Estimation of Quality-Adjusted Life Expectancy of Patients With Oral Cancer: Integration of Lifetime Survival With Repeated Quality-of-Life Measurements

• Published in: Value in health regional issues Vol. 21; pp. 59 - 65
• Main Authors: Chung, Chia-Hua, Hu, Tsuey-Hwa, Wang, Jung-Der, Hwang, Jing-Shiang
• Format: Journal Article
• Language: English
• Published: United States Elsevier Inc 01.05.2020
• Subjects: Cohort Studies; cost-effectiveness analysis; Female; Humans; Life Expectancy; Male; Middle Aged; Mouth Neoplasms - complications; Mouth Neoplasms - epidemiology; Mouth Neoplasms - mortality; quality of life; Quality of Life - psychology; quality-adjusted life year; Quality-Adjusted Life Years; Survival Analysis; survival extrapolation; cost-effectiveness analysis; quality of life; quality-adjusted life year; survival extrapolation
• ISSN: 2212-1099; 2212-1102
• DOI: 10.1016/j.vhri.2019.07.005

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. 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. 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. 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. The methods for estimating QALE and loss of QALE can be applied to economic evaluation of cancer control, including screening. •Quality-adjusted life expectancy (QALE) is currently widely applied in cost-effectiveness analysis, which considers both survival and quality of life (QoL). When most diseases become chronic, it is imperative to quantify the overall health impact of a disease in lifetime perspective.•Both survival function and mean QoL function for estimating the QALE are required extrapolations beyond the maximum follow-up time. This study introduces a robust survival extrapolation method and proposes a method for estimating lifetime mean QoL function when QoL measurements assessed prior to death are available. We applied the methods to real-world data of oral cancer patients registered in Taiwan to quantify the health impact and burden of the disease.