Hatswell, Anthony J;
Chaudhary, Mohammad A;
Monnickendam, Giles;
Moreno-Koehler, Alejandro;
Frampton, Katie;
Shaw, James W;
Penrod, John R;
(2023)
Modelling Health State Utilities as a Transformation of Time to Death in Patients with Non-Small Cell Lung Cancer.
PharmacoEconomics
, 42
pp. 109-116.
10.1007/s40273-023-01314-2.
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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) Log (TTD) and 1/TTD 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 Log (TTD) 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.
| Type: | Article |
|---|---|
| Title: | Modelling Health State Utilities as a Transformation of Time to Death in Patients with Non-Small Cell Lung Cancer |
| Location: | New Zealand |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1007/s40273-023-01314-2 |
| Publisher version: | http://dx.doi.org/10.1007/s40273-023-01314-2 |
| Language: | English |
| Additional information: | This article is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License, which permits any non-commercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc/4.0/. |
| Keywords: | Social Sciences, Science & Technology, Life Sciences & Biomedicine, Economics, Health Care Sciences & Services, Health Policy & Services, Pharmacology & Pharmacy, Business & Economics |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences > Dept of Statistical Science |
| URI: | https://discovery-pp.ucl.ac.uk/id/eprint/10187398 |
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