Journal
VALUE IN HEALTH REGIONAL ISSUES
Volume 21, Issue -, Pages 59-65Publisher
ELSEVIER
DOI: 10.1016/j.vhri.2019.07.005
Keywords
cost-effectiveness analysis; quality-adjusted life year; quality of life; survival extrapolation
Funding
- Multidisciplinary Health Cloud Research Program: Technology Development and Application of Big Health Data of Academia Sinica (Taiwan)
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Background: Quality-adjusted life year is widely applied nowadays, which consider both survival and quality of life (QoL). When most diseases are becoming chronic, it is imperative to quantify the overall health impact of a disease in lifetime perspective. Objective: The purpose of this study is to introduce methods for estimating quality-adjusted life expectancy (QALE) and loss of QALE in patients with a disease or specific conditions. Methods: The QALE of an index cohort can be represented as the integration of the product of lifetime survival function and mean QoL function. We introduce a robust extrapolation approach for estimating lifetime survival function and propose an approach for estimating lifetime mean QoL function for studies with limited follow-up. The best part of the proposed method is that the survival data and QoL data can be collected separately. A cohort of patients with a specific condition can be identified by databases that regularly collect data for the control of diseases, and their survival status is verified by linking to a mortality registry. Although nationwide QoL data are not available, researchers can implement a relative short-term follow-up interview on a random sample of patients to collect QoL data. For demonstration, we applied the proposed methods to estimate QALE and loss of QALE of oral cancer patients. Results: The estimates (95% confidence interval) of QALE for oral cancer patients were 11.0 (10.5-11.6) and 14.2 (12.7-15.5) quality-adjusted life years (QALYs) for men and women, respectively. The estimates of loss of QALE for the male and female patients with oral cancer were 14.4 (13.8-14.9) and 7.5 (6.2-9.0) QALYs, respectively. Conclusions: The methods for estimating QALE and loss of QALE can be applied to economic evaluation of cancer control, including screening.
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