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Comment on: waist‐to‐height ratio, body mass index and waist circumference for screening paediatric cardio‐metabolic risk factors: a meta‐analysis

Dear Editor I have read the recent meta-analysis by Lo et al. (1) published online the July 25th 2016 issue of Obesity Reviews, with great interest. In this review, the authors performed a comprehensive literature search and proceeded to evaluate the discriminatory power of three obesity indices for cardiometabolic risk factors in children and adolescents. Unfortunately, the validity of their conclusion simply based on the area under curve (AUC) is questionable because the statistical method involved in this meta-analysis was not suitable. With use of QUADAS-2 form for the quality of the included studies, the meta-analysis of Lo et al. is more likely to be a meta-analysis of diagnostic accuracy studies (2). This kind of meta-analysis is different from the meta-analysis of therapeutic/interventional studies, and is characterized by two important features: a negative correlation between sensitivity and specificity and a substantial between-study heterogeneity in paired indices (3,4). Considering this, the present meta-analysis includes two major methodological constraints. First, the authors used a single measure of diagnostic accuracy to evaluate the discriminatory power of three obesity indices for identifying cardio-metabolic risk factors. The disadvantage of using a single measure is that it does not distinguish between the ability of detecting the sick (sensitivity) and identifying the well (specificity). Moreover, although it is possible to pool diagnostic accuracy parameters from separate conventional ‘univariate’ randomeffects meta-analyses, this separate pooling method is applicable only if there is evidence of no correlation between sensitivity and specificity across studies, a condition that is highly unlikely to arise in practice (3). Second, the authors used the inverse variance method for pooling the AUC for each study, and this approach was not appropriate for meta-analysis of diagnostic accuracy studies. Actually, the most recommended and rigorous approaches are the hierarchical summary receiver operating characteristic model and bivariate random effects metaanalysis on sensitivities and specificities (5–7). Both approaches enable to take into account any correlation between sensitivity and specificity, then the parameter estimates from either model can be used to produce a summary operating point, an SROC curve, confidence regions or prediction regions. In conclusion, the excellent work of Lo et al. is to be appreciated for addressing an interesting and highly relevant topic. However, owing to the methodological limitations, the conclusion made by this meta-analysis should be interpreted cautiously, and especially the strength of the evidence raised should be reconsidered.