Quantifying the advantages of conducting a prospective meta-analysis (PMA): a case study of early childhood obesity prevention

Abstract

BackgroundFor prospective meta-analyses (PMAs), eligible studies are identified, and the PMA hypotheses, selection criteria, and analysis methods are pre-specified before the results of any of the studies are known. This reduces publication bias and selective outcome reporting and provides a unique opportunity for outcome standardisation/harmonisation. We conducted a world-first PMA of four trials investigating interventions to prevent early childhood obesity. The aims of this study were to quantitatively analyse the effects of prospective planning on variations across trials, outcome harmonisation, and the power to detect intervention effects, and to derive recommendations for future PMA.MethodsWe examined intervention design, participant characteristics, and outcomes collected across the four trials included in the EPOCH PMA using their registration records, protocol publications, and variable lists. The outcomes that trials planned to collect prior to inclusion in the PMA were compared to the outcomes that trials collected after PMA inclusion. We analysed the proportion of matching outcome definitions across trials, the number of outcomes per trial, and how collaboration increased the statistical power to detect intervention effects.ResultsThe included trials varied in intervention design and participants, this improved external validity and the ability to perform subgroup analyses for the meta-analysis. While individual trials had limited power to detect the main intervention effect (BMI z-score), synthesising data substantially increased statistical power. Prospective planning led to an increase in the number of collected outcome categories (e.g. weight, child's diet, sleep), and greater outcome harmonisation. Prior to PMA inclusion, only 18% of outcome categories were included in all trials. After PMA inclusion, this increased to 91% of outcome categories. However, while trials mostly collected the same outcome categories after PMA inclusion, some inconsistencies in how the outcomes were measured remained (such as measuring physical activity by hours of outside play versus using an activity monitor).ConclusionProspective planning led to greater outcome harmonisation and greater power to detect intervention effects, while maintaining acceptable variation in trial designs and populations, which improved external validity. Recommendations for future PMA include more detailed harmonisation of outcome measures and careful pre-specification of analyses to avoid research waste by unnecessary over-collection of data.