BACKGROUND: Indirect evidence is particularly valuable in health care decision making when direct trial evidence comparing relevant treatments is absent or limited. Current approaches using a predetermined set of comparators in the search query may fail to identify all relevant indirect evidence. PURPOSE: To present a framework for the efficient design of search strategies for identifying clinical trials providing indirect evidence for a treatment comparison. FINDINGS: The authors present 2 search strategies that differ from traditional search strategies in using a series of iterative searches to identify the set of relevant comparators. In both, the comparators included in each search are determined by the results of previous searches. For a given number of searches, the strategies presented will find all indirect comparisons that include a certain number of comparators linking the treatments of interest. Methods of estimating the value of indirect evidence via a given number of comparators linking the treatments of interest are presented, thus allowing the burden of additional searching to be traded off against the likely impact of finding more distant comparisons. A practical illustration of the search strategies in the context of informing a network meta-analysis of second-line treatments for non-small cell lung cancer is presented. CONCLUSIONS: The iterative strategies presented offer a means of identifying such evidence and allow the researcher to determine the optimal scope of the search by estimating the value of additional indirect evidence.