A systematic review of the applications of the real option value of medical technologies in oncology.

Background: Real option value (ROV) offers an innovative paradigm to evaluate the dynamic value of medical technologies, particularly in cancer, by capturing the value of extending patient survival to access future innovations. Despite its potential, the application of ROV in medical technologies in oncology remains underexplored.

Objective: To synthesize existing evidence on the application of ROV in medical technologies in oncology.

Methods: A comprehensive search of PubMed, ScienceDirect, and Web of Science was conducted to identify peer-reviewed studies published in English from January 2000 to May 2024. In the search query, a combination of keywords related to "real option value" and "cancer" was used. Key data extracted included study characteristics, objectives, ROV modeling technique, and primary findings. The Consolidated Health Economic Evaluation Reporting Standards 2022 checklist was used for quality assessment of the studies.

Results: A total of 13 of 165 studies assessed the ROV of medical therapies, with a primary focus on melanoma, lung cancer, and prostate cancer. ROV was modeled from the ex post and ex ante perspectives. The methodologies employed vary, with common forecasting approaches including the Lee-Carter model to project future decreases in mortality rates, fitting Cox proportional regression models on administrative claims data, or estimating the approval likelihood of early pipeline drugs based on data from early randomized clinical trials.

Conclusions: The ROV represents a critical dimension in evaluating medical technologies in oncology, where innovation is rapid. The implications of ROV extend beyond oncology, with the potential to influence funding, pricing, and access decisions in other disease areas as well. However, challenges such as oversimplification of assumptions for forecasting, methodological consistency, and lack of standardized framework remain pervasive. This systematic review underscores the need to integrate ROV into Health Technology Assessment practices to inform resource allocation and policy decisions.