Classifying information-sharing methods: a citation-mining systematic review

Abstract

BackgroundSparse relative eectiveness evidence is a frequent problem in Health Technology Assessment(HTA). Where evidence directly pertaining to the decision problem is sparse, it may be feasible to expand theevidence-base to include studies that relate to the decision problem only indirectly: for instance, when there isno evidence on a comparator, evidence on other treatments of the same molecular class could be used;similarly, a decision on children may borrow-strength from evidence on adults. Usually, in HTA, such indirectevidence is either included by ignoring any dierences (`lumping`) or not included at all (`splitting`). However,a range of more sophisticated methods exists, primarily in the biostatistics literature. The objective of thisstudy is identify and classify the breadth of the available information-sharing methods.MethodsForwards and backwards citation-mining techniques were used on a set of seminal papers on thetopic of information-sharing. Papers were included if they specied (network) meta-analytic methods forcombining information from distinct populations, interventions, outcomes or study-designs.Results: Overall, 89 papers were included. A plethora of evidence synthesis methods have been used forinformation-sharing. Most papers (n = 78) described methods that shared information on relative treatmenteects. Amongst these, there was a strong emphasis on methods for information-sharing across multipleoutcomes (n = 39) and treatments (n = 23), with fewer papers focusing on study-designs (n = 10) orpopulations (n = 6). We categorise and discuss the methods under four 'core' relationships ofinformation-sharing: functional, exchangeability-based, prior-based and multivariate relationships, and explainthe assumptions made within each of these core approaches.ConclusionsThis study highlights the range of information-sharing methods available. These methods oftenimpose more moderate assumptions than lumping or splitting. Hence, the degree of information-sharing thatthey impose could potentially be considered more appropriate. Our identication of four `core` methods ofinformation-sharing allows for an improved understanding of the assumptions underpinning the dierentmethods. Further research is required to understand how the methods dier in terms of the strength of sharingthey impose and the implications of this for health care decisions.