OBJECTIVES: An increasing number of oncology drugs are licensed for multiple indications. Currently, health technology assessment (HTA) bodies appraise the use of a drug in each indication, ignoring evidence available on the same drug in other indications. However, evidence from other indications could reduce the high levels of uncertainty characteristic of the available indication-specific data, which at the time of appraisal is typically immature and imprecise. Using bevacizumab as a case-study, we explore methods to present and summarise evidence in multi-indication oncology HTA, creating visual maps that can be used to present the accumulation of evidence across multiple indications to inform policy-makers, support evidence synthesis approaches, or to guide expert elicitation.

METHODS: We identified randomised controlled trial evidence for 11 cancer indications where bevacizumab has been approved. We reviewed existing literature on the visualisation of complex evidence and explored methods to represent the precision and maturity of evidence across indications. Based on these reviews, we developed new evidence maps to help visualise the evolution of relative effectiveness evidence on bevacizumab over time, both within and between oncology indications.

RESULTS: The evidence maps developed for bevacizumab enable complex patterns in study-level evidence to be easily visualised and updated as evidence accumulates over time. We constructed bubble plots with multiple dimensions to display important features of oncology data that have not been adequately addressed by existing literature. We also developed displays of the evidence pooled across studies over time (meta-analysed), within and between-indications.

CONCLUSIONS: Improved displays of evidence are a first step towards the development of multi-indication evidence synthesis methods and more efficient use of information for HTA. A clear graphical representation of how evidence accumulates provides a better understanding of the entire evidence base for a product which can inform judgements concerning the appropriate use of data across indications.