Presentation (CTI)

OBJECTIVES: In health economic evaluations for oncology indications, partitioned survival models (PSMs) are commonly used as a standard approach. PSMs enable the capturing of disease progression and outcomes over time. There are variations in how models are structured, inputs are defined, and assumptions are considered across health technology assessments (HTAs) for National Institute for Health Care Excellence (NICE). To reduce the challenges caused by such heterogeneity, a consistent and efficient way of developing economic evaluations is necessary. We aim to develop a transparent and flexible PSM template that accommodates a wide range of methodologies used in the oncology HTA submissions and support the development of PSM models in a transparent and consistent way.
METHODS: We conducted a targeted review of recent PSMs submitted to NICE focusing on capturing key parameters such as health states definitions, survival extrapolation, cure assumptions, costs, adverse events and disutilities. This helped in creating a customisable template that integrates multiple modelling options with a standardised approach, allowing users to switch between different functionalities and assumptions with minimal reprogramming of the model.
RESULTS: The resulting PSM template incorporates a consistent framework for defining assumptions and specifying model inputs. Functionalities for accommodating various approaches to include survival parameters, treatment posology, on-treatment status, subsequent treatments, adverse events, disutility, cure parameters, and cost data were included, in addition to flexibility on how inputs are allocated to health states and/or transitions. The template integrates validation checks, one- and two-way sensitivity analysis, probabilistic sensitivity analyses, and the ability to conduct scenario analyses. The key findings are displayed through the dashboard's target product profile to give a comprehensive overview.
CONCLUSIONS: This PSM provides a consistent framework for streamlining oncology economic evaluations, offering a clear and customisable platform, promoting a transparent approach to demonstrating the economic value of treatments for patients.