Does Classification of Composites for Network Meta-analyses Lead to Erroneous Conclusions?

Abstract

Composites can be classified differently, according to manufacturer information, filler particle size, resin-monomer base, or viscosity, for example. Using clinical trial data, network meta-analyses aim to rank different composite material classes. Dentists then use these ranks to decide whether to use specific materials. Alternatively, annual failure rates (AFRs) of materials can be assessed, not requiring any classification for synthesis. It is unclear whether different classification systems lead to different rankings of the same material (ie, erroneous conclusions). We aimed to evaluate the agreement of material rankings between different classification systems. A systematic review was performed via MEDLINE, Cochrane Central Register of Controlled Trials, and EMBASE. Randomized controlled trials published from 2005-2015 that investigated composite restorations placed in load-bearing cavitated lesions in permanent teeth were included. Network meta-analyses were performed to rank combinations of composite classes (according to manufacturer, filler particle size, resin-monomers, viscosity) and adhesives. Material combinations were additionally ranked using AFRs. A total of 42 studies (6088 restorations, 2325 patients) were included. The ranking of most material class combinations showed significant agreement between classifications ( R2 ranged between 0.03 and 0.56). Comparing material combinations using AFRs had low precision and agreement with other systems. AFRs were significantly correlated with follow-up periods of trials. There was high agreement between rankings of identical materials in different classification systems. Such rankings thus allow cautious deductions as to the performance of a specific material. Syntheses based on AFRs might lead to erroneous results because AFRs are determined by follow-up periods and have low precision.