bias and quality reporting issues in 18\% of studies analyzed \ref{fig:FIGURE_4}.   In assessing risk of bias, high/medium/low scale was used most commonly (19\%, n=11/58) followed by high/medium/unclear (14\%, n=8/58), and quality was assessed through author created scales (29\%, n=17/58) and the Jadad scale (16\%, n=9/58) \ref{fig:FIGURE_5}. Low Quality or High risk of bias studies were found in 46 studies out of the 91 studies that assessed quality \ref{fig:FIGURE_5}. There were 37 studies in which it could not be determined whether low quality or high risk of bias studies were isolated. 
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