Modelling Health State Utilities as a Transformation of Time to Death in Patients with Non-Small Cell Lung Cancer

Abstract

Background When utilities are analyzed by time to death (TTD), this has historically been implemented by ‘grouping’ observations as discrete time periods to create health state utilities. We extended the approach to use continuous functions, avoiding assumptions around groupings. The resulting models were used to test the concept with data from different regions and different country tariffs. Methods Five-year follow-up in advanced non-small cell lung cancer (NSCLC) was used to fit six continuous TTD models using generalized estimating equations, which were compared with progression-based utilities and previously published TTD groupings. Sensitivity analyses were performed using only patients with a confirmed death, the last year of life only, and artificially censoring data at 24 months. The statistically best-fitting model was then applied to data subsets by region and different EQ-5D-3L country tariffs. Results Continuous (natural) and models outperformed other continuous models, grouped TTD, and progression-based models in statistical fit (mean absolute error and Quasi Information Criterion). This held through sensitivity and scenario analyses. The pattern of reduced utility as a patient approaches death was consistent across regions and EQ-5D tariffs using the preferred model. Conclusions The use of continuous models provides a statistically better fit than TTD groupings, without the need for strong assumptions about the health states experienced by patients. Where a TTD approach is merited for use in modelling, continuous functions should be considered, with the scope for further improvements in statistical fit by both widening the number of candidate models tested and the therapeutic areas investigated. Supplementary Information The online version contains supplementary material available at 10.1007/s40273-023-01314-2.

International Cost-Effectiveness Analysis of Durvalumab in Stage III Non–Small Cell Lung Cancer

“…Our assumed POD1 and POD2 utility of 0.76 aligns well with other disparate estimates in the field, with a meta-analysis citing utility ranges of 0.66 to 0.84 in stage IV NSCLC . Alternative methods that might minimize bias introduction within NSCLC specifically include utilities analyzed by time to death, although this method has not yet gained traction …”

“…46 Alternative methods that might minimize bias introduction within NSCLC specifically include utilities analyzed by time to death, although this method has not yet gained traction. 47 Another major limitation of our model includes the reliance on utilities and QALYs in oncologic cost-effectiveness analyses. While these economic estimates aim to standardize health-state preferences, they inherently vary based on the population of interest.…”