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Published on: January 7, 2013
Estimating Quality of Life Decrements in Oncology Using Time to Death
Matthijs Versteegh1, Ide van der Helm2, Hamraz Mokri2
1Institute for Medical Technology Assessment, Erasmus University Rotterdam, Rotterdam, The Netherlands.
Objectives:
The estimation of lifetime quality-adjusted life-years (QALYs) requires the extrapolation of both length and quality of life (QoL). The extrapolation of QoL has received little attention in the literature. Here we explore the predictive value of "time to death" (TTD) for extrapolating QoL in oncology.
Methods:
We used QoL and survival data from the Patient Reported Outcomes Following Initial Treatment and Long-Term Evaluation of Survivorship registry, which is linked to The Netherlands Cancer Registry. QoL was assessed with EQ-5D and SF-6D. We tested the relationship between TTD and QoL using linear, 2-part, and beta regression models. Incremental QALYs were compared using the TTD approach and an annual age-related disutility approach using artificial survival data with varying mortality rates.
Results:
A total of 6 samples with >100 patients each were used for the analysis. A declining pattern in QoL was observed when patients were closer to death, confirming the predictive value of TTD for QoL. The declining pattern in QoL was most pronounced when QoL was measured with SF-6D. Proximity to death had a larger impact on QoL than age. Incremental QALYs were higher using the TTD approach than annual age-related disutility, ranging from +0.139 to +0.00003 depending on mortality rates.
Conclusions:
TTD is a predictor variable for QoL. Using TTD allows cost-effectiveness models that lack QoL data to extrapolate morbidity using overall survival estimates. The TTD approach generates more incremental QALYs than an annual age-related disutility, most notably for longer survival periods.
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