Literature DB >> 31655464

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

Chia-Hua Chung1, Tsuey-Hwa Hu1, Jung-Der Wang2, Jing-Shiang Hwang3.   

Abstract

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.
Copyright © 2019 ISPOR--The professional society for health economics and outcomes research. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  cost-effectiveness analysis; quality of life; quality-adjusted life year; survival extrapolation

Mesh:

Year:  2019        PMID: 31655464     DOI: 10.1016/j.vhri.2019.07.005

Source DB:  PubMed          Journal:  Value Health Reg Issues        ISSN: 2212-1099


  3 in total

1.  Estimation of losses of quality-adjusted life expectancy attributed to the combination of cognitive impairment and multimorbidity among Chinese adults aged 45 years and older.

Authors:  Suting Xiong; Siyuan Liu; Yanan Qiao; Dingliu He; Chaofu Ke; Yueping Shen
Journal:  BMC Public Health       Date:  2021-01-05       Impact factor: 3.295

2.  Survival-Weighted Health Profiles in Patients Treated for Advanced Oral Cavity Squamous Cell Carcinoma.

Authors:  Yao-Te Tsai; Wen-Cheng Chen; Cheng-Ming Hsu; Ming-Shao Tsai; Geng-He Chang; Yi-Chan Lee; Ethan I Huang; Chiung-Cheng Fang; Chia-Hsuan Lai
Journal:  Front Oncol       Date:  2021-09-29       Impact factor: 6.244

3.  Optimal Intervals of Ultrasonography Screening for Early Diagnosis of Hepatocellular Carcinoma in Taiwan.

Authors:  Shih-Chiang Kuo; Chia-Ni Lin; Yih-Jyh Lin; Wei-Ying Chen; Jing-Shiang Hwang; Jung-Der Wang
Journal:  JAMA Netw Open       Date:  2021-06-01
  3 in total

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