Assessing cost-effectiveness in oncology treatment sequences: a review of pathway modeling methods for health technology assessment.

Abstract

Objectives: Pathway models incorporate multiple decision nodes to assess the most cost-effective sequence or the optimal point of introduction of a new technology within a treatment pathway. Pathway models are particularly useful in disease areas such as oncology, where patients may have several lines of therapy. We aimed to review methodologies for modeling and evidence synthesis in pathway models that evaluate the cost-effectiveness of treatment strategies within oncology.

Methods: We designed a search to identify relevant methodological papers and systematic reviews of oncology pathway models that critique their methodological approaches. We also updated a previous review of studies on methods for evidence synthesis to inform pathway models. Best practice recommendations were extracted and summarized.

Results: Nine and five studies were included on methods for model structures and evidence synthesis, respectively. Key themes related to data requirements, including a preference for patient-level model structures and data from multi-line sources. There was limited guidance on alternative model structures in the absence of patient-level data. Multi-state network meta-analysis with flexible survival models was the most appropriate method identified for evidence synthesis; however, due to data limitations, it may be necessary to conduct separate syntheses at each line of therapy.

Conclusions: Data limitations may reduce the potential benefits of pathway models. Further method development is needed for pathway models in decision spaces where individual patient data and sources that cover multiple lines of treatment are not available.