Sparse 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 the
evidence-base to include studies that relate to the decision problem only indirectly: for instance, when there is
no 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 indirect
evidence 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 this
study is identify and classify the breadth of the available information-sharing methods.
Forwards and backwards citation-mining techniques were used on a set of seminal papers on the
topic of information-sharing. Papers were included if they speci ed (network) meta-analytic methods for
combining information from distinct populations, interventions, outcomes or study-designs.
Results: Overall, 89 papers were included. A plethora of evidence synthesis methods have been used for
information-sharing. Most papers (n = 78) described methods that shared information on relative treatment
eects. Amongst these, there was a strong emphasis on methods for information-sharing across multiple
outcomes (n = 39) and treatments (n = 23), with fewer papers focusing on study-designs (n = 10) or
populations (n = 6). We categorise and discuss the methods under four 'core' relationships of
information-sharing: functional, exchangeability-based, prior-based and multivariate relationships, and explain
the assumptions made within each of these core approaches.
This study highlights the range of information-sharing methods available. These methods often
impose more moderate assumptions than lumping or splitting. Hence, the degree of information-sharing that
they impose could potentially be considered more appropriate. Our identi cation of four `core` methods of
information-sharing allows for an improved understanding of the assumptions underpinning the dierent
methods. Further research is required to understand how the methods dier in terms of the strength of sharing
they impose and the implications of this for health care decisions.