OBJECTIVES:

Distributional cost-effectiveness analysis (DCEA) facilitates a quantitative assessment of how health effects and costs are distributed between population subgroups, and of any ensuing trade-offs between health maximisation and equity. Implementation of DCEA is currently being explored by the National Institute of Health and Care Excellence (NICE) in the UK. Previous research has established a link between lung cancer and socio-economic status. We aimed to conduct an aggregate DCEA of treatments of lung cancer recommended by NICE and identify key drivers of the analysis.

METHODS:

Population subgroups were defined based on socio-economic deprivation. Data on health benefits, costs and target populations were extracted from two NICE appraisals in lung cancer (atezolizumab and alectinib). Distributions of population health and health opportunity costs were taken from the literature. A social welfare analysis was conducted to assess the trade-off between health maximisation and equity. Sensitivity analyses were conducted varying a range of model parameters.

RESULTS:

The results were sensitive to assumptions around the opportunity cost. Alectinib and atezolizumab were equity improving when opportunity costs were assumed equivalent to the applied NICE cost-effectiveness threshold (£50,000/QALY for atezolizumab and £20,000 to £30,000 for alectinib). Increasing or decreasing the value of the health opportunity costs threshold improved or reduced equity, respectively. Another key driver is the distribution of patients by socio-economic groups; skewing the distribution to most/least deprived improves/reduces the equity gain.

CONCLUSIONS:

This study has demonstrated that alectinib is equity improving, and that atezolizumab has the potential to be equity improving under specific assumptions. Key drivers in the analysis are the incremental costs and QALYs, epidemiological characteristics of the disease and the opportunity cost threshold. Guidance for building DCEAs and transparency on how HTA agencies, such as NICE, would interpret the results and incorporate them in the decision-making would be valuable.