Answer to the Letter to the Editor of Mingbo Tian et al. concerning “Body mass index and risk of surgical site infection following spine surgery: a meta-analysis” by D.Y. Abdallah, M.M. Jadaan and J.P. McCabe; Eur Spine J, doi:10.1007/s00586-013-2890-6

Abstract

We would like to respond to the Letter to the Editor concerning our meta-analysis [1].For the electronic search, we used PubMed, which provides a search interface to Medline, and Embase. These two search engines complement each other [2], and, in addition to CENTRAL, contain the largest number of studies according to the Cochrane Handbook of Systematic Reviews of interventions [3]. We did not search CEN-TRAL, as the focus of our research was on observational studies. The search, supplemented by screening of reference lists, identified 34 studies relevant to our research question, which is not a small number. However, it was not appropriate to pool results from all 34 studies. It is not uncommon to pool results from \10 studies. Between 50 and 75 % of meta-analyses contain \10 studies, including Cochrane reviews [4,5]. While we know that a single search engine does not yield all pertinent studies, we are not aware of guidelines that specify at least three databases to be searched. Nevertheless, during literature search we used Google Scholar to identify additional studies. Despite the large number of results, the search did not yield relevant studies beyond those already identified. We did not formally include Google Scholar, as the search engine has low specificity and does not utilise controlled vocabulary relevant to the research question [6].Ideally, to circumvent the problem of publication bias, a meta-analysis should include unpublished literature and non-English language studies, but this is not always feasible and is a limitation of many published meta-analyses, not only ours. We conducted a formal assessment of publication bias using more than one method and did not rely on visual inspection of funnel plots. Applying these methods when the number of studies is small is not wrong, but has limited power [4]. We reported the results of these tests and were careful in our interpretations by acknowledging the low power of Egger's test. We never claimed that there was no publication bias, and we stated that ''we were unable to reliably assess the presence of publication bias due to the small number of studies included'' [1]. We would also like to draw the attention of the writers of the Letter that we explicitly discussed English language bias and the potential over-estimation of results in the discussion section.In relation to assessment of study quality, first, we assigned the 'level of evidence' to each study, which is a ''hierarchical rating system for classifying study quality'' [7]. It is a well-established scoring system and is used by several journals. Second, to minimise bias, we used several inclusion criteria, and listed all excluded studies as well as the reasons for their exclusion. We reported all information that would potentially introduce bias, such as study design, categorisation of BMI, and adjustment for confounders. No subjectivity was involved in extracting the data. Therefore, data extraction was reviewed by the second author to ensure correctness rather than any other degree of agreement...