Missing the forest-plot for the trees

Systematic reviews and meta-analyses are methods increasingly used in biomedical research since their introduction in the 1970s. They serve to replace other non-systematic and cherry-picked narrative reviews, which are highly variable in their approach, structure and content. Their increase in popularity parallels the increase in overall scientific output, and when properly conducted, systematic reviews can contribute highly impactful summaries of a fast-growing evidence base. Meta-analyses offer statistical summaries, called forest plots, which similarly provide a powerful synopsis unachievable by individual studies. Thus, it is not difficult to imagine why systematic reviews are published more often. Should scientists be concerned by the accelerated output of research, from systematic reviews or other? If quantity comes at the expense of quality, then yes, of course; but should important manuscripts be rationed out otherwise? A new scientific technique can seem scary at first, especially to the researcher who is unfamiliar with its application or uncertain of its validity. In that case, we should become familiar with new and popular methods, and understand their strengths and limitations. There is a rightful place for systematic reviews and meta-analyses among respectable research tools. Importantly, however, despite standard operating procedures and best practices, the quality of systematic reviews today is highly variable, warranting serious concerns for quantity exceeding quality. Therefore, the appropriate response should be to instil researchers with an appreciation for the complexity of conducting and interpreting a systematic review and meta-analysis, to create more knowledgeable authors, reviewers and editors, who collectively will improve, rather than dismiss, these important scientific contributions.