Treatment comparisons for decision making: Facing the problems of sparse and few data

Advanced evidence synthesis techniques such as indirect or mixed treatment comparisons provide powerful analytic tools to inform decision making. In some cases, however, existing research is limited in quantity and/or existing research data are 'sparse'. We demonstrate how modelling assumptions in evidence synthesis can be explored in the face of limited and sparse data by using an example where estimates of relative treatment effects were required in a synthesis of the available evidence regarding treatments for grade 3 or 4 pressure ulcers.