BACKGROUND: Head-to-head trials are rarely conducted for orphan drugs due to ethical reasons and the desire to maximize the statistical power of results. However, decision making is challenging when comparative data doesn’t exist. Innovative modelling methods are therefore required to estimate incremental efficacy from single-arm trial data.

AIM: We sought to investigate how incremental efficacy is estimated in partition survival modelling in the absence of comparative data, the limitations of the methods used and whether RWE is used to bridge the gaps of traditional methods. We conducted a search of HTA submissions and manuscripts for methods used, noting the strengths and weaknesses of the methodologies discussed. We identify and discuss the limitations of the methods most commonly listed and determine when and how RWE has been used. Whether RWE replaces methods using literature sourced data, or whether it is used to provide additional validity to other methods.

CONCLUSIONS: The historical control method is most commonly used to estimate incremental efficacy in the absence of comparative data. This method involves pooling published trial data (after the digitization of their Kaplan-Meier). The major limitation of this method is considered to be the potential for bias if populations between trials vary, which in turn raises the question of the appropriateness of pooling. RWE has rarely been used to estimate comparator efficacy in partition survival modelling. This is generally because efficacy estimates derived from RWE are highly subject to quality and quantity of the data, effecting the robustness and generalisability of results. There is also a risk of bias when comparing evidence from a real world to controlled trial setting. In order to aid decision making, a scenario using estimates derived from RWE in addition to a historical control derived base-case could be provided to strengthen the robustness of results when modelling single-arm trials.