OBJECTIVES:

Follicular lymphoma (FL) is the commonest indolent lymphoma, with ~1,860 new-cases diagnosed each year in the UK. Clinical management ranges from immediate treatment with chemotherapy and/or radiotherapy, to observation ("watch-and-wait”); initiating treatment if/when symptoms develop. Previous studies have focussed on clinical trial data for specific drugs, meaning that their findings cannot be extrapolated to the general patient-population. Based on a population-based patient-cohort, the objective of this study was to develop a generic and flexible decision model to reflect real-world practice and predict cost, survival and quality-adjusted life years (QALY) for different scenarios.

METHODS:

Patients newly diagnosed 2004-11 with FL in the UK’s population-based Haematological Malignancy Research Network (www.hmrn.org) were followed until 2015 (n=740). Mapped treatment pathways, QALYs, and cost information, were incorporated into a discrete event simulation that reflected patient heterogeneity, including age and treatment options. Two scenarios based on latest NICE guidelines (www.nice.org.uk/guidance/ng52 and TA226) were conducted.

RESULTS:

The annual cost of treating FL across the UK was around ~£55 million. The predicted mean cost and QALY per patient from diagnosis to death were £24,872 and 9.72 for those treated with curative intent (69%), £5,296 and 8.21 for those managed by “watch-and-wait” throughout (29%), and £6,165 and 0.1 for those who only received palliative care (2%). Scenario analyses demonstrated that the cost of introducing frontline and maintenance rituximab to all patients would be ~£5.7 and £6.7 million/year respectively, but the potential saving based on the improved outcomes could be in the region of £6-10 million (induction) and £14-18 million (maintenance) a year.

CONCLUSIONS:

This is the first modelling study to use ‘real-world’ evidence to predict costs of entire FL treatment pathways and permit scenario analyses at any part of the pathway. Future application of the model could support healthcare policy-making and the introduction of new drugs such as biosimilars.